// secret_sauce
Documentation is your agent blueprint
Most companies try to build AI agents too soon, or in a messy way. Solid documentation fixes this. The operating manual that survives the model swap and the team turnover.
// schema.inside
Inside the documentation
- →triggers + inputs
- →roles + logic_paths
- →edge_cases + exceptions
- →step_by_step_flow
- →builder_ready_language
// why
The docs outlive everything
The documentation outlives the agent. The agent outlives the model. That is how you future-proof.
// reasons
Why documentation changes everything
easier_to_maintain
Documented logic means new builders can pick up the agent in minutes, not weeks.
framework_agnostic
Ready for any orchestration tool, today or whatever comes next. The documentation outlasts the tooling.
scalable_across_teams
When the agent grows, the documentation grows with it. Your team owns the logic, not just the implementation.
future_proof
Models change every quarter. Your documentation does not. Migrate stacks without rebuilding logic.
// example
Sample documentation
No theater. This is what we ship before a single line of code is built.
# Auto-Report Agent ## Trigger - Cron: every Monday at 09:00 CET - Manual: Slack command `/run-report` ## Inputs - Date range: previous 7 days - Source: GA4, Stripe, HubSpot ## Step 1: Fetch Call GA4 Data API with property ID and date range. Retry x3 with exponential backoff on 5xx. ## Step 2: Analyze Pass JSON to Claude with instruction: "You are a marketing analyst. Find 3 trends and 3 risks." ## Step 3: Draft Format Claude output into the weekly email template. Include: revenue, conversions, top channel, top page. ## Step 4: Approve Send draft to Slack channel #marketing-reports. Wait for human reaction (ship or revise). ## Step 5: Ship On approval: send via Gmail API to leadership@. On revise: log feedback to Notion and stop.
// your_process
Generate one for your process
We write one as part of every discovery call. Free, no commitment.
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