Prototype → Production - You built it with AI. We’ll make it production-ready.
The prototype did its job. It proved the idea, got the buy-in, maybe won the pilot. Now someone has asked when it goes live, and the honest answer is that it isn’t a system yet — it’s a demonstration with a URL.
That’s not a failure. This is the normal shape of AI-assisted development. The generated code is often fine. What’s missing is everything around it.
What’s usually missing
- Tests. Not “some tests” — a suite you can run before every deploy and believe the result.
- A real environment, including secrets management, backups, monitoring, a way to roll back.
- Data model discipline. Database schemas generated from code and automatically applied to production.
- Access control that survives a security questionnaire.
- Documentation that lets a second developer contribute in week one, not month three.
- A deployment process that isn’t a person.
What we do
- Read what you have. A short review — days, not weeks. You get a written assessment of what’s salvageable, what has to be rebuilt, and roughly what each costs.
- Agree what “done” means. Explicit, written, testable. Most disagreements about software are actually disagreements about this.
- Build it out. Test-driven, AI-accelerated, in short cycles with working software at the end of each one.
- Deploy it. To a secure production environment, with the pipeline and the runbook.
- Hand it over. Code, tests, docs, and the rules file that keeps the AI tooling consistent for whoever comes next.
What we might tell you
We may set aside some of your wonderful ideas. More likely we’ll adapt them to what you really need. However, if the honest answer is “start again”, you’ll hear that in week one rather than in month four.
Let’s have a chat.
Thirty minutes, no pitch deck. Tell me what you’re building or what’s stuck, and I’ll tell you what I’d do.
Ireland. Remote-first.