Build with a coding agent

Use your coding agent to develop a Cayu application. The coding agent edits software; the resulting Cayu agent performs the domain job at runtime. Keep those roles explicit in the implementation brief.

Give the builder a concrete brief

Create a Cayu application using cayu new.
Job: summarize a support request and identify missing order information.
Input: user text supplied to run.py.
Output: a summary plus the specific information still needed.
Start with one model-only agent. Read the generated AGENTS.md first.
Use the declared build_app factory and configuration seams.
Update the existing test and eval to represent the job.
Run inspect, strict check, tests and eval; report actual results.
Configure the live provider once I supply the selected provider and credentials.

Replace the job, inputs and acceptance criteria with your domain. Add authority requirements when the job includes spending, external mutations or human decisions. The builder needs enough context to distinguish a useful result from plausible prose.

Discovery and the authoring loop

Ask the builder to read these version-matched sources inside the project:

uv run --no-sync cayu guide anatomy
uv run --no-sync cayu guide authoring#cayu-map
uv run --no-sync cayu inspect --json
uv run --no-sync cayu check --fail-on warning --json

The capability map routes optional behavior to the smallest relevant contract. The small machine-readable API index leads to namespace and alphabetic symbol indexes. Follow a symbol’s Markdown URL for its signature, fields and source. Package-shipped guides remain the local reference when the installed version differs from this site.

Review evidence

Check the factory declaration, registrations and tests rather than accepting a completion message. A useful handoff records the changed behavior, test results, eval results and observed live-run outcome. Verify that deterministic fixtures test real runtime seams, and that a live-model claim actually came from a model run.

For a protected external action, require a test that proves denial or a durable pause before authorization, then independent evidence of the effect after authorization. Tests that assert only the tool’s own success text cannot establish downstream state.

Keep the project small

Add tools, environments, workers, workflows, memory and approvals as the job needs them. A model-only application is a valid starting point. Read authoring for exact placement and testing for proof through public seams.