PyCon DE & PyData 2026

One of the hardest parts of applied NLP has always been breaking down complex business problems into machine learning components. It's so hard because it requires domain expertise and reasoning about the specific use case, and it's the one thing technology couldn't fix. But what if we could take some of the learnings from AI-powered coding assistants and apply them to solving real-world NLP problems? In this talk, I'll show how we've built powerful assistants and tools to help developers solve NLP tasks using open-source software, and create modular solutions that are small, fast and fully data-private.

At the core of it is an often overlooked idea: using LLMs to build systems instead of as systems. AI-powered coding assistants have transformed the way we build software – and they can be even more impactful for AI development itself and bridge the experience gap that's often holding teams back and causing projects to fail. In the talk, I will show you a new way of using generative models for AI development, and some practical examples of how to make "Vibe NLP" work for real-world problems