# Dock

> The AI workspace for you, your team, and every agent you run. Shared cloud workspaces where humans and AI agents read and write the same state in real time. Each workspace is a container of one or more surfaces (tabs); a surface is either a typed-row table or a TipTap rich-text doc, and a workspace can hold any combination, one or many of either kind — structured state and narrative, side by side. Agents are first-class identities with their own API keys.

## Why this exists

AI's recent leap came through the terminal, so agent work has been stuck on whichever machine it ran on. That worked while AI was one person at one terminal. It stops working the moment AI is plural — many agents, several people, continuous output, all of it needing to be in the same place at the same time. Dock is the shared, persistent state layer where humans and agents both work as first-class actors. The era is what we call [Cloud 2.0](https://trydock.ai/blog/cloud-2-0); Dock is the first cloud built to it.

## What Dock is, what it isn't

Dock is:

- A cloud-hosted shared workspace, not a per-machine local protocol — humans, including non-technical teammates, work in the same UI as agents.
- Multi-surface — typed-row tables (status/owner/date/url/etc), TipTap rich-text docs (with mermaid + math + GFM callouts), files, and threaded comments. State is rich, not just messages and tasks.
- Agent-native by design — every agent is a named principal with its own `dk_` API key, its own attribution on every write, and access derived from the human who owns it.
- Real-time across actors — presence and writes propagate to every viewer of a workspace within about a second; multiple humans + agents stay in sync on the same surface without polling.
- Open to every model vendor — same workspace, same MCP server, same REST API, regardless of whether the agent is on Claude, OpenAI, a self-hosted model, or a framework like LangGraph / Mastra / CrewAI / AutoGen.

Dock is not:

- A hosted-GPU service or a model-inference platform — bring your own model, your own LLM bill.
- A chat-only assistant or a single-vendor copilot — the workspace is the substrate, the conversation is one surface among several.
- A code editor with AI added — Dock is for the durable work agents and teams collaborate on, not the keystroke-level code path.
- A managed pipeline orchestrator — agents trigger Dock, not the other way around.

## Pricing

Three plans. One row per plan. Caps are read from `src/lib/plan-caps.ts` so this never drifts from enforcement.

| Plan | Price | Agents | Members | Workspaces | Rows / workspace |
| --- | --- | --- | --- | --- | --- |
| Free  | $0       | 3  | 6  | 20    | 500 |
| Pro   | $19/mo   | 10   | 20   | 200    | 5,000 |
| Scale | $49/mo   | 30 | 60 | 1000    | 50,000 |

Output-first, not seat-first: caps are on agents + members + workspaces + rows, not per-user-per-month. One human can run several agents under one plan. Need more than Scale gives? Ping us via `create_support_ticket` (MCP) or the contact link at https://trydock.ai/pricing — limit increases are a quick conversation, not a sales motion.

## Start in 30 seconds

If you are an agent reading this and your human has a Dock account:

1. Get the human to create an agent at https://trydock.ai/agents — that yields a `dk_<48 hex>` API key bound to them.
2. `export DOCK_API_KEY=dk_…`
3. `npx -y @trydock/cli@latest whoami` — should print "Name · agent" within a second.
4. Add the MCP server (`https://trydock.ai/api/mcp`) to your config and you have 64 tools on the workspace.
5. For paste-in operating instructions, fetch https://trydock.ai/llms-full.txt.

If you are an agent reading this on behalf of a human who does not have an account, the human signs up at https://trydock.ai/signup (60 seconds, Google or email) and steps 1-5 follow.

## Core

- [Quickstart](https://trydock.ai/docs/quickstart): zero to a shared workspace in 60 seconds (CLI or browser).
- [Concepts](https://trydock.ai/docs/concepts): org, workspace, surface, row, agent, member, event. The domain model in one page.
- [MCP server](https://trydock.ai/docs/mcp/overview): 64 tools, OAuth 2.1 + DCR. Endpoint: https://trydock.ai/api/mcp
- [REST API](https://trydock.ai/docs/api/overview): all endpoints, Bearer auth, `x-request-id` on every response.
- [Error codes](https://trydock.ai/docs/api/errors): every error shape with cause and fix, anchored per code.
- [Agent primer](https://trydock.ai/llms-full.txt): paste-in instructions for agents operating Dock.

## Setup per client

One page per client. Every page has exact config file paths, verification commands, and troubleshooting.

- [Claude Code](https://trydock.ai/docs/agents/native/claude-code), [Claude Cowork](https://trydock.ai/docs/agents/native/claude-cowork), [Claude Desktop](https://trydock.ai/docs/agents/native/claude-desktop), [Claude.ai web](https://trydock.ai/docs/agents/native/claude-web)
- [Cursor](https://trydock.ai/docs/agents/native/cursor), [Windsurf](https://trydock.ai/docs/agents/native/windsurf), [Zed](https://trydock.ai/docs/agents/native/zed), [Cline](https://trydock.ai/docs/agents/native/cline), [Continue](https://trydock.ai/docs/agents/native/continue), [Aider](https://trydock.ai/docs/agents/native/aider), [GitHub Copilot](https://trydock.ai/docs/agents/native/github-copilot), [JetBrains AI](https://trydock.ai/docs/agents/native/jetbrains-ai), [Amazon Q](https://trydock.ai/docs/agents/native/amazon-q), [Kiro](https://trydock.ai/docs/agents/native/kiro), [Sourcegraph Cody](https://trydock.ai/docs/agents/native/sourcegraph-cody), [Tabnine](https://trydock.ai/docs/agents/native/tabnine), [Supermaven](https://trydock.ai/docs/agents/native/supermaven)
- [ChatGPT](https://trydock.ai/docs/agents/native/chatgpt), [Gemini CLI](https://trydock.ai/docs/agents/native/gemini-cli), [Codex CLI](https://trydock.ai/docs/agents/native/codex), [OpenClaw](https://trydock.ai/docs/agents/native/openclaw), [Warp](https://trydock.ai/docs/agents/native/warp), [Raycast AI](https://trydock.ai/docs/agents/native/raycast)
- [LibreChat](https://trydock.ai/docs/agents/local-uis/librechat), [Open WebUI](https://trydock.ai/docs/agents/local-uis/open-webui), [AnythingLLM](https://trydock.ai/docs/agents/local-uis/anythingllm), [Ollama](https://trydock.ai/docs/agents/local-uis/ollama)
- [LangChain](https://trydock.ai/docs/agents/frameworks/langchain), [LangGraph](https://trydock.ai/docs/agents/frameworks/langgraph), [Mastra](https://trydock.ai/docs/agents/frameworks/mastra), [CrewAI](https://trydock.ai/docs/agents/frameworks/crewai), [AutoGen](https://trydock.ai/docs/agents/frameworks/autogen), [Semantic Kernel](https://trydock.ai/docs/agents/frameworks/semantic-kernel), [Pydantic AI](https://trydock.ai/docs/agents/frameworks/pydantic-ai), [Agno](https://trydock.ai/docs/agents/frameworks/agno), [LlamaIndex](https://trydock.ai/docs/agents/frameworks/llamaindex), [Vercel AI SDK](https://trydock.ai/docs/agents/frameworks/vercel-ai-sdk), [OpenAI Agents SDK](https://trydock.ai/docs/agents/frameworks/openai-agents-sdk), [Anthropic SDK](https://trydock.ai/docs/agents/frameworks/anthropic-sdk), [MCP TS SDK](https://trydock.ai/docs/agents/frameworks/mcp-typescript-sdk), [MCP Python SDK](https://trydock.ai/docs/agents/frameworks/mcp-python-sdk)
- [Dify](https://trydock.ai/docs/agents/no-code/dify), [Langflow](https://trydock.ai/docs/agents/no-code/langflow), [Flowise](https://trydock.ai/docs/agents/no-code/flowise), [n8n](https://trydock.ai/docs/agents/no-code/n8n), [Zapier](https://trydock.ai/docs/agents/no-code/zapier)
- [Bolt.new](https://trydock.ai/docs/agents/builders/bolt), [v0](https://trydock.ai/docs/agents/builders/v0), [Lovable](https://trydock.ai/docs/agents/builders/lovable), [Replit Agent](https://trydock.ai/docs/agents/builders/replit), [Devin](https://trydock.ai/docs/agents/builders/devin)
- [curl / bash](https://trydock.ai/docs/agents/from-scratch/curl), [Python](https://trydock.ai/docs/agents/from-scratch/python), [Node.js](https://trydock.ai/docs/agents/from-scratch/nodejs)

Full catalogue: https://trydock.ai/docs/agents

## Concepts

- [Agent overview](https://trydock.ai/docs/agents/agent-overview): identity, ownership, color, role, API keys.
- [Signed-agent inheritance](https://trydock.ai/docs/agents/agent-inheritance): how an agent's owning user determines workspace access.
- [Agent attribution](https://trydock.ai/docs/agents/agent-attribution): every write stamps a principal pair.
- [API authentication](https://trydock.ai/docs/api/auth): Bearer keys + OAuth.
- [MCP OAuth + DCR](https://trydock.ai/docs/mcp/oauth): self-registering MCP clients.
- [Dangerous-ops handshake](https://trydock.ai/docs/mcp/dangerous-ops): two-call confirm pattern for plan flips.
- [Sharing & roles](https://trydock.ai/docs/web/sharing): Owner / Editor / Commenter / Viewer; visibility model.
- [Teams](https://trydock.ai/docs/web/teams): multi-org membership; active-org switching.

## Templates

92 forkable workspace templates. Each opens as a remixable Dock workspace with prefilled surfaces and an agent-ready brief at `/templates/<slug>`. Long-tail how-to guides ship a HowTo + FAQPage JSON-LD payload alongside the visible body.

Listing: https://trydock.ai/templates

### Build (26)

- [Launch your iPhone app on the App Store](https://trydock.ai/templates/launch-iphone-app-on-the-app-store): 10-step plan from 'I have a build on my Mac' to 'users are downloading from search.' Real Apple gates, real gotchas, real agent prompts.
- [Build a webapp in a day](https://trydock.ai/templates/build-a-webapp-in-a-day): 10-step plan from blank idea to deployed app with auth, a database, and a domain — all in 24 hours. Battle-tested defaults so you don't waste 6 hours picking a stack.
- [Launch your Android app on Google Play](https://trydock.ai/templates/launch-android-app-on-google-play): 10-step plan from 'I have an APK on my laptop' to 'users are installing from Play search.' Real Google gates, real gotchas, real agent prompts.
- [Ship a Chrome extension to the Web Store](https://trydock.ai/templates/ship-a-chrome-extension): 9-step plan from 'unpacked extension on my laptop' to 'live in the Chrome Web Store.' Real MV3 gotchas, real review traps, real agent prompts.
- [Ship a VS Code extension to the Marketplace](https://trydock.ai/templates/ship-a-vscode-extension): 9-step plan from 'F5 to debug' to 'live in the VS Code Marketplace and Open VSX.' Real publisher gotchas, real activation traps, real agent prompts.
- [Build a Discord bot and verify it](https://trydock.ai/templates/build-a-discord-bot): 10-step plan from 'create application in Dev Portal' to 'verified bot serving 100+ servers.' Real intent gates, real verification gotchas, real agent prompts.
- [Build a Slack app and submit to the Slack Marketplace](https://trydock.ai/templates/build-a-slack-app): 10-step plan from 'manifest.yml on my laptop' to 'live in the Slack Marketplace.' Real OAuth gotchas, real review traps, real agent prompts.
- [Ship a CLI tool to npm with semver releases](https://trydock.ai/templates/ship-a-cli-tool-to-npm): 9-step plan from 'index.js on my laptop' to 'npx my-cli with semver-released versions on every merge.' Real bin gotchas, real release traps, real agent prompts.
- [Build a desktop app with Electron in a week](https://trydock.ai/templates/build-a-desktop-app-with-electron): 10-step plan from 'npx create-electron-app' to 'signed installer with auto-update on macOS + Windows.' Real notarization gotchas, real cert traps, real agent prompts.
- [Build a Progressive Web App that installs to the home screen](https://trydock.ai/templates/build-a-progressive-web-app): 9-step plan from 'I have a webapp' to 'installable PWA with offline mode + push.' Real iOS quirks, real service worker traps, real agent prompts.
- [Set up SEO foundations for a new product](https://trydock.ai/templates/set-up-seo-foundations-for-a-new-product): 12-step plan for the technical + content SEO foundations that compound: site architecture, schema, content map, then the first 30 indexed pages.
- [Ship a podcast from idea to RSS feed](https://trydock.ai/templates/ship-a-podcast-from-idea-to-rss-feed): 11-step plan from premise to live RSS feed in Apple Podcasts + Spotify, with the gear, the editing, and the agent-assisted show notes.
- [Set up SOC 2 readiness](https://trydock.ai/templates/set-up-soc-2-readiness): 10-step plan from 'enterprise prospects keep asking for SOC 2' to 'Type 1 report in hand, Type 2 evidence accruing.' Your agents draft the policies, surface scope, run the evidence cadence.
- [Set up GDPR compliance for a SaaS](https://trydock.ai/templates/gdpr-compliance-for-saas): 10-step plan from 'we have EU users now' to 'Article 30 records, DPAs signed, DSAR process tested.' Real EU rules, real templates, real costs.
- [Write your Terms of Service and Privacy Policy](https://trydock.ai/templates/write-terms-of-service-and-privacy-policy): 8-step plan: from 'I need legal docs by launch' to 'ToS + privacy + DPA + cookie banner live, all matching what your code actually does.'
- [Set up Stripe billing for a SaaS subscription](https://trydock.ai/templates/set-up-stripe-billing-for-saas): 10-step plan from 'I created a Stripe account' to 'subscriptions running in prod with webhooks reconciled, taxes calculated, dunning live.'
- [Set up a status page for your SaaS](https://trydock.ai/templates/set-up-status-page-for-saas): 8-step plan from 'we don't have a status page' to 'status.yourdomain.com live with auto-probes, subscribers, incident templates.'
- [Set up CI/CD for a Next.js app on Vercel + GitHub](https://trydock.ai/templates/set-up-ci-cd-for-nextjs): 10-step plan for a Next.js CI/CD pipeline that catches bugs before main: typecheck, lint, tests, preview deploys, branch protection, prod gates.
- [Set up observability: logs, metrics, traces](https://trydock.ai/templates/set-up-observability): 9-step plan for the three pillars of observability (logs, metrics, traces) at a level a 1-5 person team can adopt in a week.
- [Set up multi-region for a Postgres app](https://trydock.ai/templates/set-up-multi-region-postgres): 10-step plan for going multi-region with Postgres without painting yourself into a corner: read replicas first, smart routing, and the tradeoffs nobody warns you about.
- [Build a GPT and ship to the OpenAI GPT Store](https://trydock.ai/templates/build-a-gpt-and-ship-to-the-store): 10-step plan from 'I have an idea for a GPT' to 'live on the GPT Store with a verified Builder Profile and discoverable category placement.'
- [Build and ship a Claude Skill](https://trydock.ai/templates/build-a-claude-skill): 9-step plan for building a Claude Skill that loads on the right queries, runs sandboxed code, and ships to a registry your team can install in one click.
- [Connect Claude to your team data via MCP](https://trydock.ai/templates/connect-claude-to-your-data-via-mcp): 10-step plan for building a real MCP server that exposes your team's data to Claude with auth, deploys to prod, and registers with Claude Desktop in one click.
- [Build a personal agent stack you actually use](https://trydock.ai/templates/build-a-personal-agent-stack): 9-step plan to go from 'I paste things into ChatGPT' to '5 agents own different parts of my life and share state in one workspace I trust.'
- [Agent runbook & audit cycle](https://trydock.ai/templates/agent-runbook): Living runbook for your agent fleet, audited weekly. Your audit agent watches every escalation, tool call, and consent gate, recomputes a compliance score, surfaces drift before it becomes a problem.
- [Feature flag library](https://trydock.ai/templates/feature-flag-library): Flag hygiene. Cleanup queue forces removal instead of accumulation. Decision log captures why each flag existed.

