01 · Diagnose
Structured diagnostics
A score across ten categories — agent instructions, architecture, types, tests, CI/CD, production, security, compliance, observability, and workflow — against the repo and the running product.
Post Code helps businesses professionalize AI-generated applications: cleaner architecture, stronger types, safer releases, and a lower-risk path forward than starting again from scratch.
Agents are excellent at creating momentum. Post Code supplies the diagnostic, remediation, and review discipline an AI-built product needs once real users and real money are on the line.
01 · Diagnose
A score across ten categories — agent instructions, architecture, types, tests, CI/CD, production, security, compliance, observability, and workflow — against the repo and the running product.
02 · Plan
Convert generated screens and duplicated handlers into typed domain modules, enforceable module boundaries, and runtime-validated trust boundaries so future changes have somewhere stable to land.
03 · Harden
Reinforce the paths most likely to break under real users — authentication, authorization at the data layer, idempotent jobs and payments, rate limits, security headers, and the observability needed to know when something is wrong.
04 · Guard
Make AI tools safer by giving them a project constitution, strict lint and type rules, required CI gates, and review checklists so the next prompt doesn't quietly make the app worse.
05 · Test
Turn brittle happy-path coverage into focused unit, integration, and end-to-end checks around the workflows where an AI-assisted change would be most expensive to get wrong.
06 · Run
Wire the product for maintenance after launch with release discipline, actionable monitoring, incident paths, and the ownership notes a team needs before scaling the next round of changes.
The first version proves demand. The next version needs boundaries, runtime checks, and the confidence to change important code without restarting the product
Plausible code, hidden risk
Generated code that looks consistent often skips the runtime checks at trust boundaries
Forms, API routes, webhooks, and queues validate at compile time but not at runtime. We surface where the database schema, the application types, and the actual inputs have quietly diverged.
Bugs the agent keeps reintroducing
Recurring regressions usually mean a missing type, test, or lint rule — not a longer prompt
We convert repeat bugs into discriminated unions, regression tests, and project-specific lint rules so the same mistake cannot land twice. Duplicated logic across screens and jobs becomes shared, typed utilities.
The demo-to-durable gap
Auth gaps, non-idempotent writes, and missing observability are what hurt real users
We harden authentication on every protected route, push authorization down to the data layer, make payment and background jobs idempotent end to end, and wire critical paths to monitoring so failures surface before customers notice.
Send the repo context, your stack, the next feature you need, and the part of the app that currently feels hardest to change.
Articles on the point where AI-assisted prototypes need clearer architecture, stronger types, and more durable workflows.
Why formatting, import rules, naming conventions, and static checks become practical safety systems in AI-heavy workflows.
Read articleA practical way to turn architectural decisions, naming conventions, data rules, and forbidden patterns into durable project constraints.
Read articleStart small with a diagnostic, then invest in the code paths that unblock growth. Pricing is scoped after reviewing the product and repository.
$649
A structured diagnostic that scores the repository, product, and agent workflow.
Custom
Flexible implementation, technical leadership, coaching, or maintenance for a team that needs support.
A few practical answers for teams deciding whether to stabilize, modernize, or rewrite an AI-built app.
The best fit is a working web app with real business value, a growing feature backlog, and increasing friction from generated code.
Not by default. I start by identifying what is already valuable, then replace brittle pieces only when that is cheaper or safer than stabilizing them.
No. The goal is to make agents safer by giving them clearer architecture, better repo instructions, typed contracts, and review gates.
Need more detail? Read the full FAQ.