Simon Bruno

Simon Bruno

simonbruno[at]proton[dot]me

Working on multi-agent RL and interpretability. Building voice agents at Stellar.

Researcher &  Founder

TL;DR

Now
building voice agents at Stellar and doing my AI master's at UvA, focused on multi-agent RL and interpretability.

Before that
co-founded Omen, was a Founder in Residence at Antler, did AI R&D at Bit, a former professional League of Legends player (top 400 in Europe), and the founder of a web development agency since age 15.


I spend most of my time thinking about how agents learn to cooperate (and when they don't). Multi-agent RL, social dilemmas, setups where individually rational agents end up in collectively terrible outcomes. Recently been reading Agents of Chaos, where autonomous LLM agents with real tools started spoofing identities, propagating unsafe behaviors across agents, and lying about task completion. If agents with basic tools already break down like this, we're nowhere near ready for real autonomous multi-agent systems.

On the interpretability side, I care about the mechanistic approach. Not just measuring outputs, but tracing the actual computation: what are the circuits, what do the features represent, and can we reverse-engineer how a model arrives at a decision? We're early, but the progress in the last two years has been real.

Recent Blog Posts

Writing about AI, engineering, and things I've been working on.

Work Experience

December 2025 -
Present
Software Engineer

Building AI-powered voice agents for telephone customer service. Developing intelligent conversational systems that handle real-time customer interactions at scale.

July 2025 -
December 2025
Co-Founder

Redefining eCommerce growth by turning every visitor into a customer. Built and scaled growth technology for online retailers.

September 2025 -
November 2025
Founder in Residence

Chosen as one of the top 100 founders in Europe, I joined the first ever Antler One residency. It is the continent's most exclusive early-stage accelerator.

March 2025 -
September 2025
AI Engineer - Prototyping & Research

As an AI Developer at Bit, I apply cutting-edge AI technologies such as graph neural networks, OCR models, and large language models to bridge research and real-world needs through hands-on client-driven innovation.

July 2022 -
November 2023
Full-stack Developer

As the first engineer hire at Equip, I collaborated closely with the CTO to develop the initial versions and further iterations of both front- and back-end of the user-platform.

October 2018 -
October 2023
Simon Bruno Webdevelopment
Full-stack Developer & Founder

At age 15, I launched my own web development agency, building websites for organizations like Eurekaweek, used by thousands of students in Rotterdam, and EAGEN, a European patient advocacy group, focused on scalable event systems and integrated payments.

October 2018 -
July 2022
Dynasty / Team THRLL (PEC Zwolle)
Professional eSporter - League of Legends

Held a paid position at age 15 competing at the highest level of Benelux esports for Dynasty and Team THRLL (PEC Zwolle), ranked in the top 400 out of 20+ million League of Legends players across Europe.

Education

Universiteit van Amsterdam
Master's degree, Artificial Intelligence
November 2025 - September 2027
Universiteit van Amsterdam
Bachelor's degree, Computing Science / Informatica
September 2022 - July 2025
Universiteit van Amsterdam
Bachelor's degree, Business Administration
August 2020 - July 2024
NTNU (Norway)
Exchange Program, Engineering & Computing Science
August 2024 - December 2024
Camphusianum
VWO/Gymnasium, Economie
2014 - 2020

What Drives Me

Intelligence evolved in steps: steering, reinforcing, simulating, mentalizing, speaking. The basal ganglia runs an actor-critic architecture, the same framework we use in modern RL. There's something fascinating about how the edge of evolution and chaos leads to creation, and that biology arrived at the same solutions we're now building independently.

Social dilemmas in multi-agent environments need more attention, especially now that agents are general pretrained models rather than task-specific policies. Reward shaping gets unclear fast when agents can generalize beyond what you designed for. These are the problems I want to work on.

Simon at Antler

Technical Expertise

Core Skills
AI & Machine Learning
Reinforcement Learning Interpretability LLMs NLP Voice AI PyTorch JAX
Software Development
React Node.js Next.js Git Docker
Business & Strategy
Startup Strategy eCommerce Product Development System Design
Languages
TypeScript 95%
Python 90%
JAX 70%
C 60%
SQL 55%

Mostly AI research, startups, and whatever I'm currently stuck on. Feel free to reach out.