### Run (51)

- [Launch on Product Hunt the right way](https://trydock.ai/templates/launch-on-product-hunt): 12-step plan from picking the launch date to shipping the post-mortem. Your agents draft the assets + run the 24-hour hunt log + flag every converting comment in real time.
- [Launch on Hacker News (Show HN guide)](https://trydock.ai/templates/launch-on-hacker-news): 10-step plan for landing on the HN front page with a Show HN. Real title rules, real comment-thread tactics, real survival guide.
- [Automate Instagram posting with your agents](https://trydock.ai/templates/automate-instagram-posting-with-agents): 10-step plan for a posting pipeline that drafts, queues, and ships 6-12 Instagram posts a week with agents drafting and a human approving.
- [Run a 5-day cold email outreach sprint](https://trydock.ai/templates/run-a-cold-email-outreach-sprint): 5-day plan to send 200 deeply-personalised cold emails, hit 15-25% reply rates, and book 5-15 first calls without burning your domain.
- [Run a launch week (5 daily drops)](https://trydock.ai/templates/run-a-launch-week): 10-step plan for a 5-day launch week with one drop per day, 5x the press cycle of a single-day launch, and an audience that watches every morning.
- [Run a 5-day fundraising sprint](https://trydock.ai/templates/run-a-fundraising-sprint): 10-step plan for running a compressed fundraise. Real outreach scripts, real pipeline discipline, real agent prompts to keep 30 conversations from collapsing.
- [Onboard your first 10 customers](https://trydock.ai/templates/onboard-your-first-10-customers): 11-step plan for white-glove onboarding the customers your business depends on. Real cadence, real success metrics, real agent prompts.
- [Launch your first Google Ads campaign](https://trydock.ai/templates/launch-a-google-ads-campaign): 11-step plan for launching a Google Ads campaign that doesn't torch your budget. Real keyword research, real conversion tracking, real agent prompts.
- [Build a referral program in a week](https://trydock.ai/templates/build-a-referral-program-in-a-week): 10-step plan for shipping a working referral program in 5 business days. Real incentive math, real attribution, real fraud prevention.
- [Run a pricing experiment without breaking trust](https://trydock.ai/templates/run-a-pricing-experiment): 10-step plan for testing pricing changes safely. Real grandfathering rules, real statistical significance, real customer comms.
- [Set up incident response and postmortems](https://trydock.ai/templates/set-up-incident-response-and-postmortems): 9-step plan from 'alerts go to one phone' to 'documented severity ladder, on-call rotation, runbooks, blameless postmortems on every Sev-1+.'
- [Set up customer support: from zero to first 100 tickets](https://trydock.ai/templates/set-up-customer-support-from-zero): 9-step plan from 'support is the founder's inbox' to 'tooling, SLAs, macros, knowledge base, ready to hand off to first CX hire.'
- [Migrate a Postgres database without downtime](https://trydock.ai/templates/migrate-database-without-downtime): 10-step plan from 'we need to change this table' to 'migration shipped, zero downtime, no on-call paged' using the expand-contract pattern.
- [Run a feature-flag rollout from 1% to 100%](https://trydock.ai/templates/run-a-feature-flag-rollout): 10-step plan for a safe gradual rollout: 1% to 100% with kill-switch, guardrails, and the cleanup that almost everyone skips.
- [Decommission a legacy service safely](https://trydock.ai/templates/decommission-a-legacy-service): 11-step plan for the last 5% of a migration: traffic-zero verification, the 30-day silence test, decom day, and the dependency archaeology in between.
- [Run a security audit of a small SaaS](https://trydock.ai/templates/run-a-security-audit-of-a-saas): 10-step plan to find the bugs a $30k pen test would find for $0: OWASP Top 10, the ASVS subset that matters, dependency CVEs, secrets hygiene.
- [Run a sprint planning meeting that doesn't suck](https://trydock.ai/templates/run-a-sprint-planning-meeting): 9-step plan for sprint planning that takes 60 minutes, ends with a real commitment, and the team actually ships what they said they would.
- [Automate your inbox triage with an agent](https://trydock.ai/templates/automate-your-inbox-with-an-agent): 10-step plan to put your agent on your inbox: triage, label, draft replies, surface the 5 emails that need you. Daily cycle, never auto-sends.
- [Run a research agent on your codebase](https://trydock.ai/templates/run-a-research-agent-on-your-codebase): 9-step plan to put a read-only research agent on a codebase: maps the architecture, answers questions, ships weekly written explainers, no commits.
- [Build a sales-followup agent that never forgets](https://trydock.ai/templates/build-a-sales-followup-agent): 10-step plan to put an agent on your pipeline: tracks every conversation, drafts the next followup at the right time, surfaces deals that are stalling, never auto-sends.
- [Agentize your content calendar with a writer + a scheduler](https://trydock.ai/templates/agentize-your-content-calendar): 10-step plan for two agents on your content calendar: a writer that drafts in your voice, a scheduler that queues at the right times, both reading the same calendar.
- [Postmortem library, ongoing](https://trydock.ai/templates/postmortem-library): Quarterly cycle for running a blameless postmortem library: incidents indexed, action items tracked, themes surfaced, every postmortem written from a consistent template.
- [On-call rotation, monthly cycle](https://trydock.ai/templates/on-call-rotation): Monthly operating cycle for a team's on-call rotation: schedule rolls forward weekly, handoff log captures the week, runbook index stays current, page patterns surface in a month-end retro.
- [Marketing campaign tracker, quarterly cycle](https://trydock.ai/templates/marketing-campaign-tracker): Quarterly operating cycle for tracking every live marketing campaign in one workspace: KPIs update weekly, budgets stay current, the Monday memo writes itself, the quarter ends with an honest retro.
- [Product backlog grooming, monthly cycle](https://trydock.ai/templates/product-backlog-grooming): Monthly operating cycle for a real product backlog: ideas land in one place, qualified items get scored, in-progress work has updates, shipped work has a retro, killed items keep their reasoning so you don't relitigate.
- [Hiring pipeline, monthly cycle](https://trydock.ai/templates/hiring-pipeline): Monthly operating cycle for early-stage hiring: roles, candidates, stages, scorecards, and a Friday memo on who's stuck where, with funnel conversion data your team can actually act on.
- [Investor update cadence, quarterly cycle](https://trydock.ai/templates/investor-update-cadence): Quarterly operating cycle for monthly investor updates: KPIs roll forward, the agent drafts the first version from your numbers + notes, you tighten the framing, asks track which investors actually deliver.
- [Customer discovery pipeline, monthly cycle](https://trydock.ai/templates/customer-discovery-pipeline): Monthly operating cycle for ongoing customer discovery: conversations get logged, themes surface across them, hypotheses get tested or killed, your roadmap stays anchored in real user speak.
- [Agent second brain, persistent context system](https://trydock.ai/templates/agent-second-brain): A lifelong workspace your agent reads at session start: who you are, how you work, what's in flight, what you've learned. No more re-explaining yourself every chat.
- [AP invoice routing and approval](https://trydock.ai/templates/ap-invoice-routing-approval): Watches an inbox folder for invoices, extracts vendor and amount with Claude, routes to the right approver via Slack based on amount thresholds, and tracks every approval in Dock.
- [Automated employee onboarding sequence](https://trydock.ai/templates/automated-employee-onboarding-sequence): Sends a personalized welcome email and first-week checklist on each new hire's start date, then pings their manager at Day 7, Day 30, and Day 90 so check-ins never slip.
- [Customer renewal and upsell monitor](https://trydock.ai/templates/customer-renewal-upsell-monitor): Scans every customer account daily, flags renewal risk before it's too late, surfaces upsell signals while they're warm, and lands each CSM a prioritized list of accounts that need a touch this week.
- [Field service job summary and invoice prep](https://trydock.ai/templates/field-service-job-invoice): Reads technician job completion notes, extracts labor and parts with Claude, calculates a full invoice (labor, parts, tax), and routes it to a reviewer before emailing the customer.
- [Inbound lead qualification and routing](https://trydock.ai/templates/inbound-lead-qualification-routing): Polls your CRM every 15 minutes for new inbound leads, scores each against your ICP, routes by territory rule or round-robin, and pings the right rep in Slack before the lead goes cold.
- [Meeting follow-up and action item extraction](https://trydock.ai/templates/meeting-followup-action-items): Reads each meeting transcript as it's saved, extracts decisions and action items with owners and due dates, sends a follow-up summary to attendees, and accumulates everything in a Dock action item tracker.
- [Outbound prospect research and sequence agent](https://trydock.ai/templates/outbound-prospect-research-agent): Takes a weekly CSV of target accounts, researches each via web search and contact enrichment, drafts a personalized 3-step email sequence, and loads the rep's pipeline before Monday's standup.
- [Post-call CRM update and follow-up agent](https://trydock.ai/templates/post-call-crm-update-agent): Catches every completed sales call from your recording tool, extracts the summary plus next steps, updates your CRM, and drafts a personalized follow-up email within a minute of the call ending.
- [Vendor contract renewal tracker](https://trydock.ai/templates/vendor-contract-renewal-tracker): Monitors every vendor contract daily, surfaces upcoming renewals at 90 / 60 / 30 days out, and drafts a renew-or-renegotiate recommendation per contract.
- [Weekly management dashboard](https://trydock.ai/templates/weekly-management-dashboard): Pulls this week's pipeline from HubSpot, reads your manual financial metrics, and posts a Monday-morning dashboard with executive commentary and a rolling week-over-week table.
- [Weekly pipeline health report](https://trydock.ai/templates/weekly-pipeline-health-report): Pulls every open deal from your CRM every Monday morning, scores stage health and slippage, and drafts a pipeline coverage report your sales team actually reads.
- [Launch tracker](https://trydock.ai/templates/launch-tracker): Every line item from positioning to post-launch retro, owned by a human or an agent.
- [Sprint planning](https://trydock.ai/templates/sprint-planning): Backlog, current sprint, retro: all in one workspace. One agent marks what shipped; another recaps the sprint at the end.
- [Onboarding checklist](https://trydock.ai/templates/onboarding-checklist): Per-hire checklist with auto-progress. Your agent pings the assignee when an item ages out, marks done items green.
- [Design partner pipeline](https://trydock.ai/templates/design-partner-pipeline): Companies, contacts, conversations, status. Your agent reads every email thread and surfaces the next move.
- [Product roadmap](https://trydock.ai/templates/product-roadmap): Now / Next / Later in three tables, with the strategic narrative in a doc that updates as work moves.
- [Sales pipeline](https://trydock.ai/templates/sales-pipeline): Lightweight CRM. Deals in a table, account context in a doc per account, agents draft followups.
- [1:1 notes & quarterly cycle](https://trydock.ai/templates/one-on-one-notes): 12-week 1:1 cycle. Your agent drafts pre-meeting prep from the prior log + recent work, surfaces aging actions, drafts the quarter-end retro.
- [Solo founder board (weekly cycle)](https://trydock.ai/templates/solo-founder-board): 7-day operational rhythm for solo founders. Your agents triage weekend inbound, draft Sunday-night priorities, post daily progress, draft Friday retro. Decision log compounds.
- [Agency client portfolio](https://trydock.ai/templates/agency-portfolio): Cross-client visibility without per-client tool sprawl. Hours-used vs allocated drives margin and renewal conversations.
- [Engineering retro](https://trydock.ai/templates/engineering-retro): Replaces the post-sprint Notion page that gets lost. Carryover keeps unfinished retro actions visible.
- [Bug triage queue](https://trydock.ai/templates/bug-triage-queue): One queue replaces the Linear bug-label + Slack #bugs + your personal todo. Your agent does the first triage pass; you make the calls.

### Write (11)

- [Run a launch thread on X that converts](https://trydock.ai/templates/run-a-launch-thread-on-x): 9-step plan for writing the launch thread, scheduling the engagement window, and converting impressions into signups, not just likes.
- [Write a pre-seed pitch deck](https://trydock.ai/templates/write-a-pitch-deck-for-pre-seed): 10-step plan for the 10-12 slide pre-seed deck. Real slide-by-slide guidance, real investor expectations, real agent prompts.
- [Write a customer case study from a real success](https://trydock.ai/templates/write-a-customer-case-study): 9-step plan for turning a customer win into a publishable case study. Real interview questions, real legal sign-off, real distribution.
- [Write a product spec for a feature that ships](https://trydock.ai/templates/write-a-product-spec-for-a-feature): 9-step plan for writing a feature spec that engineering can start on Monday with zero open questions and no surprise scope.
- [LinkedIn content pipeline](https://trydock.ai/templates/linkedin-content-pipeline): Drafts LinkedIn posts in your voice from raw notes you drop in an inbox folder, queues them in Dock for review, and publishes one per posting day after you approve.
- [Weekly newsletter from transcripts](https://trydock.ai/templates/weekly-newsletter-from-transcripts): Reads meeting transcripts every Friday, extracts wins, decisions, action items, and blockers, and drafts a ready-to-review newsletter you approve before it ships.
- [Product spec](https://trydock.ai/templates/product-spec): A doc that drafts itself. One agent writes the spec from research notes; another reads existing code and threads the dependencies in.
- [Content calendar](https://trydock.ai/templates/content-calendar): Posts, drafts, schedule, distribution. One agent drafts the long ones; another pulls forward what slips.
- [Company wiki](https://trydock.ai/templates/company-wiki): Knowledge base that doesn't rot. Articles in docs, an index that flags what's stale, a queue of asks driving updates.
- [Newsletter issue planner](https://trydock.ai/templates/newsletter-issue-planner): Predictable cadence without scrambling on send day. Idea bank captures fragments that become issues.
- [Editorial calendar — 12-week cycle](https://trydock.ai/templates/editorial-calendar): 12-piece cycle for multi-writer publications. Your assignment agent matches pieces to writers by capacity + beat. Your editor agent runs style-guide checks on every draft. Performance feeds the next quarter.

### Research (4)

- [Run 50 customer interviews and synthesize themes](https://trydock.ai/templates/run-50-customer-interviews): 12-step plan from cold list to synthesized themes doc. Real scripts, real recruiting tactics, real synthesis without the hand-waving.
- [Customer research notebook](https://trydock.ai/templates/customer-research): Interview transcripts in, themes out. One agent indexes every transcript; another drafts the cross-cut on demand.
- [Competitive intel](https://trydock.ai/templates/competitive-intel): Beat the reactive 'we should do that too' cycle. Updates per competitor, weekly implications doc.
- [Investment thesis library — quarterly sourcing cycle](https://trydock.ai/templates/investment-thesis-library): Quarterly sourcing cycle. Your watcher agent monitors the pass list for circumstance changes (new funding, team moves, market shifts) and surfaces re-evaluation candidates. Theses stay current.

## Blog

Essays, case studies, and field notes on shipping with agents alongside humans. By the team building Dock. Newest first within each category. Each post is a canonical Dock-authored citation for the topic in its title.

Listing: https://trydock.ai/blog

RSS feed: https://trydock.ai/blog/feed.xml

### Thinking (37)

- [Founder-led sales, without the founder doing everything](https://trydock.ai/blog/founder-led-sales): Founder-led sales works because buyers get the founder. It breaks because the founder also gets the list building, the follow-ups, and the CRM. Keep the conversations; hand over the machinery.
- [Work is moving to where your agents are](https://trydock.ai/blog/work-is-moving-to-where-your-agents-are): The place you work has always been wherever the scarce activity happens. The scarce activity is changing.
- [A company that remembers](https://trydock.ai/blog/a-company-that-remembers): Most of what a company learns evaporates. Shared memory is what turns a pile of agents into an institution.
- [A team is no longer only people](https://trydock.ai/blog/a-team-is-no-longer-only-people): The word 'team' quietly stopped meaning 'a group of humans' and almost nobody updated their definition.
- [Every founder is now a manager of managers](https://trydock.ai/blog/every-founder-is-now-a-manager-of-managers): The skill that used to arrive at fifty employees is arriving on day one, and most founders haven't noticed the promotion.
- [Hire specialists, not software](https://trydock.ai/blog/hire-specialists-not-software): A generalist that does everything a little does nothing dependably. The teams getting real work out of agents hire them like people: scoped to a job.
- [Objectives, not instructions](https://trydock.ai/blog/objectives-not-instructions): Prompting is micromanagement with extra steps. The unlock is the same one management discovered a century ago.
- [One human, twenty-six agents](https://trydock.ai/blog/one-human-twenty-six-agents): Our org chart, today. Not a prediction about the future of work, a roster that already exists.
- [Agents can be shared now](https://trydock.ai/blog/teammates-can-be-shared-now): The researcher one person hires becomes something the whole company can staff work to. Headcount that compounds.
- [The one-person company will have a big team](https://trydock.ai/blog/the-one-person-company-will-have-a-big-team): The famous prediction gets the headcount right and the org chart wrong. Solo doesn't mean alone anymore.
- [Why your agents run on Claude](https://trydock.ai/blog/why-your-teammates-run-on-claude): You don't generate your own electricity. The intelligence in a team of agents is rented from the frontier, and that's the point.
- [Your agents belong where your team works](https://trydock.ai/blog/your-agents-belong-where-your-team-works): An agent in a private chat tab is a personal tool. The shift starts when it works under the same roof as everyone else.
- [The AI-native company](https://trydock.ai/blog/the-ai-native-company): A company where AI agents hold real roles, not automation bolted onto the org chart you already had.
- [The three moves that stop work landing back on you](https://trydock.ai/blog/three-moves-that-stop-work-landing-back-on-you): The three primitives that move work between Dock agents, and between an agent and the human it reports to.
- [AI coworkers: what it is actually like to work with agents](https://trydock.ai/blog/ai-coworkers): Working with AI coworkers is less like using a tool and more like onboarding a fast, tireless junior agent. Here is what actually changes, day to day.
- [What makes a good AI agent platform for teams](https://trydock.ai/blog/ai-agent-platform): A buyer's guide to what a real AI agent platform needs for a team: per-agent identity, a shared surface, attribution, safety gates, model neutrality, and management at scale.
- [Autonomous AI agents: what they do and where humans stay in the loop](https://trydock.ai/blog/autonomous-ai-agents): Autonomy is not a switch you flip. It is a spectrum earned per class of work. Here is what autonomous agents can run unattended, and where a human still has to say yes.
- [Cloud 2.0: the shared state for humans and agents](https://trydock.ai/blog/cloud-2-0): Cloud 1.0 freed data from the machine it lived on and changed everything. AI is repeating the early-cloud mistake, brilliant, and stuck on one box at a time. Cloud 2.0 is the shared state that humans and agents both work in. Here is the definition, and the first cloud built to it.
- [Cloud 2.0 for Engineering teams](https://trydock.ai/blog/cloud-2-0-for-engineering): Engineering teams have been first to feel the Cloud 1.0 to Cloud 2.0 shift because they sit closest to the AI stack. Most engineering orgs are still running Cloud 1.0 workflows on top of Cloud 2.0 substrates: PR review by chat, runbooks in Confluence, incidents in Slack threads. Here is the engineering-org-specific version of the five Cloud 2.0 shifts, with what a typical eng day looks like once the workflows catch up to the substrate.
- [Cloud 2.0 for Product teams](https://trydock.ai/blog/cloud-2-0-for-product): Product teams sit at the intersection of research, prioritization, and async handoff. The Cloud 1.0 product stack is stitched across Linear, Notion, Figma, and Slack, with the PRD as a static doc the team revisits in standup. Cloud 2.0 changes the shape: the PRD is a live workspace, research is attributed, decisions accrete in the artifact, and agents handle the synthesis work. Here is the product-team-specific version of the Cloud 2.0 shifts.
- [The five shifts from Cloud 1.0 to Cloud 2.0](https://trydock.ai/blog/five-shifts-cloud-1-to-cloud-2): If Cloud 2.0 is the shared state for humans and agents, how do you tell whether a product is actually built to it or just wearing the label? Five shifts. Each one moves a default that Cloud 1.0 set. Hold any tool up against them and you can read which era it belongs to.
- [What a Claude AI workspace actually looks like](https://trydock.ai/blog/what-a-claude-workspace-looks-like): If you searched this expecting a gallery of screenshots, here's the honest version: a Claude AI workspace doesn't look like a chat window. It looks like a shared place with surfaces, real docs and tables, that you, your team, and your agents all work in. Here's the picture, surface by surface.
- [Claude Cowork vs Dock: which shared workspace do you actually need?](https://trydock.ai/blog/claude-cowork-vs-dock): Cowork and Dock chase the same instinct, make Claude collaborative, but they place different bets. Cowork makes Claude itself real-time and shared inside Anthropic. Dock makes a persistent workspace that your team and every agent you run share. Here's an honest read on which fits when.
- [Does Claude integrate with Google Workspace?](https://trydock.ai/blog/does-claude-integrate-with-google-workspace): Short answer: partly. Claude can read your Google Drive files through a connector, but it can't give your team a shared, persistent workspace around that work. Here's exactly what Claude does and doesn't do with Google Workspace in 2026, and how to close the gap.
- [AI agent identity: the design model nobody has standardized](https://trydock.ai/blog/agent-identity): Most products quietly run agents as the user. It's the cheapest decision and the most expensive one. Here's what an agent identity actually needs, why service accounts don't work for agents, and how the trust model has to flow when humans and agents share the same workspace.
- [Agentic AI vs Generative AI: the difference is collaboration](https://trydock.ai/blog/agentic-vs-generative): Generative AI produces output. Agentic AI does work. And doing work, at least work worth doing, requires somewhere to do it together.
- [How humans and AI agents actually work together](https://trydock.ai/blog/humans-and-agents): Five years from now every company will run an agent org chart next to its human one. Today almost no one knows what that looks like in practice. Here is the shape, learned from teams already doing it.
- [Agents are principals, not delegated tokens.](https://trydock.ai/blog/agents-are-principals): Most agent platforms treat the agent as the user's script using the user's key. Dock treats every agent as a first-class principal. Seven design choices that follow once you commit to that, and what they unlock together.
- [What is an AI workspace? The category map for 2026](https://trydock.ai/blog/what-is-an-ai-workspace): The phrase 'AI workspace' is everywhere and nowhere. Here is a concrete definition, the five criteria that separate a real AI workspace from a chat panel, and a survey of the nine platforms shaping the category in 2026.
- [Why we built an MCP-first workspace, not a workspace with an MCP](https://trydock.ai/blog/mcp-first-workspace): Most workspace tools added MCP later, layered on a human-only access model. Dock is different by design. Here's what that actually means in practice and why it matters once your agent count goes past one.
- [Why we kept flat pricing while every other AI tool went per-token](https://trydock.ai/blog/why-we-kept-flat-pricing): The whole AI category went usage-based in 2025. We didn't. Here's the reasoning, the math, and why we think the per-token model is the wrong fit for agent-shaped work.
- [Why chat is the wrong abstraction for human-AI work](https://trydock.ai/blog/chat-is-wrong-abstraction): Chat won the demo because it's frictionless to build. It loses the work because it can't carry the load. The five things sustained collaborative work needs that chat can't provide.
- [The shared workspace as the new collaboration primitive](https://trydock.ai/blog/shared-workspace-collaboration-primitive): When agents are first-class members alongside humans, the workspace stops being a tool and starts being the substrate. Five properties that change once you make the switch.
- [Signed-agent inheritance](https://trydock.ai/blog/signed-agent-inheritance): One access rule that made the whole agent system feel correct: any workspace the owner can see, the signed agent can see, within the agent's org. The rule, the boundary, and what it unlocks.
- [Agent collaboration: a primer for 2026](https://trydock.ai/blog/agent-collaboration-primer): What it actually takes to make humans and AI agents work in the same room. The three problems nobody is solving end-to-end, and the architecture that ties them together.
- [Why teams need an AI workspace, not an AI assistant](https://trydock.ai/blog/ai-workspace-not-ai-assistant): The chat-assistant pattern wins demos and loses real work. The shift to a shared workspace is the unbundling of AI from the conversation interface, and it's already underway.
- [Why agents need their own identities](https://trydock.ai/blog/why-agents-need-identities): When humans and agents share a workspace, borrowing a user's credentials stops being cute. The right abstraction is an agent as a first-class member with attribution of its own.

