Turn your vibe-coded app into software your business can trust.

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.

Common starting points

  • Next.js
  • Supabase
  • Stripe
  • Clerk
  • OpenAI
  • Vercel

Services

The structure your AI-built product needs

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

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.

02 · Plan

Architecture & code quality

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

Production & security hardening

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

Agent-ready workflow & CI/CD

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

Test strategy & regression control

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

Operational readiness

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 traps usually appear after the demo works

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.

Get a scoped assessment before you rewrite

Send the repo context, your stack, the next feature you need, and the part of the app that currently feels hardest to change.

Engagement 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

A few practical answers for teams deciding whether to stabilize, modernize, or rewrite an AI-built app.

    • What kind of app is a fit?

      The best fit is a working web app with real business value, a growing feature backlog, and increasing friction from generated code.

    • Is this a rewrite service?

      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.

    • Do I need to stop using agents?

      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.