who
I’m Teïlo Millet — a self-taught AI engineer based in Paris. I’m interested in research around large language models: reinforcement learning, alignment, safety, and everything in between.
now
consultant data & AI at OCTO Technology.
before
I tried to build enzu as a company at STATION F (Fighters Program). enzu is a toolkit for running LLM tasks with hard spending limits — budgets as laws of physics, not best-effort throttling. typed outcomes, async delegation, stress testing, and retry tracking. the idea: if you want to delegate a task to an LLM autonomously, you need guaranteed cost caps.
open source
textpolicy — reinforcement learning for text generation on Apple Silicon (MLX). GRPO, GSPO, LoRA fine-tuning.
enzu — budget-controlled recursive language model (RLM) execution in Python. hard caps on tokens, time, and cost. typed outcomes for every run.
gollm — unified Go interface for LLM providers. prompt optimization, structured output, model comparison.
raggo — production-ready RAG library in Go. document loading, semantic chunking, vector storage.
models
MiniMerlin-3B — reached global top 5 in the 3B parameter category on HuggingFace’s Open LLM Leaderboard.
writing
intuitus — a French newsletter on AI, prompt engineering, and the tech industry.
links
github · huggingface · x · linkedin · teilomillet@gmail.com