The recurring problems behind every AI product — who is signed in, what their plan allows, what a run cost, who to bill, what to tell an auditor — and why they belong in a dependency, not in a prompt.
Three ways a well-prompted coding agent still gets the boring half wrong — and what shipping it finished changes.
Tenancy bugs don't show up in a demo. They show up when a second workspace sees the first one's data.
Days and millions of tokens on infrastructure that has nothing to do with what makes your product yours.
A model writes in the style of what surrounds it. Start clean and every commit inherits that.
Pick the plan you'd otherwise follow and see what changes — what you keep, what you drop.
The other half — tenancy, entitlements, credits, billing, audit — arrives as typed services with the tests already around them.
A boilerplate is a snapshot you maintain alone. These stay upgradable packages — SemVer, migrations, doctor.
Those own your agent. Intelligo can't — there is no agent abstraction, only the boundary your framework's runs pass through.
Auth and billing need senior judgment every time. Here it already shipped, tested — your coding agent only has to be good at the product.
Unconnected primitives. This is a pre-wired boundary that ties AI cost to credits, entitlements and audit — the glue is what goes wrong.
Retool is for internal tools. This is a customer-facing product whose source you own and deploy like any Next.js app.
The long answer to one of them: a framework, or a SaaS boilerplate?
Ready to try it? Three commands and the app runs against a stub model.