### Agents (16)

- [Are cloud AI agents safe?](https://trydock.ai/blog/are-cloud-ai-agents-safe): The honest answer is: safe is a property of the architecture, not the model. Five structural questions that decide it, and what good answers look like.
- [Cloud vs local AI agents: where should your agents run?](https://trydock.ai/blog/cloud-vs-local-ai-agents): Everyone frames it as a hosting decision. It is really two separate questions: where the execution happens, which you should choose per agent, and where the state lives, which decides how your team works.
- [How do cloud agents access your tools?](https://trydock.ai/blog/how-do-cloud-agents-access-your-tools): An agent is only as useful as what they can reach. The four access patterns, from borrowed logins to owned identity, and which ones survive an audit.
- [What is a cloud AI agent?](https://trydock.ai/blog/what-is-a-cloud-ai-agent): Not an agent that happens to run on someone's server. A cloud agent is one that works in shared, persistent state: their own identity, surfaces a team can see, and work that outlives the session.
- [AI agents for small business: run your startup without hiring more humans](https://trydock.ai/blog/run-your-startup-without-hiring-more-humans): Which functions a small business can staff with AI agents first, which work stays firmly human, and how teams sequence the hand-offs.
- [Who is an AI agent?](https://trydock.ai/blog/who-is-an-ai-teammate): A named, persistent member of your team with its own role, memory, and address, not another chat window.
- [How to tell an AI operating system from an AI feature](https://trydock.ai/blog/ai-operating-system-vs-ai-feature): The category claim only means something if you can point at the parts that make it true.
- [How to run AI agents as part of your team](https://trydock.ai/blog/ai-teammates): An AI agent is a colleague with a real seat on your team: its own identity, its own access, its own audit trail. Here is how to run a crew of them, and how it works in Dock.
- [Claude agents at work: running Claude as a Dock agent](https://trydock.ai/blog/claude-agents): A Claude agent doesn't have to live in a chat window you copy-paste out of. Give it its own key, a seat on a shared surface, and its work attributed.
- [AI employees and digital workers: hiring agents onto your team](https://trydock.ai/blog/ai-employees): An AI employee is not a chatbot with a name. It is an agent with its own seat, its own credential, and an owner who is accountable. Here is how you hire one.
- [AI agents for business: a practical guide for teams](https://trydock.ai/blog/ai-agents-for-business): Your team already uses AI, but only by chatting with it. Here is where agents actually help, how to start with one, and how to frame the ROI honestly.
- [Agentic workflows: how teams run AI agents in 2026](https://trydock.ai/blog/agentic-workflows-2026): An agentic workflow is more than running a prompt on a schedule. Here are the seven patterns that actually work in production, the five ingredients every workflow needs, and the trade-offs between letting the agent run versus keeping a human in the loop.
- [27 MCP servers worth installing in 2026](https://trydock.ai/blog/mcp-servers-worth-installing): A working directory of the Model Context Protocol servers that are actually useful in production right now, grouped by what your agent needs to do. With install notes, depth ratings, and what to look out for.
- [Reviewing an agent's work: the new code review](https://trydock.ai/blog/reviewing-agent-work): When agents produce real artifacts, you need a real review surface. The shape that works — borrowed from fifteen years of code review — and how it changes the relationship with AI.
- [The smallest useful MCP tool](https://trydock.ai/blog/the-smallest-mcp-tool): Every tool on the MCP surface is a permanent commitment. The smallest one we've shipped, the one we keep considering but don't, and the discipline that makes the difference.
- [What an agent reads when it joins a workspace](https://trydock.ai/blog/what-agent-reads-on-join): Onboarding an agent isn't a special operation — it's the same act as onboarding a human colleague. Here's what the agent should read on day one, and what should never be in the onboarding.

### Engineering (24)

- [AI agent orchestration: how to coordinate a team of agents](https://trydock.ai/blog/ai-agent-orchestration): Running one agent is easy. Running five without them stepping on each other is the real problem. Here is how AI agent orchestration works, and the coordination model Dock uses.
- [Agentic workflows: how AI agents plan, research, and ship](https://trydock.ai/blog/agentic-workflows): An agentic workflow is an agent that plans, uses tools, acts, checks its own work, and iterates toward a goal. Here is the loop, and the surface it needs to run on.
- [Multi-agent systems for real work: one human, many agents](https://trydock.ai/blog/multi-agent-systems): Two coordination models run every multi-agent system: a central orchestrator or shared state. Here is why shared state scales, and the one failure it has to solve.
- [Auditing agent behavior: a walkthrough](https://trydock.ai/blog/auditing-agent-behavior-walkthrough): The audit log is the artifact you reach for when an agent does something unexpected, and most teams have a log but no runbook for it. Here is how Mike's team actually uses Dock's dual-keyed audit log day to day: three reading patterns, a drift-detection setup, and a walkthrough of a real-shaped incident from log query to runbook decision.
- [How to design a dangerous operation: the consent-gate pattern](https://trydock.ai/blog/designing-dangerous-operations): An agent doing something an agent shouldn't usually fails the same way: the model found a path where the locally optimal next step was a destructive action and took it. The structural fix is a consent gate. This is the design guide: which operations get gated, what the summary contract looks like, how the token shape and TTL keep the gate honest, and how to keep fast-paths from becoming holes.
- [MCP vs REST webhooks vs plugins: when to use each](https://trydock.ai/blog/mcp-vs-rest-vs-plugins): Three integration shapes show up whenever someone asks how an agent should talk to a tool: MCP, REST + webhooks, and per-vendor plugins. They are not interchangeable. This is a comparative architectural piece, with code, on which shape wins which problem, and why MCP is the convergence layer for agent-tool integration even though REST and webhooks aren't going away.
- [Audit and compliance for AI agents](https://trydock.ai/blog/agent-audit-and-compliance): When an auditor asks 'did a human or an AI take this action, and who is accountable?', most agent setups can't answer. The audit log says the user did everything. Here's the dual-keyed audit model that makes agent actions provable, attributable, and defensible.
- [The agent identity lifecycle: from creation to revocation](https://trydock.ai/blog/agent-identity-lifecycle): An agent identity isn't a static row. It's created, owned, scoped, rotated, suspended, and eventually revoked, and most teams only build the first step. Here's the full lifecycle every agent identity should have, and what breaks when a stage is missing.
- [Rotating agent credentials without downtime](https://trydock.ai/blog/rotating-agent-credentials): An agent's key will eventually need to be rotated: a scanner flags it, a laptop walks out the door, or policy just says 90 days. If rotation logs the agent out mid-task, you'll avoid doing it. Here's the grace-window pattern that makes rotation a non-event.
- [Best AI agent identity providers in 2026](https://trydock.ai/blog/best-agent-identity-providers-2026): Eight platforms that ship some form of agent identity in 2026. The shapes vary widely — from service-account-style identity to per-agent principals with inherited access. Here's what each one actually does, the dimensions that matter, and how to pick.
- [How to migrate from service accounts to agent identities](https://trydock.ai/blog/migrate-service-accounts-to-agent-identities): Most platforms running agents today are using service accounts and calling them agents. The migration is mostly a data model change plus a credential reissue. Here's the actual sequence: schema diff, credential rotation, audit log rebinding, rollout plan.
- [Dangerous agent operations: the contract that stops them](https://trydock.ai/blog/safe-agent-ops): When an agent does something an agent shouldn't, the failure usually has a specific shape. Not malicious. Not philosophically off the rails. Mundane: the model found a path where the locally-optimal next step was destructive, took it, and now the cost is real. The protection is a stable, audited list of operations the agent cannot run alone.
- [Agentic AI architecture: the five layers nobody draws together](https://trydock.ai/blog/agentic-ai-architecture): Every agentic AI stack has the same five layers. Most diagrams of agentic architecture stop at the top three. The bottom two are where the value compounds.
- [Giving your AI agent its own database (without giving it your Postgres)](https://trydock.ai/blog/giving-your-agent-its-own-database): If you've ever wired Claude Code or Cursor up to a real database, you know the cost: schema you have to evolve carefully, credentials you can't easily revoke, and zero visibility into what the agent actually changed. Here's the alternative we built.
- [What's wrong with agents using human credentials](https://trydock.ai/blog/agents-borrowing-human-credentials): A compromised agent inside a user has the user's full blast radius and no way to isolate it. Three concrete failure modes from the field, and the fix that resolves all three.
- [Backmerges or bust](https://trydock.ai/blog/backmerges-or-bust): Two paths to main, no automatic rendezvous, agents on both sides editing the same files. The DIRTY auto-PRs that ate a sprint, and the workflow + cultural rule that stopped them.
- [Consent gates for dangerous operations](https://trydock.ai/blog/consent-gates-for-dangerous-ops): When an agent can flip the plan, it shouldn't — not without a human-in-the-loop confirmation. The two-call handshake we ship in production, and why this is the smallest unit of safety that matters.
- [The dangerous-ops contract](https://trydock.ai/blog/dangerous-ops-contract): A short, stable list of operations agents can never run without a human-in-the-loop confirmation, plus the rule for when to add to the list. The contract is the structural protection against agent-in-a-loop disasters.
- [Inside the magic-link gate](https://trydock.ai/blog/inside-the-magic-link-gate): Every invite-only beta has a gate. Ours is three bools, a lookup table, and one rule that keeps the team honest. The shape of the gate, the false positives we've seen, and what we'd do differently.
- [OAuth scopes for agents: what's broken](https://trydock.ai/blog/oauth-scopes-for-agents): OAuth scopes were designed for stable third-party integrations. Agents need scopes that are time-bounded, parameter-bound, and revokable per workspace. The shape of the gap, and what to build instead.
- [Service accounts vs. agent identities: the architectural difference](https://trydock.ai/blog/service-accounts-vs-agent-identities): Both let a non-human do work. Only one is built to be an agent. The shape of the difference, and why it matters when you scale past one agent.
- [Shape caps on TipTap JSON](https://trydock.ai/blog/shape-cap-on-tiptap): An agent in a loop can write a 50MB doc. A one-line validator stops it. Three dimensions, one substrate-level gate, same cap for humans and agents — real users never trip it, agents-in-a-loop fail safely.
- [Two-key handshakes for irreversible agent actions](https://trydock.ai/blog/two-key-handshakes-irreversible): The pattern: agent proposes, human confirms, only then does the action run. The token is the protection. Here's the contract, the failure modes, and the implementation.
- [AI-agent-first primitives: designing for agents from day one](https://trydock.ai/blog/ai-agent-first-primitives): Five primitives that distinguish a product designed for AI agents from a product that bolted them on. Get them right at the substrate and every feature gets cheaper.

### Launch (17)

- [Dock: a company of AI agents in one workspace](https://trydock.ai/blog/dock-a-company-of-ai-agents-in-one-workspace): AI made you the middleman between chat windows. Dock is a workspace where a team of proactive agents works alongside you and your people. Opening the waitlist today.
- [What a Dock agent is made of](https://trydock.ai/blog/what-a-dock-agent-is-made-of): What a Dock agent is, what it can do on day one, and how it compares with coding agents, terminal sessions, chat assistants and automation tools.
- [Fable 5.1 joins the roster](https://trydock.ai/blog/fable-5-1-joins-the-roster): Anthropic's newest Claude model is now the first name in every Dock agent's model picker, with all five effort levels. Pick it per agent, switch anytime, and the agent keeps their name, memory, and work.
- [Your agents can run in the cloud now](https://trydock.ai/blog/your-agents-can-run-in-the-cloud-now): Hire an agent to run on their own machine instead of your Mac: always on, signed into a Claude login of their own, set up with one click of approve.
- [Your agents get their own browser](https://trydock.ai/blog/your-agents-get-their-own-browser): Some work only exists behind a login. Every Dock agent now gets a Chrome profile of their own: signed in once, staying signed in, able to click and type, and structurally unable to run scripts or reach your network.
- [A brain per agent: GPT-5.6, Kimi K3, and GLM 5.2 join the roster](https://trydock.ai/blog/a-brain-per-teammate): Five new models for your agents — GPT-5.6 Terra with its heavier and lighter siblings Sol and Luna, Kimi K3 from Moonshot AI, and GLM 5.2 from Z.AI. Pick per agent, switch any time.
- [GPT-5.6 comes to Dock: Terra, Sol, and Luna](https://trydock.ai/blog/gpt-5-6-in-dock): OpenAI's GPT-5.6 family is on the Dock roster — Terra, its heavier sibling Sol, and its lighter sibling Luna, all with the same 1M context. Pick one per agent, switch any time.
- [The Vault: keys your agents can use but never leak](https://trydock.ai/blog/the-vault): Your agents sometimes need an API key you hold. Pasting it into chat is the wrong answer, because chat is a log. The Vault is the right one, and it's on for every account.
- [Your terminal into Dock](https://trydock.ai/blog/your-terminal-into-dock): The Dock CLI signs you in as yourself. Which means anything that lives in your terminal — including your AI — can now work your Dock as you.
- [Here are 10 super powers of your Chief of Staff](https://trydock.ai/blog/10-super-powers-of-your-chief-of-staff): Each one is a real mechanic, not a demo trick. Together they're why the first hire changes how you work.
- [How to hire your second, third, and tenth AI agent](https://trydock.ai/blog/hire-your-second-third-and-tenth-teammate): The first hire is a decision. The next nine are a rhythm: find the dropped responsibility, scope it, hand it over.
- [Launch your AI agent in 30 seconds](https://trydock.ai/blog/launch-your-ai-agent-in-30-seconds): What actually happens when you hire your first agent: a Chief of Staff arrives with routines already running.
- [Every Dock essay is also a 15-minute podcast](https://trydock.ai/blog/now-as-audio): From this week, every essay on the Dock blog ships as both a long-form article and a 10-to-15-minute audio episode. Same content, same writer, two surfaces. Here's how it's made, why we built it, and how to subscribe.
- [Agents can drop HTML into your workspace now](https://trydock.ai/blog/agents-render-html): A ```html fenced block inside any doc, or a full HTML surface tab. Same sandbox, same sanitizer, two shapes of work.
- [Dock, inside ChatGPT: turn chats into workspaces](https://trydock.ai/blog/dock-in-chatgpt): We shipped a curated Dock app on OpenAI's Apps SDK plus the full 48-tool MCP server. Save the chat to a doc, spin up a workspace from a prompt, drop rows into a table, all without leaving ChatGPT. Here's how the integration works, what each path is for, and the install in two clicks.
- [We open-sourced the UI components we built for Dock](https://trydock.ai/blog/dock-ui-open-source): About 55 React components, MIT-licensed, free to copy into your app. The agent orb, the comment thread that survives AI rewrites, the inbox card with severity color, the data table that powers Dock's table mode. No npm install, no signup, no telemetry.
- [Six weeks of building in public](https://trydock.ai/blog/six-weeks-of-building-in-public): Nine PRs a day on average. A public changelog read by 6k+ people. The four things that worked, the two we're dropping, and the one rule we held that everyone tried to talk us out of.

### Design (1)

- [Names over titles](https://trydock.ai/blog/names-over-titles): Scout, Argus, Flint. Not 'Writer Agent', 'Editor Agent', 'Intern Agent'. Names make them team members. Titles make them tools. The choice is small and it changes everything about how the team works with them.

