AI PROJECT AUDIT BY BRAINFAB

Find out if your AI-built project is actually healthy

Get a Project Health Dashboard that brings engineering risks, architecture gaps, and missing technical decisions into one clear view

Works with your AI coding agent

  • Cursor
A technology expert speaking on a dark conference stage before an audience

AI can generate code fast

You own production readiness

Andrew Bennet, Co-Founder, Brainfab

Working software is only the tip of the iceberg

What you see in your project

  • Screens and design
  • Working features
  • User flows
  • Shipped updates

What affects your project’s health

  • Architecture and module boundaries
  • Data ownership and consistency
  • Security and access control
  • Reliability and failure handling
  • Testing and regression protection
  • Performance and scalability
  • Dependencies and integrations
  • Deployment and recovery
  • Maintainability
  • Technical decisions
Engineering areas
15
Assessment topics
46
Questions to investigate
356

Project Health Dashboard

See how audit results could appear in your dashboard

Overall health

40% Red illustrative band

  • Project Health 40% Red illustrative band
  • Architecture Health 40% Red illustrative band
  • Decision Health 40% Red illustrative band

Project Health 40% Red illustrative band

  • Payment retry policy

    A timed-out payment can be submitted a second time without a stable request key

    Status: Needs improvement Priority: Critical
  • Payment regression coverage

    No automated case covers a timeout followed by a retry

    Status: Needs improvement Priority: High

Architecture Health 40% Red illustrative band

  • Authorization ownership

    Permission rules are split between route handlers and domain services

    Status: Needs improvement Priority: High
  • Module boundaries

    Payment UI imports internal order-service modules directly

    Status: Needs improvement Priority: High

Decision Health 40% Red illustrative band

  • Recovery objectives

    No recorded decision defines acceptable downtime or order-data loss

    Status: Needs improvement Priority: High
  • Refund policy

    The project has no agreed rule for approval and order-state changes

    Status: Needs improvement Priority: High

Illustrative recommendations · Simple Project

The most valuable improvements 5

Five recommendations selected for this fictional sample. They illustrate possible next steps, not a measured ranking or a customer result.

  1. Project Health / Payment retry policy

    A timed-out payment can be submitted a second time without a stable request key

    Define one idempotency rule for payment attempts and apply it at the payment boundary. This keeps a retry from creating a second charge when the first response is lost.

  2. Project Health / Payment regression coverage

    No automated case covers a timeout followed by a retry

    Add regression cases for a successful charge, failure, timeout, and retry before the next release. These checks can expose a payment-policy break before customers encounter it.

  3. Architecture Health / Authorization ownership

    Permission rules are split between route handlers and domain services

    Choose one authorization boundary for permission decisions and document the inputs it requires. A clear owner keeps new routes and agent-written changes from applying different rules.

  4. Decision Health / Recovery objectives

    No recorded decision defines acceptable downtime or order-data loss

    Agree how long Simple Project can be unavailable and how much order data it can afford to lose, then record those targets beside the recovery plan.

  5. Decision Health / Refund policy

    The project has no agreed rule for approval and order-state changes

    Decide when refunds are allowed, who approves them, and how an order changes afterward. A shared rule keeps support, product, and payment behavior aligned.

A project-specific assessment

The assessment is designed around your product, stack, and development stage.

A dashboard you can revisit

Return to your findings whenever you decide what to improve next.

Stronger foundations, not bug fixes

Strengthen architecture, technical decisions, and project guidance.

How AI Project Audit will work

  1. Step 1:

    Create a free Brainfab account and workspace

  2. Step 2:

    Connect Brainfab MCP to Codex, Claude Code, or Cursor

  3. Step 3:

    Ask your coding agent to start an AI Project Audit through Brainfab MCP

  4. Step 4:

    Review your Project Health Dashboard and improve your project

Online audit access is not open yet.

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AI Project Audit articles

AI Project Audit Blog

Questions

Understand what the dashboard gives you

Is this a generic checklist?
No. The dashboard is organized around your project evidence. Important findings show what supports the conclusion and where information is incomplete.
What does the complete dashboard add?
The complete dashboard adds Brainfab's full diagnosis: coverage, priorities, supporting evidence, open questions, limitations, and guidance for your next decision. It does not hide evidence or observations already visible to you or your agent.
Does the audit fix the project?
The audit diagnoses and prioritizes. Implementation, ongoing monitoring, and broader AI CTO support are separate next steps.
Can I start an audit from this page?
Online audit access is not open yet.

See what an audit could reveal about your AI project