AI Delivery System Setup
Stop copy-pasting from chat. Install a delivery system.
Your team can decide where Claude Code, Cursor, and coding agents belong, then turn them into a reliable product engineering workflow — with repo context, task slicing, review loops, production guardrails, and team habits — because unreviewed agent output creates production risk.
2 weeks · best for teams already using AI to ship product
Installed system
What gets installed
Context map
Product rules, repo structure, commands, constraints, and known traps.
Task pipeline
Issues sliced so agents can work without inventing scope.
Risk rules
Hard limits for auth, data, secrets, migrations, and deploys.
Review gates
What needs human approval before code lands or ships.
Team playbook
Examples, prompts, checklists, and the operating rhythm.
How it works
Map
Understand the product, repo, stack, team habits, and current bottlenecks.
Configure
Set up agent instructions, repo docs, commands, and repeatable workflows.
Pilot
Ship real work through the new flow and tighten the guardrails.
Transfer
Leave your team with patterns, examples, and a maintenance checklist.
Good fit
Use this when AI is already in the workflow.
- Your team already uses AI tools but quality and review debt are rising.
- The repo needs shared context, commands, risk rules, and human approval gates.
- You want repeatable delivery habits, not one-off prompt tips.
Not a fit
Do not add agents before the basics work.
- You are not using coding agents yet.
- You need someone to build the whole product for you.
- The team will not follow review gates or production guardrails.
Want AI to help ship, not create review debt?
Use this before coding agents touch production work. You get a workflow that fits your product, repo, team, and production risk tolerance.