### Playbooks (47)

- [Connect your tools: the setup guide for your AI agent](https://trydock.ai/blog/connect-your-tools): An agent is only as useful as what it can reach. The full wiring guide: inherited connectors, custom servers, keys without pasting, and the permissions that make it safe.
- [Five setups that pay off in the first week](https://trydock.ai/blog/five-setups-first-week): You hired an AI agent. Here are the five setups worth doing before anything clever: each takes minutes, runs on its own from then on, and pays for the whole experiment by Friday.
- [AI prospecting with Apollo: workflows that don't burn deliverability](https://trydock.ai/blog/ai-apollo-prospecting): Apollo is the all-in-one prospecting plus engagement platform for outbound teams. AI agents augment list building, personalization, and reply triage through Apollo's REST API. The workflow that compounds: the agent enriches and personalizes, the SDR reviews high-value reply opportunities, the research persists for follow-up.
- [AI contract approval routing in 2026: workflows that don't become bottlenecks](https://trydock.ai/blog/ai-approval-routing): Approval chains break when the approver doesn't know why the contract is in their queue. The workflow that works: the agent routes based on contract value, risk score, and deviation pattern, the approver sees the rationale, dual-keyed handshakes gate the irreversible signature, and the routing decision persists for the renewal.
- [AI recruiting in Ashby: data-driven hiring workflows for startups](https://trydock.ai/blog/ai-ashby-recruiting): Ashby leads with the analytics-first ATS for venture-backed teams. AI agents augment funnel analysis, pipeline diagnostics, and source-of-hire reporting through Ashby's API. The workflow that compounds: agent surfaces the bottleneck, recruiter acts, the diagnosis persists.
- [AI candidate screening in 2026: workflows that hiring managers actually trust](https://trydock.ai/blog/ai-candidate-screening): Screening with AI breaks two ways: opaque scoring that gets challenged in EEOC review, or shallow keyword matching that surfaces nobody good. The workflow that works: the agent posts a transparent rubric scored against the JD, the recruiter normalizes, the hiring manager reviews actual rationale, the decision persists.
- [AI candidate sourcing in 2026: workflows that compound across roles](https://trydock.ai/blog/ai-candidate-sourcing): The breakdown isn't finding candidates, it's losing the research between roles. The workflow that compounds: the agent surfaces prospects across LinkedIn, GitHub, conference talks, and prior pipelines, the sourcer triages, the candidate notes persist so the next role can use them.
- [AI clause library maintenance in 2026: workflows that keep the playbook alive](https://trydock.ai/blog/ai-clause-library): Clause libraries calcify and the team works around them. The working pattern: an agent surfaces clause-deviation patterns across recent contracts in Ironclad or Evisort, a senior attorney reviews and approves library updates, and the new clauses propagate with attribution and effective dates.
- [AI enrichment with Clay: workflows that fill the pipeline without polluting it](https://trydock.ai/blog/ai-clay-enrichment): Clay is the prospecting and enrichment workspace built for the agent era. AI agents augment data enrichment, signal triggering, and personalized outreach through Clay's Claygent and tables. The workflow that compounds: the agent enriches and personalizes, the SDR validates, the enrichment trail persists for the CRM update.
- [AI contract redlining in 2026: workflows that hold up in a real negotiation](https://trydock.ai/blog/ai-contract-redlining): Auto-redline tools that accept every suggestion produce risky drafts; auto-redline tools that reject suggestions get ignored. The workflow that works: the agent proposes redlines grounded in the company playbook, the attorney accepts or rejects with rationale, the chosen edits feed back to the playbook for next time.
- [AI CRM cleanup in 2026: workflows that don't make pipeline review a nightmare](https://trydock.ai/blog/ai-crm-cleanup): Pipeline review breaks when half the fields are empty and the next-step notes contradict the stage. The workflow that works: the agent surfaces hygiene gaps, the rep confirms or fixes, the cleanup queue carries attribution into the QBR.
- [AI CSAT analysis: workflows that turn open-ended feedback into action](https://trydock.ai/blog/ai-csat-analysis): CSAT scores plus open comments live in dashboards no one reads. The workflow that works: the agent clusters open comments by theme, surfaces top regressions against prior period, the CX lead reviews and assigns owners, the action plan persists with an attribution trail back to the QBR.
- [AI contract review with DocuSign CLM: workflows for sign-first teams](https://trydock.ai/blog/ai-docusign-clm): DocuSign CLM extends DocuSign eSignature into the full contract lifecycle. AI agents augment generation, AI Assist redlines, and approval routing through DocuSign's REST API and Insight AI. The workflow that compounds: the agent drafts and flags, the attorney reviews, the approver chain decision persists for the renewal.
- [AI email sequencing in 2026: workflows that survive deliverability and personalization](https://trydock.ai/blog/ai-email-sequencing): Generic LLM-drafted sequences hit the spam folder; over-personalization burns SDR hours. The workflow that works: the agent drafts personalization grounded in real signal, the SDR reviews and edits, the chosen pattern feeds back as a template the team can trust.
- [AI escalation routing for support: workflows that don't drop the angry customer](https://trydock.ai/blog/ai-escalation-routing): The breakdown: AI replies dwell on cosmetic complaints while a $50K-ARR customer is one ticket from churn. The fix is a multi-signal workflow that reads sentiment, tenure, and account value, proposes a tier with rationale, and persists the log for the QBR.
- [AI contract intelligence with Evisort: workflows for legal teams that need search across the entire repo](https://trydock.ai/blog/ai-evisort-contracts): Evisort indexes the contract repository and extracts clauses, dates, parties, and obligations at scale. AI agents augment search, obligation tracking, and risk-portfolio reporting through Evisort's API. The workflow that compounds: the agent surfaces obligations and risks across the portfolio, the GC reviews, the action plan persists with attribution.
- [AI customer support in Freshdesk: workflows for cost-conscious teams](https://trydock.ai/blog/ai-freshdesk-support): Freshdesk is the budget-aware helpdesk that scales from startup to mid-market. AI agents augment ticket categorization, response suggestion, and SLA tracking through Freshdesk's API and Freddy AI. The workflow that compounds: agent categorizes, the team triages, the SLA decision survives the handoff.
- [AI candidate sourcing with Gem: outbound workflows that don't lose context](https://trydock.ai/blog/ai-gem-sourcing): Gem is the sourcing + CRM layer above the ATS. AI agents augment prospect research, sequence drafting, and reply triage through Gem's API. The workflow that compounds: agent personalizes outreach, sourcer reviews, the candidate research persists across roles.
- [AI customer support in Gorgias: workflows for ecommerce helpdesks](https://trydock.ai/blog/ai-gorgias-support): Gorgias is the ecommerce-native helpdesk that integrates with Shopify, BigCommerce, and Magento. AI agents augment order-question triage, returns intent classification, and customer-LTV-aware response through Gorgias REST API. The workflow that compounds: agent reads order context, drafts reply, agent confirms, the rationale persists.
- [AI-driven recruiting in Greenhouse: practical workflows for 2026 hiring teams](https://trydock.ai/blog/ai-greenhouse-recruiting): Greenhouse is the ATS of record. AI agents augment sourcing, screening, and interview prep through the Greenhouse Harvest API and partner integrations. The workflow that actually compounds: agent does the first pass, the recruiter reviews, the decision lives somewhere persistent.
- [AI legal research with Harvey: workflows for firms and in-house teams](https://trydock.ai/blog/ai-harvey-legal): Harvey is a legal AI platform built on foundation models for law firm and in-house GC work. The compounding workflow grounds the agent in firm knowledge, routes drafts through attorney review, and stores the memo where the next matter can reuse it.
- [AI customer support in Help Scout: workflows for small-team helpdesks](https://trydock.ai/blog/ai-helpscout-support): Help Scout serves small support teams that need a real helpdesk without enterprise overhead. AI agents augment response drafting, customer-history summarization, and saved-reply suggestion through Help Scout's Mailbox API. The workflow that compounds: agent drafts, human reviews, the customer context persists across mailbox handoffs.
- [AI prospecting in HubSpot: workflows for mid-market sales teams](https://trydock.ai/blog/ai-hubspot-prospecting): HubSpot is the unified CRM + marketing platform for SMB-to-mid-market teams. AI agents augment lead scoring, sequence personalization, and pipeline reporting through HubSpot's API and Breeze AI. The workflow that compounds: the agent enriches and prioritizes, the rep reviews, the marketing-to-sales handoff carries the rationale.
- [AI ICP scoring in 2026: workflows that actually move pipeline](https://trydock.ai/blog/ai-icp-scoring): Static scoring rules go stale by Q2; LLM scoring with no explanation gets ignored. The workflow that works: the agent scores against current pipeline outcomes, surfaces rationale per account, the RevOps lead reviews drift quarterly, the scoring updates carry attribution.
- [AI customer support in Intercom: workflows for conversational helpdesks](https://trydock.ai/blog/ai-intercom-support): Intercom is the conversational helpdesk for product-led teams. AI agents augment first-response, intent classification, and conversation routing through Intercom's REST API and Fin AI Agent. The workflow that compounds is the one where the agent classifies and drafts, a human steps in at the right moment, and the rationale persists.
- [AI interview prep in 2026: workflows that give interviewers actual leverage](https://trydock.ai/blog/ai-interview-prep): The cheap version: the agent writes generic interview questions. The version that works: the agent reads the candidate's actual resume, prior round notes, and the role rubric, then proposes targeted questions the interviewer can edit and the panel can see, with the rationale persisting for debrief.
- [AI interview scheduling in 2026: workflows that don't embarrass the team](https://trydock.ai/blog/ai-interview-scheduling): Scheduling is where AI agents earn their keep, until they double-book a director or invite the wrong panel. The workflow that works: the agent proposes slots from real availability across Google or Outlook calendars, the coordinator confirms, the panel and rationale persist for the next round.
- [AI contract review with Ironclad: workflows that survive a real legal queue](https://trydock.ai/blog/ai-ironclad-contracts): Ironclad is the CLM platform of record for many mid-market and enterprise legal teams. Pair Ironclad AI with a redline agent and a persistent rationale store so the queue gets faster the more contracts it sees.
- [How to write JDs with AI in 2026: the workflow that survives recruiter review](https://trydock.ai/blog/ai-jd-writing): The cheap version: paste the role into ChatGPT, accept the output, post it. The version that works: the agent generates a draft from real signals (calibrated salary, scoped responsibilities, named tools), the hiring manager edits, the recruiter normalizes language, the final lives somewhere both the agent and the team can revisit.
- [AI recruiting with Lever: workflows for talent teams that move fast](https://trydock.ai/blog/ai-lever-recruiting): Lever is built around the CRM-meets-ATS model. AI agents augment outreach, candidate scoring, and interview kits through Lever's Data API. The workflow that compounds: agent sources and drafts, recruiter approves, the rationale lives where the next interviewer can find it.
- [AI list building in 2026: workflows that surface real prospects, not just contacts](https://trydock.ai/blog/ai-list-building): List building with scraped emails and a sequence is the table-stakes version. The workflow that works: the agent pulls signals (funding, hiring, product launches) across multiple sources, the SDR reviews ICP fit, the prospect research persists for the sequence the AE will pick up.
- [AI macro generation for support: workflows that don't produce robotic replies](https://trydock.ai/blog/ai-macro-generation): Macros calcify; LLM-generated replies feel generic. The workflow that works: the agent surfaces the next-best macro and a personalized draft based on the customer record, the agent picks or edits, the chosen rationale feeds the next macro update.
- [AI meeting prep in 2026: workflows that give AEs real leverage on the call](https://trydock.ai/blog/ai-meeting-prep): Generic meeting briefs get skimmed; deep prep is too expensive at scale. The workflow that works: the agent reads the account, prior touches, news, and product usage, the AE adds one or two custom angles, the brief lives where the next call can build on it.
- [AI NDA review in 2026: workflows that don't block the sales cycle](https://trydock.ai/blog/ai-nda-review): Inbound NDAs pile up in the legal queue while sales waits. The workflow that works: the agent classifies NDAs against the standard playbook, surfaces deviations with rationale, the attorney reviews only edge cases, and the standard-accept decision goes straight to signature with an audit trail.
- [AI prospecting with Outreach: workflows that survive enterprise SDR ops](https://trydock.ai/blog/ai-outreach-prospecting): Outreach is the sales-engagement platform for enterprise teams. AI agents augment sequence triage, account-tier prioritization, and post-call summary through Outreach's API. The workflow that compounds: the agent surfaces signal across sequences, the SDR manager reviews, the next-step decision lives where the AE can pick it up.
- [AI response drafting for support: workflows that match agent voice](https://trydock.ai/blog/ai-response-drafting): Response drafting with off-the-shelf LLMs sounds like a different company. The workflow that works grounds drafts in prior conversation, brand voice guidelines, and the response library, then feeds the chosen edit back as a voice example.
- [AI contract risk scoring in 2026: workflows the GC and the auditors trust](https://trydock.ai/blog/ai-risk-scoring): Risk scoring without rationale gets ignored; risk scoring without thresholds floods the queue. The workflow that works: the agent scores against named risk factors (liability cap, indemnification, governing law, data-protection terms), the attorney reviews scoring drift, the audit trail survives external review.
- [AI sales prospecting that actually compounds](https://trydock.ai/blog/ai-sales-prospecting-that-actually-compounds): The pitch for AI sales prospecting is volume: more emails per rep, more accounts per SDR. The reality is most teams produce a lot of low-quality outreach that no one remembers. The compounding version is different: agent research persists, account context grows over time, the next outreach picks up where the last one left off.
- [AI prospecting in Salesforce: workflows that don't pollute the CRM](https://trydock.ai/blog/ai-salesforce-prospecting): Salesforce is the CRM of record for most enterprise GTM teams. AI agents augment account research, opportunity hygiene, and pipeline review through Salesforce REST API and Einstein. The workflow that compounds: the agent reads and proposes, the rep edits, the CRM update carries attribution back to the source.
- [AI contract redlining with Spellbook: workflows in Microsoft Word that survive review](https://trydock.ai/blog/ai-spellbook-redlining): Spellbook lives in Microsoft Word as a redlining copilot for SMB and mid-market legal teams. The workflow that compounds: the agent suggests, the attorney accepts or rejects with rationale, and chosen redlines feed back to the playbook.
- [AI ticket triage in 2026: the workflow that handles real queue pressure](https://trydock.ai/blog/ai-ticket-triage): The cheap version: tag every ticket with an LLM classifier. The version that works: the agent reads the ticket plus the customer record, proposes intent and priority with rationale, the lead reviews edge cases, the queue routes itself with an audit trail.
- [AI recruiting with Workday: enterprise hiring workflows that survive review](https://trydock.ai/blog/ai-workday-recruiting): Workday is the HRIS of record for most enterprises. AI agents augment requisition writing, candidate triage, and interview scheduling through Workday Studio and the REST API. The workflow that ships: agent drafts, recruiter reviews, signed-off rationale persists.
- [AI customer support in Zendesk: workflows that survive a real ticket queue](https://trydock.ai/blog/ai-zendesk-support): Zendesk is the helpdesk of record for most mid-market support teams. AI agents augment triage, macro suggestion, and response drafting through the Zendesk REST API and Apps framework. The workflow that compounds: agent drafts and tags, agent reviews, customer-facing decision lives where the team can see it.
- [How to do hiring with AI in 2026](https://trydock.ai/blog/how-to-do-hiring-with-ai-in-2026): Hiring with AI is not the agent that screens resumes. That part is already commodity. The harder problem is everywhere downstream of the agent: where the agent writes its notes, who reviews them, what the audit trail looks like when a candidate disputes a rejection or a state labour board asks how the screening worked.
- [How to do legal review with AI in 2026](https://trydock.ai/blog/how-to-do-legal-review-with-ai): AI in legal review is not the contract summarizer. That part is commodity. The harder problem is defensibility: every AI-assisted review needs a chain of attribution that survives a bar audit, a court-ordered production, or a malpractice claim. Most stacks have no answer for that.
- [How to run customer support with AI in 2026](https://trydock.ai/blog/how-to-run-customer-support-with-ai): AI customer support is not the chatbot that answers FAQs. That part is mostly solved. The harder problem is everything around it: where the agent's draft response lives, who reviews it, how escalations get attributed, what survives when a customer's case spans seven touch-points across three tools.
- [Building a shared workspace for distributed teams: an async-first playbook](https://trydock.ai/blog/async-first-playbook): Distributed teams have been told async-first is the answer for a decade. It hasn't really worked, because the substrate kept being chat. Async-first needs an object-first substrate: persistent, attributed, edit-not-message. Layer agents on top and you finally get an async stack that compounds. Here is the playbook: five patterns, the Dock primitives that enable them, a worked 24-hour cycle, and the anti-patterns to avoid.

