AI should design, not idle in the request path
Your AI builds the backend once. After that, every ordinary request runs as plain code, so you pay for AI only where it makes a decision.
AI is great for sketching templates and prototypes. Production software is different: it has to give the same answer every time, and AI is probabilistic by nature. So nostackai lets your AI describe the app, then runs it as deterministic software, serverless on AWS, without spending tokens on every request.
AI is here to stay. But the way most products use it today starts from the wrong expectation: that more AI is always better.
So AI tools generate unlimited amounts of code that someone still has to read, review and maintain. The result is AI slop: software that looks finished, costs a fortune in tokens, and gets harder to change with every prompt. Token maxing, without the benefit.
And most products charge credits for everything. That works for a demo. It stops working at scale, when every user and every request burns more credits than the business earns, and companies discover their AI bill grows faster than their revenue.
We want to change that. Use AI where it adds judgement, and let reliable software do the rest.
“AI is the once-in-a-lifetime technology I've been waiting for since my first four lines of Fortran.”
I fell in love with programming the moment I wrote my first program in Fortran. Ever since, I've been obsessed with one idea: making it easier to turn what you imagine into software.
I've built framework after framework, platform after platform, always trying to close the gap between what I imagined and what technology let me build. It was a constant battle. My ideas were always bigger than the tools available to bring them to life.
Then AI changed everything.
For the first time, we have a technology that can understand intent, reason about possibilities, and turn them into working software at an entirely different scale. It's the biggest shift in software creation I've seen in my career.
But there's a catch: AI is probabilistic, and software needs to be dependable. Using AI for everything, especially work that ordinary software can do deterministically, burns tokens on every request and gives different answers to the same question.
I believe the future isn't AI replacing software engineering. It's AI and software engineering working together, each doing what it does best.
That's why I built nostackai.
AI understands what you want to build. Purpose-built software handles the execution. The result: fewer tokens, less AI slop, greater reliability, and a dramatically shorter path from idea to production.
After a lifetime of trying to make software easier to build, I finally feel like the tools have caught up with the ambition.
Your AI builds the backend once. After that, every ordinary request runs as plain code, so you pay for AI only where it makes a decision.
Bring your own keys on every plan, including Free, for Anthropic, OpenAI, Gemini or any OpenAI-compatible model. We never resell tokens.
Entities, Logic Blocks, automations and agents are versioned config. A change is a few fields, not a regenerated codebase.
Every org's and workspace's data sits in its own partitions, checked on every request. Enterprise gets a dedicated stack.
Workspaces, sign-in, SSO, access rules, payments, schedules and feature flags are part of the platform, not a weekend of glue code.
API and architecture docs are generated from what you built, so they are never out of date.
We share new features, walkthroughs and builds as they ship.
Start free with your own AI keys, or tell us what you're building and we'll show you how it fits.