Capstone: Ship a Reusable Agent Workbench Pack
The mini-track ends with a pack you drop into any repo. Eleven lessons of surfaces compressed into a directory you can cp -r and have an agent working reliably the next morning. The capstone is the artifact this curriculum trades on. Package the seven workbench surfaces into one drop-in directory. Pin the schemas, scripts, and templates so a new repo gets a known-good baseline. Add a single installer script that lays down the pack idempotently. Decide what stays in the pack and what stays out, defending the cut for each. A workbench that lives in a Google Doc, a chat history, and three half-remembered scripts is a workbench that gets rebuilt every quarter. The cure is a versioned pack: a repo or directory with the surfaces, the schemas, the scripts, and a one-command installer. You will end this lesson with outputs/agent-workbench-pack/ shipped on disk and a bin/install.sh that drops it into any target repo. In: Surface schemas. They are the contract. The four scripts above. They are the runtime. The four docs. They are the rules and the rubric. Out: Project-specific tasks. Tasks belong on the target repo's board, not in the pack. Vendor SDK calls. The pack is framework-agnostic. Onboarding prose. The pack lives next to the team's existing onboarding, not inside it. A short bin/install.sh (or bin/install.py): Refuses…
Capstone: Ship a Reusable Agent Workbench Pack: The mini-track ends with a pack you drop into any repo. Eleven lessons of surfaces compressed into a directory…
This free lesson is part of the AI Engineering from Scratch curriculum. Read the full explanation, run the lesson code, and verify the result in the interactive reader or from the repository source.
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