PyCon DE & PyData 2026

Life sciences compliance isn't forgiving. When your software helps companies navigate FDA regulations, ISO 13485, and EU MDR, "move fast and break things" isn't an option. Audit trails matter. Documentation is mandatory. Getting it wrong means regulatory findings, delayed product launches, or worse — patient safety risks.

During the development of our AI Assistant we made every mistake in the most unforgiving environment possible. After more than a year building with PydanticAI, pydantic-evals, and Claude — nearly 3,000 commits and 20+ contributors — here are 7 anti-lessons so you don't have to repeat them:

1. "We need a multi-agent system" — We built one. Then deleted it.
2. "Agents need sophisticated planning" — A todo list beat our workflow engine.
3. "Give the agent lots of specific tools" — Two high-level tools replaced dozens.
4. "Encode workflows in code" — Markdown files the agent reads at runtime won.
5. "It works when I test it" — Simple tests ≠ real user journeys. Realistic evals or you're blind.
6. "Automate everything" — Human stays in the driver's seat, not the trunk.
7. "Apply what made you successful before" — Your engineering instincts might hurt you here.

Real code, real git commits, real mistakes from a domain where mistakes are expensive.

Come for the mistakes. Leave with shortcuts.