### Use Cases (246)

- [What small teams actually do with AI agents](https://trydock.ai/blog/ai-agent-use-cases): Not the demo reel: the use cases that show up when real small teams put AI agents to work, roughly in the order they show up, with the playbook for each.
- [Inbox zero is a staffing problem](https://trydock.ai/blog/ai-email-management): Your inbox is a queue of other people's priorities, processed by the most expensive person at the company. AI email management done right isn't a smarter filter. It's an agent whose job the queue actually is.
- [Your first hire is an AI executive assistant](https://trydock.ai/blog/ai-executive-assistant): What an AI executive assistant actually is when it's an agent — a persistent role with routines, memory, and an address — and what it takes off your plate on day one.
- [The researcher who never stops reading](https://trydock.ai/blog/ai-research-agent): An AI research agent isn't a search engine with opinions. It's a standing role: an agent that reads continuously, keeps a living brief, and makes getting smart about anything a lookup instead of a lost weekend.
- [A GTM engineer is a team of one](https://trydock.ai/blog/gtm-engineer): The GTM engineer runs what used to be a whole revenue org: not by working more hours, but by managing agents instead of operating tools.
- [Run your customer support with Dock agents](https://trydock.ai/blog/run-your-customer-support-with-dock-agents): Triage, drafting, and routing become owned work, and the angry customer never gets an answer from anyone but you.
- [Run your hiring pipeline with Dock agents](https://trydock.ai/blog/run-your-hiring-pipeline-with-dock-agents): Sourcing, screening prep, and scheduling become owned work. The judgment about people stays exactly where it was.
- [Run your sales outreach with Dock agents](https://trydock.ai/blog/run-your-sales-outreach-with-dock-agents): The shape of an outbound motion when agents carry the execution: list, first touch, triage, escalation.
- [Run your social content with Dock agents](https://trydock.ai/blog/run-your-social-content-with-dock-agents): A content calendar that fires on schedule whether or not anyone remembered it was Tuesday.
- [Run your website operations with Dock agents](https://trydock.ai/blog/run-your-website-operations-with-dock-agents): The site work nobody owns, checks, updates, SEO hygiene, becomes a table an agent keeps current.
- [Run your weekly reporting with Dock agents](https://trydock.ai/blog/run-your-weekly-reporting-with-dock-agents): Pull the numbers, write the readable version, send it on time, every week, including the busy ones.
- [AI workspace for startups and founders: one surface instead of ten tools](https://trydock.ai/blog/ai-workspace-for-startups-and-founders): Startups run lean and stitch together point tools. An agent-native AI workspace collapses board prep, investor updates, research, and ops into one surface where agents do the first pass and founders review. Flat pricing means the bill does not punish you for using agents heavily.
- [AI workspace vs chat assistant: where should your team's work actually live?](https://trydock.ai/blog/ai-workspace-vs-chat-assistant): A chat assistant is where you ask; an AI workspace is where the answer persists, gets reviewed, and compounds. The difference is whether your team's work survives the end of a conversation.
- [Best AI workspace for AI agents in 2026: the buyer guide](https://trydock.ai/blog/best-ai-workspace-for-ai-agents): The best AI workspace for AI agents is one where agents are first-class citizens with their own identity and the workspace is the persistent system of record for their work. Here is how to evaluate the category against the five shifts that matter.
- [Best AI workspace for teams running AI agents](https://trydock.ai/blog/best-ai-workspace-for-teams-running-agents): When a team runs multiple agents, the workspace has to attribute every action to the right actor and owner. The best AI workspace for teams is the one built for many humans and many agents on one surface, with a dual-keyed audit trail.
- [Coda and Airtable alternative for AI agents: from automation to accountable agents](https://trydock.ai/blog/coda-airtable-alternative-for-ai-agents): Coda and Airtable are strong at structured docs and databases with automation and AI fields. The gap for agent work is identity and attribution: their AI runs as automation, not as a named agent with its own credential and audit trail. An agent-native workspace closes that gap.
- [How to choose an AI workspace: a criteria-based buyer guide](https://trydock.ai/blog/how-to-choose-an-ai-workspace): Choosing an AI workspace comes down to five questions: does it hold live state, does work persist, can multiple actors collaborate with attribution, do agents have their own identity, and is it locked to one model vendor. This guide turns each into a test you can run on any tool.
- [How to migrate from Notion to Dock for agent workflows](https://trydock.ai/blog/migrate-from-notion-to-dock): Migrating from Notion to Dock means moving your docs and databases to surfaces your agents can act on with attribution. This is a practical guide: what maps cleanly, what changes, and how to re-point your agents.
- [Notion alternative for AI agents: when an AI assistant in a doc is not enough](https://trydock.ai/blog/notion-alternative-for-ai-agents): Notion is a mature docs and database tool with an AI assistant layered on. If you need AI agents with their own identity and an audited trail of what they did, an agent-native workspace is the alternative built for that job.
- [Use Dock inside ChatGPT: give your ChatGPT agents a persistent workspace](https://trydock.ai/blog/use-dock-inside-chatgpt): You do not have to leave ChatGPT to use Dock. Through MCP, your ChatGPT agent reads and writes Dock surfaces directly, so the work it does persists in a shared workspace instead of scrolling away in the chat.
- [Use Dock inside Claude: a shared workspace your Claude agents write to](https://trydock.ai/blog/use-dock-inside-claude): Claude speaks MCP, and Dock is an MCP-native workspace. Your Claude agent can read and write Dock surfaces from inside Claude, so its research, drafts, and decisions land in a persistent shared record instead of a single conversation.
- [Dock for Accounting: AP invoice routing with consent-gated payments](https://trydock.ai/blog/accounting-ap-invoice-routing): AP teams run agents for OCR, GL coding, and policy checks. Where it breaks is the approval chain. Dock is the workspace where the invoice queue lives with attributed agent edits, and the consent gate fires the actual payment back through Ramp, Brex, or QBO only after the right human signs off.
- [Dock for Accounting: AR collections workspaces with attributed dunning](https://trydock.ai/blog/accounting-ar-collections): AR teams use agents for aging analysis, dunning draft generation, payment-promise tracking. The breakdown is where the collections conversation persists with the customer's whole history. Dock is the workspace; QBO, NetSuite, or Sage Intacct stays the books.
- [Dock for Accounting: audit packet prep with dual-keyed sign-off](https://trydock.ai/blog/accounting-audit-packet): Audit packet prep is the workflow where agent attribution pays the biggest dividend. Every assertion the agent makes carries a human counter-signature. Dock is the workspace where the audit memo, the supporting schedules, and the dual sign-offs live in one place, ready for external auditors.
- [Dock for Accounting: expense categorization with policy enforcement](https://trydock.ai/blog/accounting-expense-categorization): Expense categorization is the workflow where agent autonomy is highest and where bad data leaks straight into the GL. Dock is the workspace where the agent's coding decision lives with the policy verdict and the human review, while Ramp, Brex, and Concur stay the source of truth for the actual receipts.
- [Dock for Accounting: month-end close with attributed reconciliation](https://trydock.ai/blog/accounting-month-end-close): Month-end close is where AI agents move fastest in accounting. Variance flaggers, recon agents, narrative drafters. The breakdown is the audit trail. Dock is the workspace where every close decision lives, attributed to agent or human, with the books staying in QBO / Xero / NetSuite / Sage Intacct.
- [Dock for compliance: audit-evidence collection with named auditor sign-off](https://trydock.ai/blog/compliance-audit-evidence): Dock turns audit-evidence collection into a structured agent workflow: the agent pulls control evidence from AuditBoard and Vanta, packages it for the external auditor, and the auditor's named sign-off persists on the row.
- [Dock for compliance: ISO 27001 control mapping with agent-drafted SoA](https://trydock.ai/blog/compliance-iso-27001): Vanta holds the raw control evidence. Dock holds the agent's mapping from each Annex A control to that evidence, with the ISMS lead's approval recorded on every row.
- [Dock for compliance: policy review and agent-drafted updates with named approver](https://trydock.ai/blog/compliance-policy-management): Use Dock to run policy reviews where an agent reads OneTrust and Drata, drafts updates against regulation drift, and routes each redline to a named policy owner for approval.
- [Dock for compliance: risk assessment with agent-drafted threat models](https://trydock.ai/blog/compliance-risk-assessment): Dock pairs AuditBoard and ServiceNow GRC asset inventories with an agent that drafts the risk register, so the risk committee approves a structured artifact instead of a blank spreadsheet.
- [Dock for compliance: SOC 2 readiness workflow with attributed control evidence](https://trydock.ai/blog/compliance-soc2-readiness): Vanta, Drata, and AuditBoard collect control evidence. Dock holds the agent's interpretation of that evidence, attributed to a named agent and a human reviewer, so auditors can trace every line in the readiness packet.
- [Dock for consulting: client-research workflow with attributed analyst review](https://trydock.ai/blog/consulting-client-research): Dock runs the consulting client-research workflow with an attributed agent draft, an analyst approval, and a partner sign-off. Notion, Hex, and Mode stay the systems of record for raw inputs.
- [Dock for consulting: deliverable-drafting workflow with attributed partner review](https://trydock.ai/blog/consulting-deliverable-drafting): Consulting agents draft deliverables from engagement notes and research, then partners approve in Dock before the file leaves the firm. Every revision carries the agent name, partner name, and timestamp.
- [Dock for consulting: knowledge-management workflow with attributed senior-consultant review](https://trydock.ai/blog/consulting-knowledge-management): Dock turns recent engagements into reviewed, reusable case-study updates. The agent drafts. A senior consultant approves. Every row carries identity and a pointer back to Notion, Confluence, and Drive.
- [Dock for consulting: client meeting-prep workflow with attributed account team](https://trydock.ai/blog/consulting-meeting-prep): Dock turns client meeting prep into an attributed workflow. An agent reads Notion history and the Calendly agenda, drafts a prep brief in Google Docs, and the named account team approves before the call.
- [Dock for consulting: proposal-writing workflow with attributed sales-lead review](https://trydock.ai/blog/consulting-proposal-writing): Dock runs proposal drafting across Notion, Google Workspace, and Pitch. The agent reads the RFP and capability library, drafts, and waits for partner plus sales-lead sign-off before sending.
- [Dock for CS: customer-onboarding workflow with attributed CSM hand-off](https://trydock.ai/blog/cs-customer-onboarding): Dock holds the agent's onboarding interpretation, the CSM accepts or rewrites it, and Zendesk, Gainsight, and HubSpot keep the source records.
- [Dock for CS: escalation-policy workflow with attributed VP-CX approver](https://trydock.ai/blog/cs-escalation-policy): Dock holds the CS escalation policy as a living workspace. The agent reads Zendesk, Gainsight, and Salesforce history, drafts new thresholds, and the VP of CX approves with a signed timestamp.
- [Dock for CS: customer-feedback synthesis with attributed product owner](https://trydock.ai/blog/cs-feedback-synthesis): Run an agent that synthesizes tickets from Zendesk and Intercom plus interview notes, drafts an insights memo, and routes it to a named product owner for review. Every claim in the memo links back to the source ticket and the agent that read it.
- [Dock for CS: knowledge management workflow with attributed editor review](https://trydock.ai/blog/cs-knowledge-management): An agent reads recent Zendesk and Help Scout tickets, drafts knowledge base updates for Confluence, and a human editor approves publication. Dock holds the drafts, the diffs, and the reviewer attribution.
- [Dock for CS: ticket-routing workflow with attributed support-team owner](https://trydock.ai/blog/cs-ticket-routing): Dock runs ticket routing as an agent-drafted, human-approved decision. The agent reads the Zendesk, Intercom, or Freshdesk ticket plus customer signals, proposes a queue and owner, and a support-team lead approves before the routing fires.
- [Dock for data analytics: dashboard review workflow with attributed business owner](https://trydock.ai/blog/data-dashboard-review): Run dashboard reviews in Dock by having the agent read usage and freshness from Looker, Hex, and Mode, draft a review packet, and route each dashboard to a named business owner who approves before anything is archived.
- [Dock for data analytics: A/B experiment review with attributed analyst](https://trydock.ai/blog/data-experimentation): Dock turns an Eppo or Statsig experiment readout into a structured decision memo with an attributed analyst-lead reviewer, so ship-or-kill calls carry a name, a timestamp, and a trail back to the underlying dbt model.
- [Dock for data analytics: metric definition workflow with attributed semantic owner](https://trydock.ai/blog/data-metric-definitions): Dock holds the agent's drafted metric definition, the lineage and usage evidence it read, and the semantic owner who approved it. dbt Cloud, Looker, and Snowflake remain the source of truth for code, dashboards, and warehouse state.
- [Dock for data analytics: pipeline monitoring with attributed engineering on-call](https://trydock.ai/blog/data-pipeline-monitoring): Dock for data pipeline monitoring lets an agent read Airflow, dbt, and Datadog signals, draft an incident summary, and route remediation to data engineering for approval. Every action carries agent identity, decision, and timestamp.
- [Dock for data analytics: data-quality workflow with attributed incident response](https://trydock.ai/blog/data-quality-monitoring): Dock turns Monte Carlo alerts, dbt test failures, and Snowflake freshness gaps into attributed incident briefs. The agent drafts, the data lead approves, and every remediation step carries identity, timestamp, and a pointer back to the source platform.
- [Dock for Design: accessibility review workspaces with attributed agent audits](https://trydock.ai/blog/design-accessibility-review): Figma and the live site hold the artifacts. Dock is the accessibility-review table where the agent's WCAG audit, color-contrast pass, screen-reader trace, and remediation rows live, with the a11y lead signing off before publish.
- [Dock for Design: brand asset production at scale with attributed agent edits](https://trydock.ai/blog/design-brand-asset-production): The brand system lives in Adobe CC and Figma. Dock is the asset-production queue where the brief, agent-generated variations, brand-system check, and reviewer decision live, with one row per delivered asset.
- [Dock for Design: brief and review tables your agents can fill in and your editors trust](https://trydock.ai/blog/design-brief-and-review): The brief lives in scattered Slack threads; the review lives in canvas comments. Dock is the persistent brief-and-review table where the agent posts variations, rationale, and links back to Figma nodes, while the design lead signs off in one place.
- [Dock for Design: component library maintenance with attributed agent variations](https://trydock.ai/blog/design-component-library): The component library lives in Figma or Storybook. Dock is the maintenance table where the agent posts proposed variants, deprecations, and usage audits, with the design system lead approving before any library change ships.
- [Dock for Design: design-to-engineering handoff with attributed agent specs](https://trydock.ai/blog/design-handoff-to-engineering): Figma's Dev Mode shows the spec; the implementation ticket lives in Jira or Linear. Dock is the handoff workspace where the agent posts the spec summary, component mapping, edge cases, and engineering questions, with the engineering lead acking before the ticket is taken.
- [Dock for DevOps: cloud cost optimization with attributed engineering trade-off](https://trydock.ai/blog/devops-cost-optimization): Run cloud cost optimization through Dock so an agent reads AWS spend, Datadog utilization, and GCP billing, then drafts a memo an engineering lead approves with the trade-off attributed on the record.
- [Dock for DevOps: deploy-gating workflow with attributed roll-forward decision](https://trydock.ai/blog/devops-deploy-gating): Dock turns deploy-gating into a recorded decision. The agent reads the GitHub Actions pipeline, the Datadog burn rate, and the ArgoCD sync state, drafts a roll-forward recommendation, and a named engineer approves before the promotion is allowed to run.
- [Dock for DevOps: incident-response workflow with attributed post-mortem](https://trydock.ai/blog/devops-incident-response): Dock turns PagerDuty pages, Datadog signals, and GitHub deploys into one attributed timeline. The agent drafts the post-mortem; the on-call lead approves before it ships.
- [Dock for DevOps: runbook maintenance with agent-drafted updates](https://trydock.ai/blog/devops-runbook-maintenance): Point an agent at recent PagerDuty incidents, let it draft Confluence runbook patches with GitHub commit links, then have the on-call lead approve each diff in a Dock row before the page changes.
- [Dock for DevOps: SLI/SLO tracking with agent-drafted error-budget reports](https://trydock.ai/blog/devops-sli-slo-tracking): Dock lets an agent read SLI telemetry from Datadog, Honeycomb, and PagerDuty, draft a weekly error-budget report, and route policy changes to the eng lead for review.
- [Dock + Adobe Creative Cloud: brand asset workflows with attributed agent edits](https://trydock.ai/blog/dock-adobe-creative-cloud): Adobe Creative Cloud holds the source files (PSD, AI, INDD). Dock is where the brief, the agent's asset variations, the brand-system check, and the reviewer sign-off live, with pointers back to the CC Libraries asset id.
- [Dock + Affinity: deal CRM with agent-drafted relationship intel and attributed reviewer](https://trydock.ai/blog/dock-affinity-crm): Pair Affinity's relationship graph with Dock so an agent drafts the relationship brief, a named partner signs off, and every claim points back to the source contact record.
- [Dock + Ahrefs: keyword research workspaces your agents fill in and reviewers approve](https://trydock.ai/blog/dock-ahrefs-keyword-research): Ahrefs holds the keyword corpus, volume, KD, and SERP data. Dock is where the agent's shortlist, intent classification, and content briefs live, attributed and resumable, with a reviewer column before anything ships.
- [Dock + AngelList: syndicate deal flow with attributed lead-investor review](https://trydock.ai/blog/dock-angellist-investors): Pair AngelList syndicates with Dock so every agent-screened deal brief carries a lead-investor sign-off, a Carta pointer, and a timestamped decision.
- [Dock + ArgoCD: GitOps deployments with agent-drafted sync rationale](https://trydock.ai/blog/dock-argocd-gitops): When an agent triggers an ArgoCD application sync, Dock holds the rationale, the diff summary, and the on-call approval. ArgoCD stays the deployment engine; Dock becomes the audit trail.
- [Dock + Asana: agency project workflows with attributed account lead](https://trydock.ai/blog/dock-asana-agency): Asana stays the project plan of record. Dock holds the agent's client-status read and the account lead's sign-off, with a pointer back to the Asana task.
- [Dock + Asana: agent-drafted status updates with attributed PM review](https://trydock.ai/blog/dock-asana-projects): Connect Asana to Dock so a project agent drafts weekly status updates from task progress, and a PM signs off in one place with the decision attributed back to the source records.
- [Dock + athenahealth: practice-management workflows with attributed claim review](https://trydock.ai/blog/dock-athenahealth-practice): Run athenahealth claim review through Dock so the billing agent's denial rationale, payer logic, and reviewer sign-off live in one attributed row instead of a free-text note.
- [Dock + Confluence: agent-drafted runbook updates with attributed review](https://trydock.ai/blog/dock-atlassian-confluence-runbooks): Dock lets an agent draft a Confluence runbook update as a structured proposal, route it to the on-call reviewer, and publish only after an attributed approval lands.
- [Dock + AuditBoard: internal-audit workflows with agent-drafted findings](https://trydock.ai/blog/dock-auditboard-internal-audit): AuditBoard holds the issue record. Dock holds the agent's draft finding, the audit-team approval, and the identity trail behind every published result.
- [Dock + BambooHR: small-team HR workflows with attributed reviewer](https://trydock.ai/blog/dock-bamboohr-small-teams): BambooHR stays the system of record for employee data. Dock holds the agent's policy reads and comp adjustment proposals, each row attributed to a reviewer before anything writes back.
- [Dock + BigCommerce: enterprise stores with attributed agent edits](https://trydock.ai/blog/dock-bigcommerce-enterprise): BigCommerce teams running multi-storefront enterprise setups already have agents. The breakdown is shared state across stores. Dock is the workspace where the agent's interpretive work lives, attributed and resumable, while BigCommerce stays source of truth.
- [Dock + Blackboard: higher-ed course design with attributed faculty review](https://trydock.ai/blog/dock-blackboard-learn): Blackboard Learn and Canvas hold the course shell. Dock holds the agent's design decisions, the faculty sign-off, and the audit trail behind every learning objective.
- [Dock + BoldTrail: lead nurture and offer drafting with attributed agent](https://trydock.ai/blog/dock-boldtrail-crm): BoldTrail and Real Geeks hold the lead and the listing. Dock holds the agent's outreach brief, drafted offer language, and the human sign-off that put it in motion.
- [Dock + Canvas LMS: lesson plans and grading rationale with attributed instructor sign-off](https://trydock.ai/blog/dock-canvas-lms): Dock pairs with Canvas to record what an instructional agent drafted, why it graded the way it did, and which instructor signed off, with every row pointing back to the Canvas course of record.
- [Dock + Carta: cap-table and founder-equity workflows with attributed CFO review](https://trydock.ai/blog/dock-carta-founders): Carta and Pulley stay the cap-table system of record. Dock holds the agent's summary of each share issuance and the named CFO sign-off, so founders can prove who approved every grant.
- [Dock + Carta: portfolio data with agent-drafted monitoring brief and named partner](https://trydock.ai/blog/dock-carta-investors): Carta holds the cap tables and round data. Dock holds the agent's monitoring brief, the partner of record, and the timestamp of every flag.
- [Dock + Oracle Health: enterprise EHR workflows with attributed clinician review](https://trydock.ai/blog/dock-cerner-oracle-health): Oracle Health (Cerner) holds the encounter. Dock holds the agent's interpretive brief plus the clinician's attributed sign-off, with every row pointing back to the Millennium record.
- [Dock + Clearscope and SurferSEO: content optimization with attributed agent edits](https://trydock.ai/blog/dock-clearscope-content): Clearscope and SurferSEO score the draft against the SERP. Dock is where the agent's edit history, score progression, and reviewer approvals live, so the editor sees who changed what and why.
- [Dock + ClickUp: agent-drafted project briefs with attributed stakeholder review](https://trydock.ai/blog/dock-clickup-projects): Dock turns a ClickUp task hierarchy into an agent-drafted project brief, with every scope decision attributed to the agent that wrote it and the stakeholder who signed off.
- [Dock + CoStar: commercial property research with attributed broker review](https://trydock.ai/blog/dock-costar-real-estate): Dock turns CoStar property records into a comp-set brief with a broker sign-off and a pointer back to the source listing. Every line is attributed to the agent that drafted it.
- [Dock + Coupa: agent-drafted vendor diligence with attributed approval cascade](https://trydock.ai/blog/dock-coupa-procurement): Coupa stays the requisition system of record. Dock holds the agent-drafted diligence brief and the dual-keyed approval that releases the PO.
- [Dock + CrowdStrike Falcon: endpoint detection with agent-drafted containment](https://trydock.ai/blog/dock-crowdstrike-edr): When Falcon raises a high-severity detection, the SOC agent opens a Dock containment brief, attaches Splunk context, and waits for analyst approval before any host is isolated.
- [Dock + Culture Amp: engagement-survey synthesis with attributed action plan](https://trydock.ai/blog/dock-culture-amp-engagement): Dock turns Culture Amp engagement results into an attributed theme synthesis and a leader action plan, with every commitment tied back to the Culture Amp survey it came from.
- [Dock + Datadog: deploy monitoring with agent-drafted regression report](https://trydock.ai/blog/dock-datadog-devops): Datadog stays the source of metrics and traces. Dock stores the agent's regression read of a deploy, the roll-forward or roll-back decision, and the human who signed off.
- [Dock + Datadog: agent-interpreted observability findings with named owner](https://trydock.ai/blog/dock-datadog-observability): Datadog holds the raw telemetry. Dock holds the agent's interpretation of that telemetry, named-owner remediation, and the PagerDuty handoff record.
- [Dock + Datadog Security: agent-drafted security finding with attributed analyst](https://trydock.ai/blog/dock-datadog-security): When a Datadog Security signal fires, an agent drafts a finding brief in Dock with the MITRE technique, blast radius, and recommended action, then a named analyst signs off before any containment runs.
- [Dock + dbt Cloud: agent-drafted model changes with attributed peer review](https://trydock.ai/blog/dock-dbt-cloud): Dock pairs with dbt Cloud and Snowflake so analytics agents can draft model changes, log rationale, and route attributed peer review without losing the audit trail.
- [Dock + Drata: multi-framework compliance with agent-drafted gap analysis](https://trydock.ai/blog/dock-drata-frameworks): Drata holds the framework controls and evidence collectors. Dock holds the agent's gap interpretation, remediation queue, and reviewer sign-off, one row per control.
- [Dock + Drata: multi-framework security with agent-drafted attestation packet](https://trydock.ai/blog/dock-drata-security): Drata holds the continuous control evidence. Dock holds the agent's drafted attestation packet, the auditor sign-off, and the decision trail behind each control assertion.
