Design an Enterprise-Grade Software Factory

Assemble an agent from model, context, instructions, tools, skills and memory, so every part has one job you can test.

Trace a bad result to the part that caused it, so you fix the context or a tool instead of rewording the prompt.

Write task briefs that state the goal, the limits, the checks and when to stop, so agents stop guessing what done means.

Define done as a check someone else can run, so no agent ever grades its own work

Evaluate every agent, the reviewer included, on many real cases and more than once, not one lucky demo.

Rerun your evals whenever a model, prompt or skill changes, and catch regressions before they ship.

Pair a builder agent with an independent reviewer, and route risky changes like permissions or customer data to a named person.

Run every job through a control plane that keeps its state, owner and next step, so work survives a crash or a closed chat.

Climb an evidence ladder from CI to shadow runs to staged rollout, and roll back fast when production says no.

Turn failures and repeated review comments into tests, rules and reviewed memory, so the next run starts smarter.

Mine agent logs for what people keep correcting and what agents keep searching for, not just what crashed.

Keep self-learning separate from retries: a retry fixes one run, reviewed memory fixes every run after it.

Count accepted work, not tries or pull requests, and price in every failed attempt.

Track time, cost and how often people stepped in per job, and find where the factory loses time.

Check the worst case, not just the average, before you give an agent more autonomy.

Put the day's ideas to work in a hands-on hour, with your own coding agent on a practice repo.

Leave with a starter kit, bootstrap template for your own repo, and a 7-day plan to bring one real workflow on your team into a factory.