Platforms for humans and machines: Engineering for the age of AI agents

As AI coding agents become first-class users of internal developer platforms, the practices that make platforms accessible to humans are proving to be the same ones that enable AI to thrive. Self-service interfaces, well-defined APIs with schemas and documentation, local-first workflows, and rich observability have always been important elements of a good platform. Now they are prerequisites for agents that can autonomously build, debug, and ship software.

This talk explores what it means to design platforms where both humans and AI can collaborate effectively. It covers:
• How to expose a platform as a product with structured APIs and perhaps MCPs
• Why prioritizing local tooling pays dividends when agents need to iterate on errors
• How observability becomes the bridge between runtime behavior and AI understanding

It also discusses the flip side: AI is making it easier than ever to contribute to platform code, but that comes with new responsibilities around quality gates, context files like CLAUDE.md, and maintainability.