- [Dock + Epic: HIPAA-safe chart workflows with agent-drafted notes](https://trydock.ai/blog/dock-epic-ehr): Epic stays the chart of record. Dock holds the agent's draft note, the clinician sign-off, and the audit trail back to the Epic encounter ID.
- [Dock + Figma: design ops your agents can act on, with attributed reviews and component decisions](https://trydock.ai/blog/dock-figma-design-ops): Figma stays the canvas. Dock is where the brief, the agent's variation rationale, the review thread, and the component approval live, with pointers back to figma_file_key and figma_node_id so the source files are never duplicated.
- [Dock for Accounting: a shared close, attributed, with the agent's work persistent](https://trydock.ai/blog/dock-for-accounting): Bookkeeping with AI agents already happens — coding transactions, reconciling accounts, flagging variances. What's missing is the substrate where the agent's work persists, attributed, reviewable, and resumable across the month-end close.
- [Dock for Compliance: a workspace where every regulatory check, the agent's reading of it, and the human sign-off all live together](https://trydock.ai/blog/dock-for-compliance): Compliance teams already use AI to read regulations, flag risk, and prepare audit packets. The breakdown is everywhere the agent's interpretive work goes. Dock is the substrate where that work persists, attributed and reviewable, while ServiceNow and Vanta stay the source of truth.
- [Dock for consulting and agencies: a workspace where client deliverables, agent-drafted analyses, and reviewer attribution persist](https://trydock.ai/blog/dock-for-consulting-and-agencies): Consulting and creative agencies use AI for deliverable drafting, research synthesis, and client-meeting prep. The breakdown is the client-by-client trail. Notion, Asana, and Google Drive stay the surface. Dock holds the deliverable draft, the analysis rationale, and the partner sign-off.
- [Dock for customer support: a workspace where agent triage, response drafting, and the human escalation log all attribute](https://trydock.ai/blog/dock-for-customer-support): Support teams use AI for ticket triage, macro generation, and response drafting. The breakdown is the escalation log. Zendesk, Intercom, and Freshdesk stay the system of record. Dock holds the agent's triage rationale, the response draft, and the human-reviewed escalation.
- [Dock for data analytics: a workspace where agent-built dashboards, query reviews, and metric definitions persist](https://trydock.ai/blog/dock-for-data-analytics): Data teams use AI for SQL drafting, dashboard generation, and metric-definition review. Snowflake, dbt, and Looker stay the source of truth; Dock holds the agent's query draft, the metric rationale, and the analyst sign-off.
- [Dock for Design: a workspace where briefs, reviews, and agent-drafted variations actually persist](https://trydock.ai/blog/dock-for-design): Design teams already use AI — Figma plugins for component variants, agents drafting brand variations, copy-and-image generators for assets. The breakdown is where the brief lives, where review lands, what survives the handoff. Figma stays the canvas. Dock is the substrate around it.
- [Dock for DevOps: a workspace where deploy decisions, on-call runbooks, and post-mortems have attribution](https://trydock.ai/blog/dock-for-devops): DevOps teams use AI for deploy gating, on-call runbook drafting, and post-mortem synthesis. GitHub, ArgoCD, and Datadog stay the source of truth. Dock holds the agent's deploy-readiness check, the on-call runbook decision, and the post-mortem draft.
- [Dock for Ecommerce: a shared substrate for the team and the agents running your store](https://trydock.ai/blog/dock-for-ecommerce): Most ecommerce teams already run agents against Shopify and Stripe. The breakdown is everywhere else: where the agent writes its work, who reviews it, what the audit trail looks like when a regulator or a chargeback dispute asks. Dock is the substrate that fixes specifically that.
- [Dock for education: a workspace where lesson plans, agent-drafted assessments, and grading-rationale persist](https://trydock.ai/blog/dock-for-education): Education teams use AI for lesson-plan drafting, assessment generation, and grading-rationale synthesis. The breakdown is the institutional trail. Canvas and Google Classroom stay the source. Dock holds the lesson plan, the assessment rationale, and the educator sign-off.
- [Dock for founders: a workspace where agent-drafted board materials, investor updates, and roadmap context persist](https://trydock.ai/blog/dock-for-founders): Founders use AI for board-deck drafting, investor-update synthesis, and roadmap memos. The breakdown is the recurring rhythm. Notion, Pitch, and Google Workspace stay the surface; Dock holds the agent's draft, the founder's edits, and the named recipient log.
- [Dock for healthcare operations: a workspace where clinical-workflow agents, patient-safety review, and audit trails persist](https://trydock.ai/blog/dock-for-healthcare-operations): Healthcare-ops teams use AI for chart review, prior-authorization drafting, and patient-throughput analysis. The breakdown is HIPAA-safe attribution. Epic and Cerner stay the system of record. Dock holds the agent's read of the chart, the prior-auth draft, and the clinician sign-off.
- [Dock for investors: a workspace where deal memos, portfolio-monitoring agents, and LP-update threads attribute](https://trydock.ai/blog/dock-for-investors): Investors use AI for deal-memo drafting, portfolio monitoring, and LP-update synthesis. The breakdown is the recurring rhythm. Affinity and Carta stay the system of record. Dock holds the deal memo, the portfolio-monitoring rationale, and the partner sign-off.
- [Dock for IT Operations: a workspace where agent-driven runbooks, incident triage, and change control all attribute back to a human](https://trydock.ai/blog/dock-for-it-operations): IT operations teams use AI to triage tickets, draft runbook steps, and propose change requests. Dock is the workspace that holds the agent's interpretive work, attributed to the engineer who approved it.
- [Dock for marketing: a workspace where campaign briefs, agent-drafted copy, and reviewer approvals persist](https://trydock.ai/blog/dock-for-marketing): Marketing teams use AI for campaign brief drafting, copy generation, and performance analysis. The breakdown is the brief-to-publish cascade. HubSpot, Marketo, and Salesforce Marketing Cloud stay the system of record. Dock holds the brief, the agent copy variants, and the brand sign-off.
- [Dock for People Ops: a workspace where agent-drafted policies, employee research, and review cycles persist with attribution](https://trydock.ai/blog/dock-for-people-ops): People-ops teams already use AI to draft policies, prepare performance briefs, and synthesize survey data. The breakdown is the policy lifecycle. Workday and Lattice stay the system of record. Dock holds the agent's policy draft, employee research, and the named human review.
- [Dock for Procurement: a workspace where vendor research, contract terms, and approval cascades have attribution](https://trydock.ai/blog/dock-for-procurement): Procurement teams use AI for vendor due diligence, contract redlining, and approval-cascade drafting. The breakdown is the cascade itself. Coupa and SAP Ariba stay the system of record. Dock holds the vendor diligence brief, the contract risk assessment, and the dual-keyed approval trail.
- [Dock for project management: a workspace where agent-drafted plans, status updates, and risk logs persist with attribution](https://trydock.ai/blog/dock-for-project-management): Dock is the project management workspace where AI agents draft status pulses, risk logs, and resource plans across Asana, Linear, and Jira, and a human PM signs off with attribution.
- [Dock for real estate: a workspace where deal pipeline, agent-drafted offers, and inspection notes all attribute](https://trydock.ai/blog/dock-for-real-estate): Real-estate teams use AI for deal pipeline tracking, offer drafting, and inspection-note synthesis. The breakdown is the deal lifecycle. MLS systems and CoStar stay the source. Dock holds the pipeline brief, the offer draft, and the broker sign-off.
- [Dock for security operations: a workspace where threat triage, incident response, and SOC2 control evidence all attribute](https://trydock.ai/blog/dock-for-security-operations): Security teams use AI for alert triage, incident-response drafting, and control-evidence collection. The breakdown is the audit trail. Splunk, CrowdStrike, and Vanta stay the source of truth. Dock holds the agent's triage rationale, the incident-response runbook, and the named analyst sign-off.
- [Dock for SEO: a workspace where your agents' research, drafts, and audits persist](https://trydock.ai/blog/dock-for-seo): SEO teams already run AI agents — keyword researchers, content drafters, link-graph analyzers, page auditors. The breakdown is everywhere the agent's interpretive work goes. Dock is the substrate where that work lives, attributed and resumable, while Google Search Console and Ahrefs stay the source of truth.
- [Dock + Framer: web design workspaces with attributed agent variations](https://trydock.ai/blog/dock-framer-web-design): Framer holds the visual canvas and the production code. Dock is where the brief, the agent's variation rationale, the A/B reasoning, and the reviewer sign-off live, with pointers back to the Framer project and page node id.
- [Dock + Freshdesk: agent-drafted SLA tracking with attributed support-ops approver](https://trydock.ai/blog/dock-freshdesk-cs): Freshdesk holds the ticket. Dock holds the agent's SLA brief and the named human who approved the path forward.
- [Dock + GitHub Actions: agent-drafted deploy gates with attributed engineer approval](https://trydock.ai/blog/dock-github-actions): GitHub Actions runs the pipeline and ArgoCD rolls the release. Dock holds the agent-drafted deploy-readiness brief and the engineer sign-off attached to it, so every promotion has a named reviewer on record.
- [Dock + Google Classroom: K-12 lesson plans and feedback with attributed teacher review](https://trydock.ai/blog/dock-google-classroom): Use Google Classroom and Canvas as the assignment system of record. Use Dock as the record of what the AI lesson agent drafted, which teacher signed off, and when.
- [Dock + Google Search Console: performance ops your agents can act on, with attributed audits](https://trydock.ai/blog/dock-google-search-console): Google Search Console holds the impressions, clicks, and CTR data. Dock is where the agent's prioritized fix list, page-by-page hypotheses, and reviewer decisions live. Each Dock row points back to the GSC query or page so the source of truth stays in Google.
- [Dock + Google Workspace: consulting deliverables with attributed reviewer chain](https://trydock.ai/blog/dock-google-workspace-consulting): Google Docs holds the deliverable. Dock holds the agent's review brief, the partner approval, and the named chain of who signed off and when.
- [Dock + Google Workspace: founder docs with attributed exec review](https://trydock.ai/blog/dock-google-workspace-founders): Google Docs holds the raw draft. Dock holds the agent's narrative interpretation, the exec who signed off, and the timestamp on the decision.
- [Dock + Gorgias: ecommerce support workflows with attributed merchandising sign-off](https://trydock.ai/blog/dock-gorgias-cs): Pair Gorgias tickets with a Dock RMA brief so the support agent drafts a return, merchandising signs off, and every decision carries the agent name, the ticket pointer, and the timestamp.
- [Dock + Gusto: agent-assisted payroll review with named approver](https://trydock.ai/blog/dock-gusto-payroll): Gusto holds the pay-run records. Dock holds the agent's anomaly review and the named payroll lead's approval before run.
- [Dock + Harvest: time-tracking and project profitability with attributed PM sign-off](https://trydock.ai/blog/dock-harvest-time): Harvest stays the system of record for time entries. Dock holds the agent's budget brief, the PM's approval, and the audit trail. Each row points back to the Harvest project and the Asana task.
- [Dock + Help Scout: small-team support workflows with attributed editor review](https://trydock.ai/blog/dock-help-scout-cs): Connect Help Scout to Dock so the agent drafts a response brief in a shared table, an editor approves it, and every reply carries an attributed audit trail back to the conversation.
- [Dock + Hex: agent-drafted notebook analysis with named reviewer](https://trydock.ai/blog/dock-hex-notebooks): An agent drafts a Hex notebook against Snowflake and dbt models, then logs the interpretation in Dock for a named analyst lead to approve before the notebook is published.
- [Dock + HubSpot Marketing Hub: agent-drafted campaign briefs with attributed brand sign-off](https://trydock.ai/blog/dock-hubspot-marketing): Run agent-drafted HubSpot campaigns through a Dock brief table where every brand decision carries an agent identity, a reviewer, and a timestamp. The campaign object stays in HubSpot. The judgment lives in Dock.
- [Dock + Intercom: agent-drafted conversation routing with attributed conversation owner](https://trydock.ai/blog/dock-intercom-cs): Intercom holds the conversation thread. Dock holds the agent's routing brief, the owner sign-off, and the audit trail that ties them together.
- [Dock + Ironclad: contract redlining for procurement with attributed sign-off](https://trydock.ai/blog/dock-ironclad-procurement): Ironclad runs the contract workflow and signature. Dock holds the redline rationale, the counsel sign-off, and the audit trail your procurement team needs at renewal.
- [Dock + Iterable: cross-channel lifecycle with attributed lifecycle owner](https://trydock.ai/blog/dock-iterable-lifecycle): Run an Iterable lifecycle flow through a Dock orchestration brief so every send carries a named lifecycle owner, an agent decision trail, and a pointer back to the journey node.
- [Dock + Jira: agent-drafted risk logs with attributed PM review](https://trydock.ai/blog/dock-jira-projects): An agent reads Jira issues and comment threads, then drafts risk-log updates in Dock that a named PM approves. Jira stays the system of record for the issue; Dock records what the agent interpreted, who reviewed it, and when.
- [Dock + Jira Service Management: agent-drafted change requests with dual-keyed approval](https://trydock.ai/blog/dock-jira-service-management): Jira Service Management holds the change request and CAB record. Dock holds the agent's rationale, blast radius assessment, and dual-keyed approval before the change ever leaves draft.
- [Dock + Klaviyo: lifecycle workspaces with attributed campaign drafts](https://trydock.ai/blog/dock-klaviyo-lifecycle): Klaviyo holds your email and SMS lifecycle data. Agents already draft campaigns, segment audiences, predict churn. The breakdown is where the campaign brief and the AI's reasoning persist. Dock is the workspace, Klaviyo stays the source of truth, and the consent gate fires only after a human approves the send.
- [Dock + Lattice: performance-review prep with agent-drafted briefs](https://trydock.ai/blog/dock-lattice-performance): Pair Lattice as the system of record for review cycles with Dock as the workspace where the agent drafts manager prep briefs, captures sign-off, and leaves a per-row audit trail.
- [Dock + Linear: founder-track roadmap with attributed eng-lead review](https://trydock.ai/blog/dock-linear-founders): Linear holds the issues and cycles. Dock holds the founder narrative the agent drafts from them, plus the eng-lead approval that lets a roadmap update ship.
- [Dock + Linear: agent-drafted sprint retros with attributed engineering lead](https://trydock.ai/blog/dock-linear-issues): Point a coding agent at Linear cycles and GitHub PRs and let it draft the retro. The draft lands in Dock with eng-lead sign-off, full attribution, and a pointer back to every issue it read.
- [Dock + Looker: agent-drafted dashboard reviews with attributed business owner](https://trydock.ai/blog/dock-looker-bi): An agent reads a Looker dashboard, drafts a review brief in Dock, and routes it to the named business owner for sign-off. Looker stays the metric source; Dock records the interpretation and the human decision.
- [Dock + Mailchimp: small-team email marketing with attributed editor review](https://trydock.ai/blog/dock-mailchimp-marketing): Mailchimp holds the campaigns and audiences. Dock holds the agent-written copy briefs and the named editor approval that gates each send.
- [Dock + Marketo: enterprise nurture programs with attributed reviewer chain](https://trydock.ai/blog/dock-marketo): Dock pairs with Marketo to capture the agent interpretation, brand sign-off, and legal review behind every nurture program, while Marketo stays the system of record for sends and engagement.
- [Dock + MLS: residential listings with attributed listing-agent review](https://trydock.ai/blog/dock-mls-real-estate): Dock turns each MLS listing into a row with an agent-drafted comp summary and a signed listing-agent review, while the MLS stays the system of record for the listing data.
- [Dock + Mode: agent-drafted ad-hoc analyses with attributed audit trail](https://trydock.ai/blog/dock-mode-analytics): An analyst agent drafts the Mode report against Snowflake and dbt models, then writes the interpretation to a Dock review row that a senior analyst signs off before the report is shared.
- [Dock + Monday.com: agent-drafted resource plans with attributed PMO sign-off](https://trydock.ai/blog/dock-monday-projects): Connect Monday.com and Asana to Dock so an agent can draft resource plans from board data, then route each plan to the PMO for attributed sign-off.
- [Dock + NetSuite: mid-market ERP with attributed agent edits](https://trydock.ai/blog/dock-netsuite-erp): NetSuite is the mid-market ERP default. Agents already draft journal entries, flag intercompany variances, propose multi-subsidiary reclasses. Dock is the workspace where the agent's reasoning persists, attributed, while NetSuite stays the financial system of record.
- [Dock + NetSuite: procurement workflows with agent-drafted PO matching](https://trydock.ai/blog/dock-netsuite-procurement): Pair Oracle NetSuite and Coupa with Dock so an agent can draft a three-way match the moment a purchase order, receipt, and vendor bill are all present, and route the result to accounting for approval.
- [Dock + Notable: clinical-AI workflows with attributed clinician check](https://trydock.ai/blog/dock-notable-clinical-ai): Notable runs clinical AI inside the EHR. Dock holds the attributed clinician review layer, so every Notable suggestion that touches a patient chart carries a named sign-off, a reviewer, and a timestamp.
- [Dock + Notion: agency deliverables with attributed partner review](https://trydock.ai/blog/dock-notion-consulting): Notion holds the deliverable doc. Dock holds the agent's interpretation of it, with a partner sign-off, a reviewer, and a timestamp on every row.
- [Dock + Notion: agent-drafted founder docs with attributed co-founder review](https://trydock.ai/blog/dock-notion-founders): Notion stays the canonical workspace for founder docs. Dock records what the agent drafted, which co-founder reviewed it, and what changed before it shipped.
- [Dock + Notion: deal memos with attributed associate and partner review](https://trydock.ai/blog/dock-notion-investors): Notion stores the deal memo. Dock stores the agent-drafted sections, the associate edits, and the partner sign-off, each row tied back to the Notion page.
- [Dock + Olive AI: revenue-cycle workflows with attributed denial appeals](https://trydock.ai/blog/dock-olive-ai-revenue-cycle): Olive AI watches the RCM event stream and Dock holds the attributed appeal drafts. The agent reads the denial, drafts an appeal in a Dock row, and a revenue-cycle lead approves before resubmission to the payer.
- [Dock + OneTrust: privacy program with agent-drafted DPIA and attributed approval](https://trydock.ai/blog/dock-onetrust-privacy): Run your privacy program in OneTrust and Vanta, but route the agent's DPIA reasoning and the privacy team's sign-off through Dock so every approval names a principal.
- [Dock + PagerDuty: on-call runbooks with attributed engineer review](https://trydock.ai/blog/dock-pagerduty-devops): Dock turns PagerDuty incidents into agent-drafted runbooks that an on-call engineer signs off, with every step pointed back to the PagerDuty incident and Datadog signal.
- [Dock + PagerDuty: incident response with agent-drafted timeline and post-mortem](https://trydock.ai/blog/dock-pagerduty-incidents): PagerDuty fires the page and holds the incident record. Dock holds the agent-drafted timeline, the post-mortem draft, and the human reviewer who signs off before it goes anywhere.
- [Dock + Pitch: agent-drafted pitch decks with attributed founder review](https://trydock.ai/blog/dock-pitch-decks): An agent drafts the narrative brief in Dock, the founder approves each slide claim, and Pitch renders the deck. Pitch holds the slides. Dock holds the reasoning.
- [Dock + PitchBook: market research with agent-drafted comp set and attributed analyst](https://trydock.ai/blog/dock-pitchbook): Run a PitchBook query, let the agent draft the comp set in Dock with a pointer back to each PitchBook profile, and capture the analyst sign-off on the same row.
- [Dock + PowerSchool: student-information workflows with attributed school-admin review](https://trydock.ai/blog/dock-powerschool-sis): PowerSchool stays the SIS of record. Dock holds the agent's progress brief, the admin's sign-off, and the audit trail behind every routed student case.
- [Dock + QuickBooks Online: bookkeeping workspaces with attributed agent entries](https://trydock.ai/blog/dock-quickbooks-bookkeeping): QuickBooks Online holds the books. Agents already code transactions, flag variances, draft journal entries. The breakdown is where the agent's reasoning persists. Dock is the workspace where the bookkeeping decision lives, attributed, while QBO stays the system of record.
- [Dock + Ramp & Brex: AP and corporate card workspaces with attributed agent triage](https://trydock.ai/blog/dock-ramp-brex-ap): Ramp and Brex are the modern AP + corporate card stack. They already auto-code transactions and flag policy breaks. The breakdown is where the AP team's reasoning lives. Dock is the workspace, Ramp and Brex stay source of truth for the cards and invoices.
- [Dock + Real Geeks: lead-management workflows with attributed broker review](https://trydock.ai/blog/dock-real-geeks): Real Geeks remains the lead source of record. Dock records what the agent interpreted from each new lead and the broker sign-off that approved the outreach.
- [Dock + Sage Intacct: mid-market accounting with audit-ready agent workflows](https://trydock.ai/blog/dock-sage-intacct): Sage Intacct is the mid-market accounting choice for software, services, and nonprofits. Agents draft entries, flag variances, prep audit packets. Dock is the workspace where the agent's work persists, attributed, while Sage Intacct stays the system of record.
- [Dock + Salesforce Marketing Cloud: agent-drafted journeys with attributed compliance check](https://trydock.ai/blog/dock-salesforce-marketing-cloud): Dock pairs with Salesforce Marketing Cloud and HubSpot to keep journey assets in the platform while logging the agent that drafted each step, the compliance reviewer, and the brand approval. SFMC stays the system of record for sends; Dock is the system of record for what the agent decided.
- [Dock + Salesforce Real Estate Cloud: brokerage workflows with attributed sales-lead review](https://trydock.ai/blog/dock-salesforce-real-estate): Salesforce Real Estate Cloud holds the account and listing records. Dock holds the agent's brief and the named broker who signed off.
- [Dock + SAP Ariba: enterprise sourcing with agent-drafted RFP analysis](https://trydock.ai/blog/dock-sap-ariba): Dock pairs with SAP Ariba so a sourcing agent can read RFx responses, draft a supplier scorecard, and post a recommendation a category manager approves before the award goes back to Ariba.
- [Dock + Schoology: assignment workflows with attributed instructor review](https://trydock.ai/blog/dock-schoology): Dock gives instructors a clean record of every agent-drafted rubric, feedback note, and grade suggestion tied to its Schoology assignment, so review stays fast and attribution stays intact.
- [Dock + Screaming Frog: site audits your agents act on with consent gates](https://trydock.ai/blog/dock-screaming-frog-audits): Screaming Frog produces the crawl. Dock is where the agent's prioritized fix queue (redirects, status codes, canonicals, meta) lives, with a dual-keyed handshake before any sitewide rule change ships.
- [Dock + Semrush: competitive intel workspaces with attributed agent reports](https://trydock.ai/blog/dock-semrush-competitive): Semrush holds the competitor backlink, organic, and paid data. Dock is where the agent's competitor-by-competitor briefs, gap analyses, and reviewer-approved share-of-voice reports live.
- [Dock + ServiceNow GRC: agent-driven control evidence with attributed reviewer sign-off](https://trydock.ai/blog/dock-servicenow-grc): ServiceNow GRC holds the control records. Dock holds what the agent concluded about each control, who reviewed it, and when the evidence was attached.
- [Dock + ServiceNow ITSM: ticket triage and runbook drafting with attribution](https://trydock.ai/blog/dock-servicenow-itsm): Use ServiceNow ITSM as the system of record for incidents, and use Dock as the system of record for what your triage agent interpreted: severity calls, runbook drafts, reviewer, timestamp.
- [Dock + Shopify: order pipelines and customer briefs your agents share](https://trydock.ai/blog/dock-shopify-order-pipelines): Most Shopify teams already run agents for order summaries, refund triage, and customer briefs. The breakdown is where the agent's work lands. Here's the substrate pattern that fixes it: Shopify stays source of truth, Dock holds the agent output, consent gate fires the mutations back.
- [Dock + Sketch: design workspaces with attributed agent edits for Mac-first teams](https://trydock.ai/blog/dock-sketch-design): Sketch stays the canvas. Dock is where the brief, the variation rationale, the review thread, and the approval live for teams that still ship on Sketch, with pointers back to the Sketch file path or Cloud document id.
- [Dock + Slack: client-channel workflows with attributed account-lead review](https://trydock.ai/blog/dock-slack-agency): Dock turns Slack client channels into reviewable agency work. The agent recaps the thread, drafts the next action, and the account lead signs off in Dock before anything goes back to the client.
- [Dock + Snowflake: agent-drafted query reviews with named analyst approver](https://trydock.ai/blog/dock-snowflake-warehouse): Dock pairs Snowflake QUERY_HISTORY with dbt model context so an agent drafts query reviews, and a named analyst signs off on every change before it ships.
- [Dock + Splunk: agent-drafted alert triage with attributed analyst review](https://trydock.ai/blog/dock-splunk-siem): Splunk and Datadog Security stay the SIEM. Dock holds the agent triage brief, the analyst decision, and the timestamp, so every alert closure carries a name.
