Built for large legacy codebases

Designed for large codebases where one uncontrolled change propagates regressions across dozens of modules.

In the following 18 minutes video, learn why generic agents fail, and how AICode works.

18 min

AI coding agents versus AICode

Why classical AI agents fail on large existing systems, and how AICode's methodology solves it, demonstrated on a real feature.

AICode is its own proof of concept.

AICode is 750,000 lines of production TypeScript, generated in 8 months, testable and in production, built and maintained by a single developer using AICode itself.

5h / uncut

Filmed proof, in real conditions

An unedited live development session of a full feature on a large production app. The full process as it actually happens, start to finish.

Another proof is the case study: an "impossible" 160-file refactor, rebuilt in three days with zero regressions.

The engineering expertise behind AICode.

15 years maintaining the same production codebase

Most developers never live with the consequences of their own code. They move on every 18 months. Before building the tool that solves this problem, Joël Abenhaïm created and maintained player22.com / keyja.com, a multiplayer gaming platform with 10 million downloads, as sole developer for 15+ years. AICode is built from that lived experience of what long-term maintenance really costs.

Master's in computer science, valedictorian

Graduate with highest honors. Background spans compiler theory, distributed systems, and real-time algorithms, well before AI coding tools existed. See the degree and the exceptional course-by-course results (PDF).

A documented engineering philosophy

The quality manifesto behind AICode, 31 pages on what differentiates maintainable code from code that will cost you a fortune in two years, is available for download (PDF). The same philosophy is infused into every AICode system instruction.

"Beyond a certain code size (roughly 50,000 lines), you cannot afford to code however you feel like. No human memory, including collective memory, is large enough to hold all the traps and side-effects a codebase of that size contains."

// from "The good code and the bad code", Joël Abenhaïm

This is not theory. This is the hard lesson of 15 years building and maintaining a large consumer platform alone. It is now the core constraint AICode enforces on every AI-assisted change.

Put it to the test.

Test AICode two days on your dirtiest legacy codebase, the one nobody dares touch.