01 · Constitution
A project constitution your agents read
An AGENTS.md (with CLAUDE.md or .cursor/rules bridges) naming architecture boundaries, source-of-truth files, forbidden patterns, and verification commands.
Help your team write AI-assisted code the way a senior team would.
Most teams adopt Cursor, Copilot, and Claude Code months before they adopt the review habits, repo instructions, and CI gates that should sit around them. Post Code Labs works alongside your developers to put those pieces in place — on real pull requests in the repository you are already shipping from.
Common in the teams we work with
- Cursor
- Claude Code
- Copilot
- GitHub Actions
- Next.js
- TypeScript
Services
What an engagement actually changes
Six concrete things we put in place. None of them are deliverables we hand over and walk away from.
02 · Review
Review heuristics your team can apply themselves
We pair on the next handful of pull requests, name the heuristics out loud, and leave the checklist your developers will keep using.
03 · CI
A CI pipeline that is authoritative, not decorative
Install from the lockfile, typecheck, lint, tests, build, and migration validation — required on the merge path.
04 · Release
Branch protection and a release path you can describe
A default branch nobody pushes to directly, short-lived feature branches, preview deploys, and a release habit the team owns.
05 · Tests
Regression tests around the workflows worth protecting
Unit tests on the domain logic where an AI rewrite would hurt most, one integration test on the critical path, and a smoke test against a preview.
06 · Cadence
Working sessions on the real backlog
Two sessions a week on tickets the team would have shipped anyway, with asynchronous pull request review in between.
Once shipping is no longer the bottleneck, the same three doubts show up
After the first few months of agent-assisted work, the harder problems rarely come from the agent. They come from the workflow around it.
Review is the part we are least sure about
Reading an agent's diff is a different skill than reading a colleague's
Type drift, missed validation, duplicated logic, schema and code disagreements, stale agent instructions — a handful of patterns show up over and over. A short checklist catches most of them.
The same bugs keep coming back
When an agent reintroduces the same mistake, the prompt is rarely the right place to fix it
Recurring agent bugs are usually missing context, not missing instructions. The fix lives in types, lint rules, regression tests, and AGENTS.md — not in a longer prompt.
Nothing in the release path is blocking a bad change
There is plenty of automation. None of it is stopping a broken change from reaching production
A required merge path with install, typecheck, lint, tests, build, and migration validation — plus removing the silent paths that push to production from cron jobs or scripts on a server.
Tell us where the workflow is starting to creak.
A short note about the team, the stack, the next thing you are building, and the part of the workflow that has started to slow you down is enough to scope an engagement. We come back with a plan and a price.
What the first month usually looks like
Most engagements run on roughly this shape. We adapt it to what the team is actually shipping.
Week 1
Read the repo, pair on real changes
- Review the open pull requests with the team
- Walk the architecture together
- Ship a first AGENTS.md and a draft CI pipeline
Weeks 2 to 3
Wire the gates, do the work together
- Required CI checks live, branch protection on
- Pair on the next handful of pull requests
- First regression tests on the riskiest workflows
- A written review checklist, committed to the repo
Week 4 and onward
Hand it back
- The team runs the workflow without us
- Fortnightly review, ADRs, agent-instruction updates
- We stop when the cadence is no longer adding much
Field notes
Field notes for teams deciding what to do next.
Articles on the point where AI-assisted prototypes need clearer architecture, stronger types, and more durable workflows.
Linting Is Not Pedantry When an AI Is Writing Your Code
Why formatting, import rules, naming conventions, and static checks become practical safety systems in AI-heavy workflows.
Read articleYour App Needs a Constitution: Constraints for AI Coding Agents
A practical way to turn architectural decisions, naming conventions, data rules, and forbidden patterns into durable project constraints.
Read articleEngagement options
Engagements sized around the risk you need to remove.
Start small with a diagnostic, then invest in the code paths that unblock growth. Pricing is scoped after reviewing the product and repository.
$649
Fixed-price consultation
A structured diagnostic that scores the repository, product, and agent workflow.
- Ten-category repository and product review
- Pass, partial, or gap scoring with evidence
- Prioritized risk register and 30-60-90 plan
- Rewrite-versus-remediate recommendations
- Updated guardrails for agents and review
Custom
Open-ended engagement
Flexible implementation, technical leadership, coaching, or maintenance for a team that needs support.
- Diagnostic or focused discovery to start
- Hands-on implementation of priority changes
- Delivery leadership and code review for your team
- Agent workflow coaching and guardrails
- Ongoing development or maintenance support
Questions
Frequently asked questions
Practical answers for teams thinking about bringing us in.
Will you write code for us, or just teach us?
Both, in practice. We write code with the team on real pull requests in the same repository, and the lessons from that work go into the review checklist, the CI gates, and the agent instructions the team keeps. There is no parallel sprint of contractor code that gets thrown over a wall at the end.
How long is a typical engagement?
Four to six weeks of active work, then a lighter fortnightly cadence for as long as it is useful. We try not to overstay. The engagement is working when the team can run the same cadence without us.
What is in the team's hands at the end?
A committed AGENTS.md and any tool-specific bridges, a CI pipeline that is required on merge, branch protection on the default branch, a regression suite around the riskiest workflows, and a review checklist your developers actually use. The artifacts live in your repo, not in our notes.
Need more detail? Read the full FAQ.