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Claude Code course path from a convincing demo to a governed run and production evidence

My Claude Code production agents course is live

My new practical Leanpub course turns the production engineering behind Claude Code agents into labs, assessments, capstones, and a production-readiness dossier.

Two passing Claude Code test commands point to different commit, working tree, and lockfile fingerprints, so the review marks one result stale and requests a rerun

Bind Claude Code test results to the code they actually tested

Claude Code can report passing tests from different repository states. Add a run fingerprint so each result names the exact code, dependencies, tools, and policy it tested.

An approved effect contract and a Claude Code MCP write enter a receipt gate that checks the principal, target, state change, and independent verification before completion

Require an effect receipt after every Claude Code MCP write

An MCP tool can return success after changing the wrong target or using the wrong authority. Make Claude Code prove the external effect before it reports completion.

A shared working tree enters a diff ownership gate where Claude Code changes continue to review while a developer edit and unattributed generated file are excluded

Make Claude Code prove diff ownership before it commits

Claude Code can accidentally include a developer’s unfinished edit or another agent’s output in its patch. Record the baseline, attribute every hunk, and block commits when ownership is unclear.

An approved Claude Code plan bound to commit A reaches a freshness gate after commit B changes a relevant dependency, so execution stops and the agent replans for review

Expire Claude Code plans when the repository changes

A Claude Code plan can become stale after another commit changes its assumptions. Bind approval to repository state and force a replan when the relevant boundary moves.

Claude Code sends a write through an MCP tool, receives a timeout, and verifies the external system before continuing, retrying, or stopping

A Claude Code tool timeout does not mean the action failed

A timed-out MCP tool call may have completed after the connection closed. Verify the external result before Claude Code retries a write.

An AI agent proposal passing through schema, operation, target, policy, dry-run, and approval checks before a receiving system may execute it

Treat AI agent output as untrusted input at every handoff

An approved AI agent can still produce a dangerous command, query, or tool argument. Validate generated output at the receiving boundary before another system acts on it.

An AI agent model fallback stopped at a security gate that checks provider, region, data, retention, tools, and policy before routing the request

Your agent's fallback model needs its own security decision

A model fallback can move prompts, retrieved data, and tool authority across a new provider or region. Treat each switch as a fresh policy decision, not a harmless retry.

Diagram showing a bad Claude Code run becoming a replay case, an eval, a control change, and a safer next run

Claude Code evals should start with the run that scared you

The best Claude Code eval is not a tidy benchmark. It is the uncomfortable run your team does not want to repeat, captured as a replayable production control.

Diagram showing a Claude Code permission budget across scope, tools, spend, and approval

Claude Code needs a permission budget

Before giving Claude Code wider access, define what each run may read, edit, call, spend, and merge. A permission budget keeps agent speed inside a reviewable boundary.