Hey, I'm Séverin.

I'm a repeat founder and product builder.
I've been building on language models since before ChatGPT.

My obsession

Use software as a medium to let agents compound intelligence with every task.

People use LLMs as printing machines, reproducing the same artefacts over and over. I think they should be used as the brain cells of a living organism instead — an organism that uses software as a substrate to continuously improve its connections and muscle memory.

Three lines of research

All under Creative Robots, the company I've been running since 2021.

I

Better primitives, made by agents… for agents.

Mostly focused on the app-creation vertical, where the goal was to use AI to build entire web and mobile apps as artefacts.

2021 — 2025

Started as an ideation before ChatGPT, when models couldn't even produce a valid JSON yet. A DSL that lets an LLM compose an entire web and mobile app — one parse tree to Next.js and Expo — from a syntax simple enough that designers wrote it too, and constrained enough that a model can't get it wrong.

Slices
soon

Better primitives for humans and agents working on Next.js.

II

Software as a medium for muscle memory and shared knowledge.

General agents this time, no vertical. The goal is that whatever one agent figures out becomes a tested program every other agent can run, and improve.

Skills.dev → OpenIntegrations + MuscleMemory soon

A shared store of auto-optimized, auto-evaluated software snippets. An agent searches for an existing snippet that performs the action it needs, runs it, and publishes suggested changes and evolutions back — so every agent in the world can contribute to improving them.

Built before Anthropic's Agent Skills. The domain has since been sold; the work is being republished as OpenIntegrations and MuscleMemory (soon).

A harness that lets an agent modify its own code and spread across machines. It writes its own tools for whatever platform it lands on, and gains pervasive capabilities from an ever-growing mesh of devices it runs on.

Try — create an agent, run the command on your own machine, then ask it to photograph you by building the tool first, to spawn itself a server with the AWS CLI, or to spread to a Raspberry Pi on your network.

III

Humans out of the loop: safe infrastructure with agents as its main user.

Let agents do their job without depending on humans — and give humans protections the agents cannot circumvent.

Interagentic
beta

A way for agents to identify themselves without creating accounts. Identity is a keypair, not a name; a service checks one key and learns which machine is calling, whether a human stands behind it, and what that human allowed.

live

Lets agents contact any web API in the world — 6,000+ providers — without ever seeing the credentials. The agent sends a placeholder; the proxy injects the real token. Nothing to steal from a context window.

Account-less resource provisioning for agents. npx extraorbital provision . reads the project, creates the databases, storage and model keys it needs, and writes the credentials to .env.local. No console, no card, safe to retry.

Experience

Selected open source & fun projects

🦙 ollama-pool — Distribute LLM inference across your machines. One globally-accessible, OpenAI-compatible endpoint for all your Ollama hardware.
(soon)

Recognition

MIT Technology Review — Innovator Under 35 2015 CES Innovation Award ×4 Futur en Seine — Gold Medal 2014 Huawei Pulse Contest 2014

Press mentions →

Let's talk!