Turn your AI prototype into a real product

You built something with an AI tool. It works as a demo. Now you need it to work for real users, at scale, without falling over. That's what I do.

Lovable

Bolt

v0

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Replit

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You've already done the hard part

Most startups stall at the idea stage. You didn't. You picked a tool, built something real, and proved the concept works. That's genuinely valuable — you've validated your idea faster than most teams with a full engineering department.

Now the job is different. Going from demo to product means closing the gaps that AI tools leave open:

• Authentication and security — proper session management, environment variables, rate limiting
• Database design — indexed queries, migration strategy, schemas that scale with your users
• Error handling — graceful failures instead of crashes when something unexpected happens
• Testing — automated tests so you can ship changes without holding your breath
• Performance — fast load times, caching, efficient queries
• Deployment — staging environments, monitoring, deploys that don't need you awake at 3am

These aren't flaws in your prototype — they're just the next step. And it's a step that goes much faster when you start from something that already works.

Why should I care?

Your prototype works when you demo it. A production system works when 500 people use it at the same time, when someone enters something you didn't expect, when your server restarts at 2am, and when a customer trusts you with their credit card.

Here's what actually happens when founders skip this step:

• Your app goes down on launch day — you get featured, traffic spikes, and the whole thing crashes because nothing was built to handle more than one user at a time
• A user finds a way to see other people's data — AI tools rarely generate proper access controls, and one screenshot on Twitter can end your company before it starts
• You can't change anything without breaking something else — generated code is often one big tangled file with no structure, so every small change is a gamble
• You hire a developer and they want to rewrite everything — which costs you months and tens of thousands, when targeted fixes would have been a fraction of that
• Investors ask about your tech and you can't answer — "it was built with Lovable" isn't a technology strategy, and serious investors will want to know what happens when you scale

The gap between a prototype and a product isn't polish — it's the difference between something that works in a demo and something you can build a business on.

What I do

I don't just write a report and hand it back. I do the work. A typical engagement looks like this:

• Architecture review — I audit the generated codebase, identify structural issues, and prioritise what needs fixing now vs. what can wait
• Security hardening — proper auth, environment management, input validation, and OWASP compliance
• Database and API work — schema redesign, migration strategy, API structure that will scale
• Testing and CI/CD — automated tests, deployment pipelines, staging environments
• Production deployment — monitoring, logging, error tracking, and a deployment process that doesn't require you to be awake at 3am

The goal is a codebase you can confidently build on — whether that's you, your future team, or me on an ongoing basis.

Who this is for

Founders and small teams who've used AI tools to validate an idea and now need to ship it properly. You've got paying users or a launch date, and you need someone who's done this before — not another AI tool.

About me

I'm Ben Leavett. I've been working with founders like you for over 17 years, leading engineering and product teams at Microsoft, SwiftKey, and Glovo — building products from zero to millions of users. I run Cadence Digital, a product development consultancy based in France and the UK.