Can users see data that isn’t theirs?
Login, sessions, permissions and protected pages, plus the database rules behind them (Supabase RLS, Firebase rules) that AI tools often leave open.
You built it with AI and it works. Before real users depend on it, I’ll find what’s quietly broken: who can see whose data, payments, and what happens when things fail.
AI coding tools are excellent at getting you from a blank page to a working product. Working is not the same thing as ready.
I review your live app and your code, with extra attention on the places AI-built apps are most often confidently incomplete.
Login, sessions, permissions and protected pages, plus the database rules behind them (Supabase RLS, Firebase rules) that AI tools often leave open.
How your tables are set up, what happens when the data changes shape, and defaults that quietly cause problems months later.
Stripe webhooks, form validation, double submissions, retries and rate limits: the things that break once real traffic arrives.
Loading, empty and error screens; buttons that do nothing; phone layouts; things that break if someone taps twice.
API keys and secrets, separate test and live environments, logging, and whether you’d hear about a bug before a user emails you.
Refreshing mid-checkout, hitting back, cancelling, retrying, going offline, changing plans or arriving from an old link.
Every finding is labeled: fix before launch, fix soon, or leave it alone. Each one explains what it means in plain language, how to fix it, and a prompt you can hand back to your AI tool.
Weekly plan screenshot coming soon.
Refreshing here loses the user’s current plan.
Tend is the planner I’m building. I’m running the exact audit I sell on it before launch and posting every finding, including the embarrassing ones.
Follow the Tend audit →You show me what you built, where you are in the launch process and what you’re most unsure about.
You share the live app and read-only access to the repo. I send a short checklist so I have what I need.
I test the product, trace the risky paths through the code and document findings as I go.
You leave with a prioritized fix list and a clear sense of what can safely wait.
For small web apps and MVPs, roughly up to 20 core screens. Larger apps are scoped separately.
Why a founding price? I’m opening five audits at this price while I build my first case studies. You get a senior review for less; I ask for honest feedback and, if it helped, a short testimonial.
Book a free call →opens in a new tab
I’m a senior software engineer with experience across frontend, backend, APIs, authentication, data and product UX. I’ve shipped inside larger engineering teams, owned systems end-to-end and built a product from zero as a co-founder.
I use AI coding tools every day, and they’re incredibly useful. What I care about is the gap between a convincing first draft and software you can actually trust. I’m keeping this small on purpose: a handful of audits, done carefully.
Yes, that’s who it’s written for. Every finding explains what the problem is, why it matters to your users and how to fix it, including a prompt you can hand back to your AI tool.
Read-only access to your repository is all I need. I never need your live API keys or passwords, I delete my copy of your code when the audit is done, and I’m happy to sign an NDA.
Most web apps built with Cursor, Claude Code, Lovable, Bolt, Replit or v0: typically React or Next.js with Supabase, Firebase or a Node backend, and Stripe for payments. If you’re on something else, ask on the intro call.
Usually, yes. Most of these tools can sync your code to GitHub. We’ll check on the intro call before you pay anything.
Then you launch knowing it’s solid. The report still shows exactly what I checked and what’s working well, which is worth having before you send real users in.
The audit is the review, not the fixes. Many issues are quick to fix yourself with the report. If you’d rather hand them off, we can scope a Fix + Ship Sprint, and the audit fee is credited toward it.
Ready when your app is
Not ready yet? Follow @lauraq.dev for short tips on what AI gets wrong.