Faster delivery.
Focused web MVPs typically launch in about 15 days once scope is locked.
How We Use AI in Our Process
AI helps us move faster. Senior engineers make every decision that matters.
We use AI tools like Cursor and Claude Code every day. They let a small senior team ship a focused MVP in about 15 days. But speed is only useful if what ships is correct, secure and maintainable, so we're deliberate about where AI writes code and where it doesn't.
Where AI helps, and where humans decide
AI helps us with
- Boilerplate and repetitive code
- First drafts of screens and components
- Writing and updating tests
- Searching and explaining large codebases
- Documentation and migration scripts
- Spotting bugs during review
Senior engineers decide
- Architecture and how the system fits together
- The data model and database access rules
- Authentication, roles and permissions
- Payments, billing and subscription logic
- Security, secrets and production configuration
- What ships, after reviewing every change
AI is very good at producing code that works for the case you describe. It's not good at knowing what your business needs, what can go wrong, or what a mistake costs. That part is our job.
AI under our control
"AI tools changed how fast we can build, but they didn't change what makes software good. An AI will happily add a fallback that keeps your app running when a security check fails. A senior engineer knows that's exactly when the app should stop. We use AI for speed and keep the judgement for ourselves."
Our rules for AI-written code
- 01
Every change is reviewed by a senior engineer.
AI-written code goes through the same review as code written by hand. Nothing ships because "the AI said it works."
- 02
Security code fails closed.
AI tends to add fallbacks so code keeps running under every condition. In auth, permissions and payments, we remove them. If a secret is missing or a check fails, the request is refused.
- 03
Critical paths get tests.
Sign-up, login, payments and your core workflow get automated tests, so the next change (AI-written or not) doesn't silently break them.
- 04
Secrets and customer data stay out of AI tools.
We don't paste API keys, passwords or real customer data into prompts.
- 05
Simple beats clever.
AI often generates more code than a problem needs. We cut it back, because every extra line is something you'll maintain later.
What this means for you
Same fixed price.
AI makes us faster; you still get a written fixed quote before work starts.
Code a developer can take over.
Reviewed, tested and documented, not a pile of generated files.
You own everything.
100% of the code and IP, in your own repository.
By the numbers
- 30+
- Products launched
- ~15 days
- Typical focused web MVP
- Since 2010
- Building for the web
- 100%
- Code and IP ownership
What it looks like in practice
Redmator: built in 15 days, 100+ paid users in week one.
A Reddit growth and lead-generation SaaS, scoped tightly, built by a small senior team with an AI-assisted workflow, and reviewed before every release. See case studies
Finishing AI-built apps.
We also take over apps founders built themselves in Lovable, Bolt, Cursor or Replit. The pattern is almost always the same: the app works, but database rules, secret keys, permissions or payments need an engineer before real customers arrive. Read our Lovable and vibe coding security checklist.
Tools we use
We build with
- Cursor
- Claude Code
- Next.js
- Node.js
- PostgreSQL
- Supabase
- React Native
We finish apps built in
- Lovable
- Bolt
- Replit
- v0
- Cursor
Frequently asked questions
Who owns the code generated with AI?
You do. All code we write for you, whether typed by hand or generated with AI and reviewed by us, is yours, along with the IP, from the repository in your account.
Is my code or data sent to AI tools?
Your source code is processed by the AI coding tools we use (such as Cursor and Claude Code) while we work on it, the same way it would be by any developer using these tools today. For client work we use privacy mode in Cursor. We don't put secrets, passwords or real customer data into prompts. If your project has stricter requirements, tell us before we start and we'll agree on the setup in writing.
What's the difference between an AI prototype and a production product?
A prototype shows the idea works. A production product also handles real users, real payments and real data safely: permissions checked on the server, database access rules, tested payment logic, monitoring and backups. More on this in when an AI-built app needs a real engineering team.
What AI tools do you use?
Mainly Cursor and Claude Code for development. We pick tools for the job, and the tool never decides what ships; a senior engineer does.
Can AI build a complex product on its own?
Not reliably. AI can produce large amounts of working code quickly, but complex products need someone to own the architecture, the data model and the trade-offs. Without that, you get an app that works in a demo and gets harder to change every week.
Does using AI make my project cheaper?
Usually faster, which keeps fixed prices lower than they'd otherwise be. Most focused MVPs we build land between $3,000 and $10,000. See MVP development cost in 2026.
Have a project in mind?
Tell us what you want to build, or send us the AI-built app you're stuck on.