INDEX
Everything we have published
Every experiment runs in the open and every number is reproducible from the code
that produced it. Newest first.
- HL-P-006 JUL 30, 2026 Same Rule, Opposite Signs Banking ran our definition-change test for us, better documented than we could have managed, and the answer was not the one anybody expects. On one day in January 2020 a single accounting rule moved reserves up at three banks and down at a fourth, and up and down inside the same bank. That gives a coherence test costing one group-by, and it also breaks a category we had been treating as one thing. Hello World Models aiworld-modelsregulated-aibankingsimulation
- HL-P-005 JUL 27, 2026 The Rules Are Half the Physics Regulated industries break world models in four specific ways: colliding clocks, feedback loops, legal fences, and your own output becoming your next input. They also hand you the one thing world-model builders everywhere else lack, which is a supply of free, dated, published interventions to test against. Hello World Models aiworld-modelsregulated-aisimulationhealthcare
- HL-P-004 JUL 6, 2026 The LLM Learned to Stop Planning We let an LLM design competing species, run them headless in the living world, and refine them from the results. Over three rounds it revived an extinct lineage into the winner and abandoned its own planner. Going deeper on Part 1. Hello World Models · Part 3 aiagentsgoapworld-modelssimulation
- HL-P-003 JUN 29, 2026 Part 1: A World From a Seed A handful of procedural rules can grow a whole living world. First a planet from a seed, then life that adapts to it, procedurally, and with an LLM. This is how games can teach our agents. Hello World Models · Part 1 aigamesprocgenworld-models
- HL-P-002 JUN 22, 2026 Hello World Models Why we build practice worlds for regulated AI, learned from games. The story behind the series, and what it explores: costs, tradeoffs, and worlds grown from the law itself. Hello World Models aigamesregulated-aiworld-modelsintro
- HL-P-001 APR 6, 2026 Implementing TurboQuant in llama.cpp: CUDA Scars and What Actually Ships Part 1 of 2.
Why We Did This Hammer.ai runs a industrial research lab hyper focused on regulated domain document understand at extremely efficient margins. Private equity self funded companies like f cudaGPUllmquantization