AI can write code faster than any engineer you could hire. It can't tell you whether that code is secure, will hold under real users, or is quietly turning into a liability. I read what the model wrote and give you a straight answer: what's solid, what's fragile, and what to fix before it costs you.
You opened a chat window not expecting much, and by the end of the weekend you had something real: users could sign up, data was saved, buttons did things. It's a genuinely impressive experience, and it leads to one very natural conclusion — "I don't actually need to hire an engineer. I can just build this myself, with AI."
That conclusion quietly mixes up two different skills. Coding is producing lines that run. Engineering is knowing which lines to write, why, what happens when real users, real data and real edge cases hit them, and how to build something that keeps working after you've moved on to the next feature. AI is remarkable at the first. It has no opinion at all about the second — and it will never volunteer that distinction to you.
Impressive and fast is not the same as correct and safe.
It fades one uneasy realization at a time. If any of this sounds familiar, you're exactly on schedule!
It works, so it must be fine. You start telling people you built it yourself.
Googling error messages you don't understand, copy-pasting the fix without knowing why it worked.
"Wait — is this thing actually safe to put a real customer's data into?"
A new feature breaks three old ones, and you don't know which change did it, or why.
Learning auth, infrastructure and deployment all at once, while the business is still waiting on you.
It's entirely your responsibility, you're not sure who to ask, and you're not sure you want to show anyone yet.
None of this is about intelligence. It's about experience you haven't had time to build yet.
You haven't spent years learning how auth, data, infrastructure and deployment are supposed to fit together. Without that model, a normal error and a five-alarm fire look identical.
The model never says "I'm not sure." It writes broken, insecure or outdated code with exactly the same confidence as it writes good code.
On a real team, every line gets a second pair of eyes before it ships. Building solo with AI removes that check completely, right when you need it most.
Exposed keys, missing auth checks, unvalidated inputs — the kind of gap that never shows up in a demo, only in an incident.
A new feature can quietly break three old ones, and the first sign of it is a user complaint, not a red build.
Demos don't reveal slow queries or fragile infrastructure. Growth does, usually at the worst possible time.
Every shortcut is invisible today and expensive in six months. It stacks faster than it looks like it's stacking.
A future engineer, or an investor's technical due diligence, has to reverse-engineer months of undocumented decisions first — usually with money already on the table.
AI is one of the most powerful tools our industry has ever had. Like any powerful tool, it doesn't remove the need for judgment, it raises the price of not having any. A table saw doesn't replace a carpenter; it just makes an inexperienced pair of hands more dangerous, faster.
Someone still has to be the judge of what's good enough to ship. The reviewer who catches what the model missed. The gatekeeper who decides what goes near real user data and what doesn't. The one person actually responsible if it breaks. That's not a role AI can fill, no matter how good it gets as it's built to produce output and definitely not to hold responsibility.
That's what I bring back into the picture: not a rewrite of everything you built, not a lecture about the "right" way to do it from scratch but a second, experienced pair of eyes that tells you exactly where you stand, so you regain control of the beast. It's still your project, and it should stay that way.
Before this code becomes the permanent foundation of your business, let's find out what it's made of.
Architecture, data model, dependencies, and the overall shape of what's there today.
Auth, secrets, inputs, permissions: the gaps that don't show up until someone finds them for you.
What's safe to build on, what will bite you, and what needs rewriting now, ranked by how much it matters.
A concrete list you, or the next engineer you hire, can execute in order, instead of guessing where to start.
I explain the findings in plain language and answer every question — no jargon you have to pretend to follow.
Options for moving forward: fix it yourself with the plan in hand, bring me on for ongoing oversight, or hand it to a new hire with a real map instead of a blank page.
30 minutes, no commitment. We talk about what you built, what's worrying you, and what's at stake.
A read-only invite to your repository, and staging environment if there is one. Under NDA if you need one.
I read the code the way an engineer would if they were about to inherit it: architecture, security, data, dependencies, tests.
A written risk report, plus a live call to walk through it together in plain language, with a prioritized plan.
Hello there!
My name is Cyrille, I'm Canadian and French and I've been helping venture-backed startups, bootstrapped companies and medium-sized companies ship software, for the past 20 years.
My deep desire for learning and seeing my clients' businesses expand has led me all over the globe, partnering with founders, teaching and turning ideas into revenue-generating realities, in many industries including music, real estate, critical infrastructures, banking and more.
« My cofounder and I were non-technical and needed someone to help us bring our vision to life. Cyrille came on during the earliest days of Blueboard and built the whole v1 of the platform by himself. It enabled us to bring on our first 15 customers, and ultimately, to secure admission into the 500 Global accelerator. We wouldn't be here without Cyrille - beyond working together on the business side, we had fun along the way. I couldn't ask for anything more and would gladly work with Cyrille again in the future. »
No. Every audit I've done on AI-built code finds real issues — that's the entire point of doing one before it gets expensive to fix. I'm reading it as an engineer, not judging you for the sensible choice of building fast while it was cheap to do so.
Rarely all of it. Most audits find a mix: a few real problems that need fixing, and more of the app that's fine than people expect. You get a specific, prioritized answer instead of a blanket verdict.
It won't take long, and it's probably best to take a short break from development while the audit is in progress.
Most of what founders end up with when building with AI, including Rails, Node, Python, React and Next.js. If you're not sure yours qualifies, ask on the call — it's free.
Yes, happy to. Just say so when you book the call.
Whatever's useful to you: you take the report and fix it yourselves, I stay on for ongoing oversight, or you hand the report to the next engineer you hire so they start from a map instead of a blank page.
One 30-minute call so I get to know you and your project