Grab the one doc that maps to the failure you're worried about for $5, take the whole Season 1 bundle for $29, or have us audit your repo against all of it. Every purchase is an instant PDF download — no DRM, yours to keep.
Every one-pager in Season 1, the combined cover-to-cover PDF, and the standalone Go-Live Checklist — the whole doctrine in one download. Buying the 23 docs one at a time is $115; the bundle is $29.
One page per topic: what breaks, why you never see it coming, and the exact checks that catch it.
Vibe-coded apps share one flaw: authentication that looks right and functions right, but whose security model is Swiss cheese. The developer never sees it, because they only ever tested with one account.
AI-generated authentication is dangerous precisely because it looks right and functions right — while the security model underneath is Swiss cheese. A working login screen proves nothing about what's behind it.
The auth bugs that end companies never show up in testing. They show up under concurrent load, when session tokens collide and user A opens user B's dashboard.
AI coding platforms don't sandbox your secrets, don't audit for exposed credentials, and don't enforce least privilege. If you're not paying attention, your keys ship with your app — and bots find them before your first customer does.
AI-generated code compiles, runs, and demos beautifully — and most of it cannot defend against a basic cross-site scripting attack. The model optimized for "works", not for "hostile input".
AI builds by importing libraries — and it never checks whether those libraries are maintained, vulnerable, or even legal to ship. Your app is only as secure as its weakest import.
Every serious product goes through a pre-launch security review — dozens of items, checked one by one, every release. Most solo builders run zero of them. Not because they're lazy, but because nobody ever showed them the list.
If an LLM generated your app and it hit production without a human security pass, you're not running a startup. You're running an experiment on your customers' data.
AI-generated code optimizes for *works*, not for *works at scale*. Nothing is wrong until everything is wrong at once — and by then, it's launch day.
Every vibe-coded app hits the same ceiling: it runs beautifully for one user and collapses the moment real traffic shows up.
API costs that look negligible in a demo become the line item that kills your margin at scale, and by the time you notice, the invoice has already landed.
An AI feature that costs nothing with one user costs a fortune with a thousand — model the bill before you set the price, not after the first invoice.
Vibe-coded apps generate code for the happy path — never code that records what happened when things go wrong.
AI writes features on command. It never writes observability unless you ask — so most vibe-coded apps run with no idea what's actually happening inside them.
Every schema change made straight to production without a record of it is a bet that nothing will ever go wrong. Eventually the bet loses.
When a deployment succeeds or fails at random, the process isn't broken — it never existed in the first place.
Feature flags split "deploy the code" from "turn on the feature" into two separate decisions — so you never have to bet an entire release on one moment.
Vibe-coded apps get built and tested against one perfect path — one user, clean data, ideal conditions — and that path is never what real users take.
AI tools take an idea to a working prototype in a weekend — then production readiness stalls it, because a working demo and a shippable product are not the same thing.
AI doesn't click buttons. If your platform only exposes features through a UI, no AI agent — yours or anyone else's — can actually use it.
Before you promise an AI feature, check whether your architecture can physically support one — most legacy platforms can't, and no amount of clever prompting fixes that.
App-store review is a production gate, not a formality — treat it like a security audit or you'll spend months resubmitting.
AI can write code that runs on your laptop — it doesn't automatically write code another human can maintain.
Send us your repo or app URL with read access and we review it against the full go-live doctrine — auth, secrets, input validation, dependencies, scaling, API cost, logging, database, deploys and more — then deliver a ranked, triage-first report within 5 business days.
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