AI & Engineering
Everyone is being told to build with AI. Most end up with something that half-works, can't scale, and nobody can maintain. We use AI tools every single day — but the judgment that makes software actually ship is still human.
A senior engineer with AI tools builds faster, catches more edge cases, and ships with more confidence. A non-engineer with AI tools builds something that looks finished until it breaks in production.
We've seen both outcomes. The difference isn't the AI. It's the decade of experience that knows when to trust it and when to throw the output away and start again.
AI has changed how fast we can build. It hasn't changed what you need to build well.
The Limits
AI can write individual components. It can't decide whether your product should use a relational database or a document store, how to structure Firebase security rules for multi-tenant access, or what will break when you hit 10,000 users.
When your Stripe webhook fires but the database doesn't update, when your app crashes on iOS 17.4 only, when your DNS propagates to 8 of 9 nameservers — AI will guess. We've fixed these before.
App Store rejection reasons are cryptic, inconsistent, and sometimes wrong. Knowing which guideline they actually mean, how to write the response, and what to change — that's pattern recognition from shipping products, not reading docs.
AI-generated Firebase rules regularly have exploitable holes. AI-suggested auth flows sometimes expose tokens. The security layer of your product needs someone who understands what the attacker sees — not just what the tests pass.
Stripe webhooks, signature verification, idempotency keys, RevenueCat event reconciliation — AI knows the documentation. It doesn't know that the webhook will fire twice at launch, or that your test mode looks fine but live mode has a race condition.
AI will build what you ask for. It won't tell you that the feature you're asking for will make your MVP three months late, cost double, and won't matter to your first 100 users anyway. We will.
Our Approach
We're not anti-AI. We're anti-bad-judgment. Here's where it earns its place in our workflow.
The repetitive structure of a new page, API route, or component — AI handles the first pass. We review and modify. Net result: less time on the routine, more time on the parts that matter.
Before code ships, AI gets a pass to catch obvious issues — missing null checks, potential race conditions, accessibility problems. It's an extra set of eyes, not a replacement for the senior review that catches the subtle ones.
TypeScript types from API responses, JSDoc comments, README drafts — tedious but important work that AI does well. We spend that saved time on architecture and product thinking instead.
Evaluating a third-party API, exploring an unfamiliar library, comparing infrastructure options — AI accelerates the research phase so we make better decisions faster, with our own experience filtering the output.
Generating unit and integration test skeletons from existing code. We write the tests that matter for the hardest paths — AI covers the coverage-boosting repetitive cases.
When a client needs to see a concept quickly, AI helps us put something real in front of them in hours rather than days. The prototype is thrown away. The feedback is gold.
The Problem
We're not here to judge the founders who tried. We're here to help them fix it — or to make sure you don't end up here in the first place.
Every week we see the same story: a founder used Cursor, Claude, or Bolt to build their MVP. It worked for the demo. Then they tried to add a feature, onboard a paying customer, or connect a payment provider — and everything started falling apart.
The code is often functional but unmaintainable. Security rules are missing or wrong. The database schema doesn't support the features they need next. The architecture made sense at 10 users and breaks at 100.
"AI built my React Native app and it works on my phone, but it keeps crashing on Android and App Store rejected it twice."
"I got Stripe connected but I'm not sure the webhooks are actually firing correctly — sometimes subscriptions don't unlock the features."
"My Firebase database is full of user data but I realised I never set up security rules. Anyone with the config could read it all."
"The app works but nobody else can work on the codebase — it's a mess and even I can't figure out what half of it does anymore."
What This Means
AI-assisted development means we move faster than a traditional agency. Not because we're skipping steps — because the repetitive steps take less time, freeing us for the hard thinking.
Every system we build is designed to scale, maintainable by real engineers, and reviewed against the security and performance requirements of a live commercial product — not just a working demo.
If you want to add AI to your product, we'll tell you whether that actually solves a user problem or just adds complexity. We know which AI integrations are worth building and which ones burn runway with no return.
Already in the AI-built trap? We do codebase audits and rescues. We'll tell you honestly what's worth keeping, what needs to be replaced, and what it'll take to get your product to a place you can build on confidently.
Get Started
Tell us what you're building. We'll tell you how to build it in a way that lasts.