Strange Loop, Berlin. On why every interesting AI product is built on deeply boring infrastructure, and why the frameworks that try to hide it are lying to you.
Saying it out loud.
Conference talks, keynotes, and the occasional podcast episode — mostly about conversational AI, shipping ML in production, and why enterprise software is more interesting than it looks.
Boring infrastructure for un-boring products.
A keynote arguing that the most interesting AI products in 2026 sit on top of the least interesting infrastructure imaginable — and that this is not an accident. Covers queues, retries, schema contracts, and why every "agent framework" eventually becomes a worse version of Kubernetes.
AI Engineer Summit, San Francisco. What a decade of watching people ship chatbots has taught me about where they break.
OSS Europe, Bilbao. The quiet truth that most open-source adoption in the enterprise is driven by procurement, not by engineers.
AI.Engineer workshop. A hands-on session on building eval pipelines that survive quarterly model updates.
NLP Summit panel on the shift from classifier-based dialog systems to LLM-native ones — with some pushback.
QCon San Francisco. The four most common ways LLM products quietly stop working in production, and what to do before they do.
AI Engineer World's Fair. A polemic on finetuning's place in the modern stack — specifically, further down than you think.
DevNexus Atlanta. Why the architectural idea we called "dialog management" in 2017 is quietly being rebuilt as "agent orchestration" in 2024.
Web Summit. Ten years of conversational AI, told as a story about three wrong turns and two correct ones.
EMNLP industry track. Why the benchmarks we had were actively misleading us about what users experienced.
PyData Berlin. The talk that eventually became Rasa Open Source 2.0 — and my first public attempt at explaining what we were building.
Speak at your thing?
I'm selectively available in 2026 for keynotes, workshops, and occasional podcast episodes. Probably a yes if you're a conference about practical ML, an engineering org running an internal event, or a podcast with a guest list I admire.