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 turn out 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. We’ll cover:

• How to expose your 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

We’ll also discuss 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.

Finally, we’ll challenge you to measure the real impact: Is your AI integration reducing friction or creating new problems? Are you deploying faster, recovering quicker, and shipping more value? Walk away with concrete practices and metrics to ensure your platform is ready for a future where agents are not just tools, but teammates.