AI can get you to a working prototype. We get you to production.
AI-assisted and “vibe-coded” tools have made it possible for a domain expert, not an engineer, to build working software in days. That’s real progress. It proves the idea solves a real problem, and it generates a remarkably complete picture of what the software actually needs to do — discovered by building, not just by planning.
What it doesn’t do on its own is make that software secure, reliable, integrated with the systems around it, or maintainable by anyone other than the person who built it. Working and production-ready are different bars, and the gap between them is usually invisible until something breaks.
We treat the existing build as the clearest requirements document available, then take it through:
This isn’t about mistrust of AI tools — we use them too. It’s about judgment: knowing which shortcuts are fine to keep and which ones will cost you later, understanding a codebase well enough to hand it off safely, and having seen the failure modes before they happen.
We’re not here to tell you the prototype was a waste of time. It wasn’t. We’re here for the part that comes after.
The cost of finding out a prototype isn’t production-ready is much higher after it’s already carrying real users, real data, or real revenue. This engagement can help you:
Should we rebuild this prototype, or is it further from production than it looks?
Tell us about the situation behind Prototype to Production and we’ll help you figure out the right next step.