LEVIATHAN Hackathon [AXI0M labs]

We optimised our systems for everything except the people inside them. This is a hackathon to reverse that. Use AI to rebuild, optimise, or represent a human system at human resolution.

A human system is any structure where people are the moving parts. These systems were built for scale, for throughput, for someone else's metric. They were not built with the human at their centre.

We want you to pick one. Study it. Then build AI tooling that does one of two things:

Optimise it — make the system work better for the humans inside it. Not faster. Not cheaper. Better. Strip out friction that exists because nobody questioned it. Surface information that's buried. Give people agency where the system currently removes it.

Represent it — make the system legible. Build a simulation, a visualisation, a digital twin, a model that exposes how a human system actually operates — where it fails, where it helps, where it punishes the people it was built to serve. Sometimes the most powerful tool isn't a fix. It's a mirror.

AXI0M's position is simple: systems that fail to acknowledge the limitations of the human at their core are dangerous. The human limit is not a ceiling to engineer past. It is the correct size of a made thing. AI gives us new leverage — but leverage applied without understanding the human at the centre just builds faster versions of the same broken systems.

This hackathon is a test of whether you can hold both things: the power of the tool and the fragility of the subject.

We are not just interested in what you build. We are interested in how you build it.

AI must be embedded in your build process — not as a gimmick, but as a genuine part of how you think, prototype, and ship. Your submission must include a written AI workflow method: what tools you used, at what stage, how they shaped your decisions, and where they fell short.

We care about this because the hackathon's thesis applies to your own process too. You are a human inside a system — the system of building. Show us you thought about that.