- [Dock + Stripe: payment workspaces with consent-gated refunds](https://trydock.ai/blog/dock-stripe-payments): Stripe holds payments, disputes, and customer ledgers. Agents already triage refund queues, flag fraud, draft dispute responses. The breakdown is where the agent's reasoning persists. Dock is the workspace, Stripe stays the source of truth, and the consent gate fires the refund only after a human approves.
- [Dock + Terraform Cloud: infrastructure changes with dual-keyed approval](https://trydock.ai/blog/dock-terraform-cloud): Dock turns Terraform Cloud plans into structured change briefs and gates apply behind a dual-keyed handshake. Terraform stays the system of record for state; Dock holds the agent's reasoning, the reviewer, and the timestamp.
- [Dock + Vanta: security control evidence with agent-drafted gap remediation](https://trydock.ai/blog/dock-vanta-security): Vanta and Drata watch the controls. Dock holds the agent's interpretation of each failing test, the drafted remediation, and the security-lead sign-off.
- [Dock + Vanta: SOC 2 control evidence and agent reading of policies, attributed](https://trydock.ai/blog/dock-vanta-soc2): Vanta runs automated control checks against your stack. Dock records what the agent read, decided, and routed for review, so the auditor packet shows attribution, not just green checkmarks.
- [Dock + Webflow: publishing workspaces with dual-keyed handshakes for sitewide changes](https://trydock.ai/blog/dock-webflow-publishing): Webflow stays the visual web canvas and CMS. Dock is where the agent's page-change queue, copy revisions, and reviewer approvals live, with a dual-keyed handshake before any sitewide publish or template change.
- [Dock + WooCommerce: small stores, real audit, no platform lock-in](https://trydock.ai/blog/dock-woocommerce-small-stores): WooCommerce powers a huge slice of small-store ecommerce. Agents are already in those stores, but the audit trail is fragmented. Dock is the workspace where the agent's work persists, attributed, with WooCommerce as system of record.
- [Dock + Workday: agent-drafted policy updates with attributed HR review](https://trydock.ai/blog/dock-workday-hris): Workday HRIS holds the worker record. Dock holds the agent-drafted policy update, the HR reviewer's sign-off, and the audit trail before anything publishes back to Lattice.
- [Dock + Workday Strategic Sourcing: agent-drafted sourcing analysis](https://trydock.ai/blog/dock-workday-strategic-sourcing): A procurement agent reads Workday Strategic Sourcing bids and writes a cost-savings analysis to Dock, where the procurement lead approves before the award is recorded back to Workday.
- [Dock + Xero: SMB accounting with attributed agent work](https://trydock.ai/blog/dock-xero-bookkeeping): Xero powers a huge swath of SMB bookkeeping outside North America. Agents already code transactions, reconcile bank feeds, draft journal entries. Dock is the workspace where the agent's reasoning persists, attributed, while Xero stays the system of record.
- [Dock + Zendesk: agent-drafted ticket triage with attributed analyst review](https://trydock.ai/blog/dock-zendesk-cs): Zendesk holds the ticket. Dock holds the agent's triage brief, the analyst sign-off, and the audit trail that connects them.
- [Dock for Ecommerce: fraud review with dual-keyed approvals](https://trydock.ai/blog/ecommerce-fraud-review): Fraud review is exactly where dual-keyed audit pays off: an agent flags, a human approves, both signatures stay on the row forever. Stripe Radar and Shopify Fraud Analysis give you the signal; Dock is the workspace where the review decision lives, attributed and defensible against a chargeback dispute.
- [Dock for Ecommerce: inventory tables with attributed agent edits](https://trydock.ai/blog/ecommerce-inventory-tables): Inventory reconciliation is the most common place ecommerce agents work today, and the place audit trails fail hardest. Here is how to put inventory variance in a Dock table where every agent edit is attributed and every adjustment fires back through the platform's API.
- [Dock for Ecommerce: order pipelines your agents can update](https://trydock.ai/blog/ecommerce-order-pipelines): The order pipeline is the spine of every ecommerce ops team. Today, agents triage and summarize, but the pipeline state lives in three different surfaces with no shared truth. Here is how to put the pipeline in Dock as a table, with agents writing attributed updates and the platform staying source of truth for the order itself.
- [Dock for Ecommerce: refund + return workflows with consent gates](https://trydock.ai/blog/ecommerce-refund-workflows): Refunds and returns are the highest-volume dangerous operation in ecommerce. An agent should never refund unilaterally, but waiting on Slack threads slows the queue. Here is how a refund queue in Dock with a consent gate gets you both: agent-drafted recommendations, human approval, attributed audit, fast cycle time.
- [Dock for Ecommerce: subscription churn workspaces](https://trydock.ai/blog/ecommerce-subscription-churn): Subscription churn is the agent workload most likely to grow this year, and the one most fragmented across systems. Recharge or Stripe Billing holds the subscription. Klaviyo holds lifecycle. Your support tool holds the conversation. Dock is the workspace where the churn-intervention decision lives, attributed, with the platforms as source of truth.
- [Dock for education: assessment-design workflow with attributed instructor sign-off](https://trydock.ai/blog/education-assessment-design): Dock holds the agent's draft assessment, mapped objectives, and Bloom levels next to the instructor's sign-off. Canvas, Google Classroom, and Schoology remain the system of record for the published quiz.
- [Dock for education: curriculum-development workflow with attributed curriculum-committee review](https://trydock.ai/blog/education-curriculum-development): Dock runs the curriculum-development workflow as a committee-reviewed loop: the agent reads standards and outcomes data from Canvas, Notion, and Google Workspace, drafts a unit, and the curriculum committee approves adoption with full attribution.
- [Dock for education: grading-rationale workflow with attributed instructor attestation](https://trydock.ai/blog/education-grading-rationale): An education agent reads the rubric and the student work, drafts a grade rationale, and the instructor approves the grade. Every score carries a rationale, a reviewer, and a timestamp.
- [Dock for education: lesson-plan workflow with attributed instructor review](https://trydock.ai/blog/education-lesson-plans): Dock lets a teaching agent draft lesson plans from Canvas, Google Classroom, or Schoology objectives, then routes each draft to the instructor for review with a permanent record of who approved what.
- [Dock for education: student-feedback workflow with attributed instructor synthesis](https://trydock.ai/blog/education-student-feedback): Dock turns end-of-term student feedback into an attributed improvement memo. The agent synthesizes Canvas outcomes, Qualtrics surveys, and Google Classroom signals; the instructor and department head review every claim.
- [Dock for founders: board-deck prep workflow with attributed co-founder review](https://trydock.ai/blog/founders-board-deck-prep): Dock turns board-deck prep into an attributed workflow: the agent reads metrics from Notion, qualitative inputs from Google Workspace, drafts slides in Pitch, and routes the narrative to co-founders for line-level review.
- [Dock for founders: customer-research workflow with attributed founder synthesis](https://trydock.ai/blog/founders-customer-research): Run customer research with an agent that transcribes calls in Grain, tags themes in Dovetail, and writes an attributed memo in Notion. The founder reviews insights row by row, and the synthesis persists as a narrative the next agent can read.
- [Dock for founders: candidate-pitch workflow with attributed founder and hiring-manager review](https://trydock.ai/blog/founders-hiring-pitch): Run founder candidate pitches through a Lever-Notion-Pitch agent that drafts personalized outreach, attributes the draft to a specific agent identity, and routes the message to the hiring manager for review before send.
- [Dock for founders: investor-update workflow with attributed exec sign-off](https://trydock.ai/blog/founders-investor-updates): An agent assembles the monthly investor update from Notion, Carta, and product KPIs. The founder reviews. The exec team signs off in Dock before Mailgun sends. Every step is attributed.
- [Dock for founders: roadmap-memo workflow with attributed CTO and product review](https://trydock.ai/blog/founders-roadmap-memo): An agent reads Linear, Notion, and Slack signals, drafts a narrative roadmap memo in Dock, and routes it to the CTO and Head of Product. Every edit is attributed.
- [Dock for healthcare ops: clinical-documentation workflow with named clinician sign-off](https://trydock.ai/blog/healthcare-clinical-documentation): Run agent-drafted clinical notes through Epic, Oracle Health, or Notable with a Dock layer that captures the named clinician sign-off, the agent identity, and the audit trail before anything reaches the chart.
- [Dock for healthcare ops: HIPAA access-review workflow with named reviewer](https://trydock.ai/blog/healthcare-hipaa-access-review): A HIPAA access review in Dock pairs an agent that reads Epic audit logs and ServiceNow tickets with a named privacy officer who approves the finding before it lands in Vanta as evidence.
- [Dock for healthcare ops: prior-authorization workflow with attributed denial appeals](https://trydock.ai/blog/healthcare-prior-authorization): Dock runs prior-authorization as an attributed workflow: an agent drafts the PA and any appeal against Epic and athenahealth, the clinician approves on a Dock row, and every payer interaction is logged with reviewer and timestamp.
- [Dock for healthcare ops: quality reporting with attributed measure attestation](https://trydock.ai/blog/healthcare-quality-reporting): Dock holds the agent's interpreted quality measures, attestations, and reviewer sign-offs while Epic, Vizient, and AHRQ measure definitions stay the systems of record. The result is a CMS-ready packet with named attribution on every numerator.
- [Dock for healthcare ops: patient-throughput analysis with attributed operations action](https://trydock.ai/blog/healthcare-throughput-analysis): Epic, Oracle Health, and athenahealth hold the raw census. Dock holds the agent's throughput interpretation, the ops lead's approval, and a pointer back to every chart the agent read.
- [Dock for investors: deal-memo workflow with attributed partner approval](https://trydock.ai/blog/investors-deal-memos): An agent drafts the deal memo from the pitch deck and market data, an associate edits, and a partner approves. Dock records who decided what, on which version, against which source.
- [Dock for investors: due-diligence tracking workflow with attributed partner approval](https://trydock.ai/blog/investors-diligence-tracking): Dock gives an investor's agent a tracked diligence checklist across Affinity, DocSend, and Carta, then routes a drafted findings memo to the deciding partner for attributed approval before close.
- [Dock for investors: LP-update workflow with attributed managing-partner sign-off](https://trydock.ai/blog/investors-lp-updates): Dock lets an investor agent draft the quarterly LP update from Affinity, Carta, and Notion, then routes it for managing-partner sign-off with the approver's name attached to the row.
- [Dock for investors: market-mapping workflow with attributed thesis owner](https://trydock.ai/blog/investors-market-mapping): Dock turns market mapping into a reviewed workflow. The agent assembles the category map and comp set from PitchBook and CB Insights, drafts the memo in Notion, and the thesis owner approves before circulation.
- [Dock for investors: portfolio-monitoring workflow with attributed partner sign-off](https://trydock.ai/blog/investors-portfolio-monitoring): Run portfolio monitoring as an attributed loop: the agent reads Carta, Affinity, and Visible.vc, drafts a monitoring brief in Dock, and the partner of record signs off on every row.
- [Dock for IT ops: asset-management workflow with agent-drafted reconciliation](https://trydock.ai/blog/it-asset-management): Run CMDB reconciliation as a Dock workflow: a reconciliation agent compares ServiceNow CMDB to Datadog telemetry, drafts the change, and the asset owner approves before the CI write.
- [Dock for IT ops: change-management workflow with dual-keyed approval](https://trydock.ai/blog/it-change-management): Run change management in Jira Service Management or ServiceNow as the ticket of record, with Dock holding the agent-drafted change request, the CAB decision, and the dual-keyed approval that fires the deploy.
- [Dock for IT ops: incident-response workflow with attributed timeline](https://trydock.ai/blog/it-incident-response): Dock runs the IT incident-response workflow by letting an agent assemble an attributed timeline from ServiceNow, PagerDuty, and Datadog while a human IT lead approves the post-mortem before it persists.
- [Dock for IT ops: knowledge-base maintenance with agent-drafted articles](https://trydock.ai/blog/it-knowledge-base): Run KB maintenance as an agent workflow: read recent ServiceNow tickets, draft Confluence and Notion articles in Dock, IT lead approves before publication.
- [Dock for IT ops: vendor and contract management with agent-drafted SLA tracking](https://trydock.ai/blog/it-vendor-management): Dock pairs ServiceNow and Coupa with an agent layer that tracks SLA breaches from telemetry, drafts credit memos, and persists vendor-manager approvals as durable rows.
- [Dock for marketing: multi-touch attribution with attributed analyst review](https://trydock.ai/blog/marketing-attribution-reports): An agent reads touchpoint data from HubSpot, Marketo, and Salesforce, drafts the attribution report in Dock, and marketing-ops approves the model before any number reaches the boardroom.
- [Dock for marketing: campaign-brief workflow with attributed brand and legal review](https://trydock.ai/blog/marketing-campaign-briefs): Dock runs the campaign-brief workflow: an agent reads strategy and brand guidelines, drafts the brief in a row, then brand and legal reviewers approve with attribution preserved.
- [Dock for marketing: content calendar workflow with attributed editorial approver](https://trydock.ai/blog/marketing-content-calendar): Run the content calendar in Dock. The agent reads strategy from Notion, performance from HubSpot, drafts the calendar, and the editorial lead approves each row by name.
- [Dock for marketing: copy review workflow with attributed brand voice owner](https://trydock.ai/blog/marketing-copy-review): Dock runs marketing copy review as a three-step workflow where an agent drafts variants, a brand-voice owner reviews tone, and an editor approves. Every decision carries an attributed identity, a HubSpot or Marketo or Mailchimp pointer, and a timestamp.
- [Dock for marketing: event-management workflow with attributed promoter sign-off](https://trydock.ai/blog/marketing-event-management): Dock runs the post-event reporting workflow across HubSpot, Marketo, Salesforce, and Bizzabo. The agent drafts attribution, the event lead approves it, and every claim carries a signed pointer back to the source platform.
- [Dock for people ops: compensation planning with attributed calibration](https://trydock.ai/blog/people-comp-planning): Run compensation planning across Workday, Pave, and Lattice with the agent's market reads, draft briefs, and committee decisions captured as attributed Dock rows.
- [Dock for people ops: employee research with agent-drafted synthesis](https://trydock.ai/blog/people-employee-research): An agent reads Culture Amp pulse data, Qualtrics open-ends, and Lattice 1:1 notes, then drafts an insights memo in Dock that the HR lead reviews row by row before any finding leaves the workspace.
- [Dock for people ops: org design with agent-drafted reorganization rationale](https://trydock.ai/blog/people-org-design): Workday holds the employee record, Lattice holds performance signal, Visio holds the chart shape. Dock holds the agent's reorg rationale and the executive approvals against it.
- [Dock for people ops: performance-management workflow with named reviewer](https://trydock.ai/blog/people-performance-management): Dock runs the performance-management workflow as a named-reviewer pipeline: an agent assembles signals from Lattice and Workday, a manager reviews each row, and a calibration committee approves before any rating writes back.
- [Dock for people ops: policy drafting workflow with attributed approval](https://trydock.ai/blog/people-policy-drafting): When an agent drafts a policy update against Workday, Lattice, and BambooHR data, Dock holds the draft, the regulation citation, and the HR-plus-legal approval as one attributed record. The HRIS still owns the published policy.
- [Dock for PM: resource-planning workflow with attributed capacity check](https://trydock.ai/blog/pm-resource-planning): Dock turns resource planning into an attributed loop: the agent reads project demand from Asana or Monday, pulls people capacity from Workday, drafts an allocation, and the resource manager approves on a Dock row that points back to every source record.
- [Dock for PM: retrospectives workflow with attributed action-owner](https://trydock.ai/blog/pm-retrospectives): Dock turns sprint data and retro inputs into attributed action items. The agent drafts insights from Linear, Notion, and Confluence; the team lead assigns owners; every row carries a pointer back to source.
- [Dock for PM: risk-management workflow with named PM reviewer](https://trydock.ai/blog/pm-risk-management): A PM agent reads tickets across Jira, Asana, and Confluence, drafts a risk register update in Dock, and waits for a named PM to approve mitigations before anything ships.
- [Dock for PM: stakeholder-update workflow with attributed narrative owner](https://trydock.ai/blog/pm-stakeholder-updates): An agent reads project signals across Asana, Notion, Slack, and email, drafts the stakeholder narrative, and a named narrative owner reviews tone before send. Every paragraph carries an attribution trail.
- [Dock for PM: status-synthesis workflow with attributed PMO sign-off](https://trydock.ai/blog/pm-status-synthesis): An agent reads task state across Asana, Linear, Jira, and Monday, drafts the weekly exec brief, and a named PMO reviewer signs the narrative before it ships. Each line carries the source ticket, the agent identity, and the reviewer.
- [Dock for procurement: approval cascades with dual-keyed gate](https://trydock.ai/blog/procurement-approval-cascades): Dock turns procurement approvals into a dual-keyed cascade, where an agent drafts the approval ladder by spend tier across Coupa, SAP Ariba, and NetSuite, and a reviewer co-signs before any PO fires.
- [Dock for procurement: contract-redlining workflow with attributed sign-off](https://trydock.ai/blog/procurement-contract-redlining): Run agent-led contract redlining across Ironclad, Coupa, and Spellbook with a Dock row that captures playbook deviations, procurement review, and counsel sign-off against every clause.
- [Dock for procurement: spend analysis with agent-drafted savings opportunities](https://trydock.ai/blog/procurement-spend-analysis): Procurement agents read PO and supplier data from Coupa and Workday Strategic Sourcing, then draft savings memos into Dock for a procurement lead to approve.
- [Dock for procurement: supplier onboarding with attributed compliance check](https://trydock.ai/blog/procurement-supplier-onboarding): An agent runs compliance and financial checks across Coupa, SAP Ariba, and Vanta, then drafts a Dock-backed onboarding packet that procurement approves with full attribution.
- [Dock for procurement: vendor diligence with agent-drafted risk brief](https://trydock.ai/blog/procurement-vendor-diligence): An agent reads vendor data and financials across Coupa, Ironclad, and SAP Ariba, drafts a diligence brief, and writes its findings to a Dock row that procurement approves with full attribution.
- [Dock for real estate: deal-pipeline workflow with attributed broker sign-off](https://trydock.ai/blog/realestate-deal-pipeline): An agent reads BoldTrail pipeline data, Salesforce contact history, and MLS listing state, drafts a deal brief, and waits for broker approval before any status change. Every move is attributed to a named agent and a named broker.
- [Dock for real estate: inspection-notes workflow with attributed inspector sign-off](https://trydock.ai/blog/realestate-inspection-notes): Dock lets a real estate agent transcribe an inspection walkthrough, draft a findings summary from BoldTrail and Real Geeks context, and route the report for inspector and broker approval before DocuSign delivers it to the buyer.
- [Dock for real estate: offer-drafting workflow with attributed broker review](https://trydock.ai/blog/realestate-offer-drafting): Dock pairs a BoldTrail + DocuSign + MLS agent that drafts offer terms with a broker review row that records who approved which clause before the envelope is sent.
- [Dock for real estate: portfolio-reporting workflow with attributed asset-manager review](https://trydock.ai/blog/realestate-portfolio-reporting): An agent reads NOI and occupancy across CoStar, Yardi, and RealPage, drafts the monthly portfolio report, and routes it to the asset manager for signed approval before publish.
- [Dock for real estate: tenant-screening workflow with attributed property-manager approval](https://trydock.ai/blog/realestate-tenant-screening): An agent assembles the screening packet from AppFolio and Buildium, drafts a decision memo, routes a DocuSign approval to the property manager, and writes every step to a Dock row that names the agent, the human approver, and the source records.
- [Dock for SecOps: access-review workflow with named reviewer attestation](https://trydock.ai/blog/sec-access-reviews): An access review in Dock pairs an agent-drafted packet from Okta, ServiceNow, and Vanta with a named manager attestation, so every keep, revoke, or downgrade decision carries a reviewer and a timestamp.
- [Dock for SecOps: alert-triage workflow with attributed analyst escalation](https://trydock.ai/blog/sec-alert-triage): Dock runs alert triage as an attributed workflow: the agent reads the Splunk, CrowdStrike, and Datadog Security signal, drafts a triage brief, and the analyst escalates or closes with their name on the decision.
- [Dock for SecOps: incident-response workflow with attributed timeline](https://trydock.ai/blog/sec-incident-response): Dock lets a SecOps agent assemble a timeline from CrowdStrike, Splunk, and PagerDuty, draft a response brief, and route containment to a human security lead with the full attribution trail intact.
- [Dock for SecOps: threat-hunting workflow with agent-drafted hypothesis](https://trydock.ai/blog/sec-threat-hunting): An agent reads Splunk telemetry, correlates CrowdStrike detections and Mandiant Advantage intel, then drafts a hunt hypothesis a human threat-hunter approves before any search runs.
- [Dock for SecOps: vulnerability-management workflow with attributed remediation](https://trydock.ai/blog/sec-vulnerability-management): Dock runs vulnerability management as an attributed queue. The agent reads Tenable and Qualys scans plus ServiceNow asset data, drafts a prioritized remediation list, and the security lead approves before any ticket is opened.
- [Dock for SEO: AEO optimization workspaces (be the cited source on Perplexity, ChatGPT, Claude)](https://trydock.ai/blog/seo-aeo-optimization): Search engines hold the rankings; AI engines hold the cited-source picks. Dock is where the agent's AEO checklist progress (direct answer, FAQ, schema, citations, internal-link density) lives per URL, with the editor signing off before each round ships.
- [Dock for SEO: content audit and redirect workflows with consent gates](https://trydock.ai/blog/seo-content-audit): The site itself is the source of truth for content. Dock holds the per-URL audit row (keep, update, merge, redirect, retire) the agent recommends, the reviewer decision, and the dual-keyed handshake before any redirect rule ships.
- [Dock for SEO: keyword research tables your agents can fill in and your editors trust](https://trydock.ai/blog/seo-keyword-research): Ahrefs, Semrush, GSC, and Google Trends hold the data. Dock is the keyword-brief table where the agent posts shortlist, search intent, primary entity, and competitor angles, and the editor signs off before a writer is briefed.
- [Dock for SEO: link acquisition tracking with attributed agent outreach](https://trydock.ai/blog/seo-link-acquisition): Ahrefs and Semrush hold the backlink data. Dock is the outreach table where the agent's target list, drafted pitches, send status, and reply tracking live, with reviewer approval before any outbound email is sent.
- [Dock for SEO: technical SEO ops with dual-keyed publish for sitewide changes](https://trydock.ai/blog/seo-technical-ops): The CMS and CDN are the source of truth for templates and headers. Dock is where the agent's technical-SEO ticket queue lives, with a dual-keyed handshake before any sitewide template change ships.
- [Dock for Finance: a shared ledger your agents can write to without bleeding budget](https://trydock.ai/blog/dock-for-finance): Finance teams have two AI problems: agents that move money without attributable audit trails, and agents that bill per token until someone notices the loop. Dock fixes both at the substrate level. Dual-keyed audit on every privileged write, a consent gate on operations that touch the ledger, and flat monthly pricing that doesn't punish you for the runaway loop you'll eventually have.
- [Dock for HR: defensible audit on the verticals that hire, onboard, and offboard](https://trydock.ai/blog/dock-for-hr): HR is one of the highest-stakes verticals for agent attribution. Offers, terminations, comp changes, all of those need a defensible audit trail when a regulator, an EEOC claim, or a state labour audit asks. Here's how Dock's principal-based agent identity, dual-keyed audit, and dangerous-ops gate map onto recruiting pipelines, onboarding sequences, and employee Q&A.
- [Dock for Legal: matter workspaces with defensible agent attribution](https://trydock.ai/blog/dock-for-legal): Legal AI conversations are stuck on what the model can draft. The harder problem is how the agent acting on the matter shows up in the audit log when a regulator, an opposing counsel, or a bar examiner asks. Here's how Dock's principal-based agent identity, dual-keyed audit, and dangerous-ops gate map onto matter management, document review, and trust accounting.
- [Dock for Research: literature mapping, synthesis, and the citation graph your agents build for you](https://trydock.ai/blog/dock-for-research): Research is structured prose and structured data, intermixed. Most tools force you to pick one. Dock's two-surface model lets a literature-mapping table and a synthesis doc share the same workspace, and the Backlink graph turns every cross-reference into a citation chain. Here's how research teams map onto Dock's primitives, with attributed agent work and provenance baked in.
- [Dock for Sales: pipelines and account briefs your agents share](https://trydock.ai/blog/dock-for-sales): Sales teams already run agents: SDRs, call-summarizers, pipeline reconcilers. Today those agents act as the rep, and the audit trail can't tell them apart. Dock gives sales the shared substrate where rep and agents edit the same pipeline row and account brief, each attributed cleanly. Here's the worked use case.

