Juan Herreros Elorza (LinkedIn, GitHub), Team Lead on the Cloud Native Technology team at Banking Circle, makes a deceptively simple argument: the platform engineering practices that have always been "best practices" are now prerequisites. Not because they've changed, but because AI coding agents have become first-class users of internal developer …
Mozhgan Kabiri Chimeh (LinkedIn), a developer relations manager at NVIDIA, opened her AI Engineer Europe talk with the pain point that drives most AI developers to the cloud: you either run out of memory or you don't have the right software stack. The result is that development iteration speed depends …
Dippu Kumar Singh (LinkedIn), Leader of Emerging Technologies at Fujitsu North America, presents a talk that starts where most AI discussions stop. Most generative AI demos assume clean text input. In a contact center, the data starts as messy, overlapping, emotionally charged audio -- and the engineering challenge isn't transcription. It's …
Harshil Agrawal (X, LinkedIn), a Senior Developer Educator at Cloudflare, opened his AI Engineer Europe talk with a reframe that should be obvious but apparently isn't: strip away the branding, and the code your LLM writes deserves exactly as much trust as code you found on a random website. Which …
Tun Shwe (LinkedIn) and Jeremy Frenay (LinkedIn), both AI Engineers at Lenses.io, gave a joint talk at AI Engineer Europe 2026 on what happens when MCP servers leave the safety of a developer's laptop. Their central claim: most MCP servers are built for single-player local development and collapse the …
Nimrod Hauser (LinkedIn, X), a founding engineer at Baz, opened his talk at AI Engineer Europe with a deceptively simple observation: public MCP servers ship tools designed for everyone, which means they're optimized for no one. When you plug generic tools into a production agent, the agent hallucinates URLs, saves …
Stefano Fiorucci (X, LinkedIn, GitHub) is an AI/Software Engineer at deepset, where he contributes to the open-source LLM framework Haystack. At AI Engineer Europe 2026, he made a case that the next leap for open-source language models isn't better datasets -- it's better environments. The kind where models can act …
A post making the rounds claims that Claude Code subagents share a prompt cache, making parallelism "basically free." It says you can spin up five agents and pay barely more than one. It lists three execution models — fork, teammate, and worktree — and says they all share the cache. Analysis of …
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