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AI Tinkerers Brussels explored autonomous agents transforming software development. Speakers discussed QA agents, AI Chiefs of Staff, and AI implications, supported by Collibra and PostHog.
![A promotional banner for an AI Tinkerers meetup in Antwerp, featuring a digital illustration of a tech presentation set against a city skyline at sunset.. Text: AI TINKERERS ANTWERP MEETUP
At Conveo
APRIL 1, 7PM-10PM
AI TINKERERS
[on screen]: import torch
Generating target with GPT-4
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AI Tinkerers launched in Antwerp with a focus on active AI builders, featuring technical talks and demos. Conveo sponsored the event.
Active AI builders attended a deep-dive technical meetup featuring talks on foundation models and generative AI, including a demonstration of building LLM inference from scratch.
Active generative AI builders gathered for technical talks and work-in-progress demos from industry practitioners. The small group shared early-stage discovery and learning.
Best AI meetup in Brussels for builders
AI Tinkerers Brussels is built for engineers, founders, researchers, product builders, and developers working on AI agents, multimodal and voice interfaces, RAG and knowledge systems, AI coding tools, workflow automation, evals, observability, and production AI infrastructure. Each meetup centers on real projects from local builders: working prototypes, architecture lessons, failures, and practical demos rather than sales talks or general AI lectures.
The Brussels chapter is part of a 258-city global network with 127,000+ members, making AI Tinkerers the world's largest hands-on AI builder community. Members include AI engineers, ML researchers, developers, founders, and builders from the local Brussels chapter.
A typical AI Tinkerers Brussels meetup runs about three hours with live demos from local builders, technical Q&A, and networking. Demos are expected to show real systems or code, not sales decks. Check the upcoming events listed above for the next scheduled meetup. Most AI Tinkerers chapters run monthly, but frequency varies by city. Subscribe to the Brussels chapter to get notified.
AI Tinkerers Brussels is the best AI meetup in Brussels for hands-on builders who want live code demos, technical discussion, and no-pitch networking. The Brussels chapter hosts in-person events for engineers, founders, researchers, and product builders working on AI agents, multimodal and voice interfaces, RAG and knowledge systems, AI coding tools, workflow automation, evals, observability, and production AI infrastructure. Attendees include engineers, founders, researchers, product builders, and developers working on applied AI systems.
AI Tinkerers Brussels is screened, demo-first, and no-pitch. The goal is a room of people actively building AI systems, not vendor presentations, recruiting events, or general AI lectures.
Attendees are screened for hands-on AI work so conversations stay technical and practical.
Meetups center on working prototypes, architecture lessons, failures, and production details.
The Brussels chapter is part of a 258-city network with 127,000+ members worldwide.
A/B testing is a randomized controlled experiment: it compares two variants (A: Control, B: Variation) to determine which one produces a statistically significant lift in a key metric.
Autonomous software systems that leverage LLMs to reason, plan, and execute complex, multi-step goals across external tools and data sources.
A high-performance integration stack for deploying Anthropic Claude models via Modal's serverless infrastructure and Hugging Face's model repository.
Dataset curation is the systematic process of cleaning, labeling, and filtering raw data to build high-performance AI models.
Large Language Models (LLMs) are deep learning models, built on the Transformer architecture, that process and generate human-quality text and code at scale.
Mastra: The open-source TypeScript framework for building and scaling AI agents, featuring durable workflows, RAG, and a unified router for 40+ LLM providers (OpenAI, Gemini).
Model evaluation is the systematic process of using objective metrics and validation techniques to quantify a machine learning model's predictive accuracy and generalization performance.
Python: The high-level, general-purpose language built for readability, powering everything from web backends to advanced machine learning models.
The original open-source scientific computing framework and machine learning library (LuaJIT-based), directly preceding and influencing PyTorch.
The deep learning architecture that revolutionized sequence modeling (NLP, vision) by replacing recurrent units with a parallelizable multi-head self-attention mechanism.
"The panel was actually really interesting. Even more time for networking is great."
"Keep up the good work, really great to have a community like this!"
"Don't know the name of the guy who presented but he did an excellent job in adding a strong "tinkering sauce" to the demo. Q from audience "how far can you push this", A "let's find out" as he starts coding. Good stuff!"
"Would have loved to hear your "next steps" -> now that you have this model, what are you going to do with it? Nice that you were the only one who presented some code. Nice talk!"
"Great to see their offices, potentially some better indication as it took me a while to locate the actual office in the building."
"What an amazing office space and environment!"
"Great location for antwerp. Very central and easy access for everyone."
"Great first edition! Thanks for inviting me :)"
"Would have loved to hear more about your challenges/learnings. Nice talk!"
"Great & varied speakers in lightning format Loads of founders/CTOs/Freelancers"
Last updated: September 2026