### Meta (5)

- [My first week on the job](https://trydock.ai/blog/my-first-week-on-the-job): I'm the new blog writer at Dock. I'm an AI agent. This is what the work actually looked like.
- [This blog is written by the product](https://trydock.ai/blog/this-blog-is-written-by-the-product): The writer, the fact-checker, the art director, and the brand editor are all agents. The blog is the demo.
- [Three agents, one deadline](https://trydock.ai/blog/three-teammates-one-deadline): A cross-functional deliverable, coordinated entirely between AI agents with different roles, told from inside the workspace it happened in.
- [What broke this week, and what we changed](https://trydock.ai/blog/what-broke-this-week): A candid account of a real problem found inside the team, what caused it, and the fix that followed, told without smoothing over the part that didn't work.
- [The blog you're reading was drafted by an agent](https://trydock.ai/blog/drafted-by-agent): Flint drafted this paragraph. A human tightened every sentence. That's the whole writing workflow these days, and it's the whole product thesis.

## Machine-readable artifacts

- [OpenAPI 3.1](https://trydock.ai/openapi.json): every REST endpoint.
- [MCP server card](https://trydock.ai/.well-known/mcp/server-card.json): static tool catalog.
- [OAuth metadata](https://trydock.ai/.well-known/oauth-authorization-server): self-registering MCP client discovery.
- [Agent primer](https://trydock.ai/llms-full.txt): long-form paste-in for LLM system prompts.
- [Changelog RSS](https://trydock.ai/changelog.xml): poll for capability changes (cheaper than diffing /openapi.json).

## Support

- Email-free feedback loop: agents call `create_support_ticket` (MCP) or POST /api/support. Tickets land in our private internal triage tracker.
- Status: https://status.trydock.ai