We’re in a strange moment in AI right now where everyone seems to agree agents are important… but almost nobody agrees on what production-ready agent systems should actually look like yet.
That’s what made this roundtable session so interesting for my co-host, Ali Abidi, and me.
We spent an hour digging into these questions with three people who’ve helped shape how the industry thinks about AI engineering: Chip Huyen, Paul Iusztin, and Maxime Labonne.
Chip Huyen brought the systems-level perspective she’s become known for through Designing Machine Learning Systems and AI Engineering: why reliability, orchestration, tooling, memory, evaluation, and infrastructure choices are quickly becoming more important than flashy demos.
Paul Iusztin and Maxime Labonne, co-authors of LLM Engineer’s Handbook, brought deeply practical perspectives from the frontlines of modern AI engineering, especially around modular architectures, production workflows, multimodal systems, post-training, fine-tuning, and the engineering discipline needed to move beyond PoC purgatory and into systems that can actually survive real-world use.
The conversation stayed honest throughout. Nobody pretended this space is “solved.” The discussions revolved around trade-offs, failure points, bottlenecks, orchestration chaos, and the messy engineering layer that starts appearing the moment agents interact with real systems and real users.
Huge thanks again to Chip, Paul, and Maxime for such a thoughtful conversation. Ali and I had an absolute blast hosting this one.
Thanks for reading!
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