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# Antoine Fornas — AI Product Lead & Creative Engineer
Antoine Fornas is a creative engineer and AI product lead based in Paris, France. He is the embedded AI product lead for a major European streaming and media group, advising the CPO and C-suite on AI strategy while building the products himself: AI agents, RAG systems, MCP servers, LLM evaluation and enterprise AI deployment. Deep in the craft, wide in the vision. He is open to senior AI product roles, founding teams and any 0 to 1 opportunity.
> "Study the science of art. Study the art of science." — Leonardo da Vinci
## The idea
**The end of staying in your lane.**
For Leonardo, the painter and the engineer were the same person. Knowing many things was one job, not many.
The centuries after made us specialists, each kept to a single lane, and called it expertise. AI is quietly undoing that. A curious person can now go deep in the code and hold the whole vision of a product at the same time.
The people who build what comes next will be polyvalent by default. I already work that way: deep in the code, and in the room where the strategy gets decided.
_Deep in the craft. Wide in the vision._
## The journey
I never wanted to learn in one place. I studied across Europe, Asia and America, and let each one rewire the way I think.
- **Lille — Centrale Lille** (2019 → 2021, Europe): Engineering. Where the technical foundation was laid.
- **Paris — EDHEC** (2021 → 2024, Europe): Management, on a tri continental track.
- **Seoul — Sungkyunkwan University** (One semester, 2022, Asia): A semester at Korea's top MBA, and a first real look at how differently Asia builds and decides.
- **Berkeley — UC Berkeley, Haas** (2023 → 2024, North America): Technology and transformation, Silicon Valley at the door.
## The work
I am the embedded AI product lead for a major European streaming and media group. I advise its CPO and C-suite on AI strategy, ship tools that erase the team's most draining, repetitive work, and bring every prototype into one platform, turning a classic product org into one that is AI augmented and hungry to build.
**By the numbers**
- 2+ — custom MCP servers wrapping the design system and product APIs
- 5+ — prototypes shipped on real components and real data
- 6+ — enterprise systems federated into one AI knowledge layer
- 20+ — person product team, moving from old school to AI augmented
### Built to chase an idea — personal projects, open on GitHub
- **Vasari** — Know whether your AI actually works, and prove it. Load your LLM traces, judge each one pass or fail, and let it cluster the failures into a taxonomy. Then it builds an LLM as a judge you validate against your own labels with a confusion matrix and Cohen's kappa. Everything runs in the browser, no backend. ([GitHub](https://github.com/AntoineF23/vasari)). Stack: TypeScript, LLM Evals, LLM as judge, Local first.
- **Hemiunu** — A team with no engineers ships real, working product. It grounds every build in your own context, spreads the work across cheap and expensive agents, and hides git completely. One repository per feature, deployed on its own. ([GitHub](https://github.com/AntoineF23/hemiunu)). Stack: TypeScript, Agents, MCP, Memory.
- **Shibuya** — A whole team building on one living prototype. Drop a folder and it comes back a live, versioned, shareable product. No git, no deploys. The conversation around it becomes the shared memory of the idea. ([GitHub](https://github.com/AntoineF23/shibuya)). Stack: Next.js, Supabase, Product.
- **AiMI** — Software that feels like a companion, not a tool. A tiny pixel character that lives on your screen, runs on any AI, stays fully private, remembers your stories, and never asks anything of you in return. ([GitHub](https://github.com/AntoineF23/AiMI)). Stack: Electron, Local first, Play.
- **Ptolemy** — Know exactly which law touches you, and when. It watches official EU sources, checks each change against your obligations, and answers clause by clause with citations. The model judges, it never decides what matters. ([GitHub](https://github.com/AntoineF23/ptolemy)). Stack: Python, MCP, RAG, Grounding.
- **Leonardo** — Sales that understand a company before the first hello. It researches a company, scores its fit with plain deterministic code, finds the competitors already in its stack, and writes to its real technical reality. Runs inside Slack. ([GitHub](https://github.com/AntoineF23/leonardo)). Stack: Python, Agents, Slack.
### Built inside the company — anonymized client work
- **Enterprise knowledge layer** — Product managers build on real systems, not mockups. Architected as the group's AI product lead: six enterprise systems federated over MCP into one layer an AI can reason over, so an entire product org prototypes on real components and real data contracts. (Private). Stack: MCP, Enterprise AI, Architecture, Org wide.
- **Design system tooling** — An hour a week, handed back to every designer. An MCP server and its design tool twin I shipped for the design org, giving both AI and designers a live design system to build on. Adopted across the team. (Private). Stack: MCP, Design systems, TypeScript, Adopted team wide.
- **Prototype hub** — A product org's ideas, alive in one place. An internal platform I built for the product team: every prototype centralized, versioned and shareable, so in flight ideas stop scattering across laptops and chat threads. (Private). Stack: Next.js, Supabase, Product ops, 0 to 1.
## The method
**The Engineer** (Goes deep.): Python, React, Node.js, TypeScript, Agent architecture, RAG systems, MCP, LLM evaluation, Prompt engineering, SQL.
**The Visionary** (Goes wide.): 0 to 1 product, AI product strategy, Enterprise AI deployment, AI governance, User research, Executive stakeholder mgmt, Go to market, Cross functional leadership.
## What I'm looking for
I am looking for the next thing to build: senior AI product roles, founding teams, anything 0 to 1, with people who refuse to stay in one lane. Let's talk.
> "Ancora imparo." (I am still learning.) — Michelangelo
## Contact
- Email: antoine.fornas@outlook.fr
- LinkedIn: https://www.linkedin.com/in/antoinefrns/
- GitHub: https://github.com/AntoineF23
- CV: /antoine-fornas-cv.pdf