Philipp Schmid

Don't Ship Skills Without Evals — Philipp Schmid, Google DeepMind

Jul 14, 2026 · 21:46

Philipp Schmid, Staff Engineer at Google DeepMind, argues that shipping agent skills without evals is like merging code without tests, leading to unreliable performance. He explains that most of the 50,000+ skills on Skill Bench lack evals and are often AI-generated, which can negatively impact performance. The talk distinguishes between capability skills (teaching models new tasks) and preference skills (encoding team-specific workflows), with evals enabling retirement of skills as models improve. Schmid shares practical advice: keep skill descriptions concise (under 500 lines), include negative tests, and write directives over passive information. He details a case study creating 117 test cases for the Gemini interactions API, achieving 90% valid code generation using regex-based asserts and LLM-as-judge. The key takeaway: always run ablation tests with and without skills to measure their true impact, and start small with as few as 10-20 eval samples.

Why (Senior) Engineers Struggle to Build AI Agents — Philipp Schmid, Google DeepMind

May 30, 2026 · 10:40

Philipp Schmid from Google DeepMind argues that senior engineers struggle to build AI agents because they carry years of implicit context that agents don't, designing tools that assume it. He highlights five key shifts: text replaces structured state, so agents can handle semantic meaning like approving a research plan with additional input; errors are inputs, not restart triggers, since long-running agents (5-15 minutes) can't afford to start over; evals replace unit tests because agents are non-deterministic and success is measured by how often it works, not fixed outputs; and agents evolve while APIs don't, so tools like a `deleteItem` endpoint need agent-friendly docstrings because the agent only sees the schema. He advises to hand over control to the LLM, design for recovery, and build to delete since models improve rapidly.

Building Conversational Agents — Thor Schaeff and Philipp Schmid, Google DeepMind

Apr 30, 2026 · 1:47:34

Thor Schaeff and Philipp Schmid of Google DeepMind demonstrate building conversational agents with the Gemini Interactions API and Live API, arguing that the new Interactions API simplifies agent development by introducing server-side state management, unified content blocks, and remote MCP support. They walk through creating a coding agent with read/write file and bash tools using Gemini 3 Flash, highlighting how the model uses tool calling to execute commands and return results. The Live API, powering real-time voice and video interactions, supports native multilingual audio, tool calling, and Google Search grounding, though the presenters acknowledge its current limitations in production, including lack of session transcript retrieval and shorter context windows (15 minutes audio-only). They showcase a Live Jukebox demo integrating Lyria 3 music generation and discuss business use cases like Shopify Sidekick, Waymo, and elderly companion apps, emphasizing that while the technology is ready for experimentation, production readiness depends on partner integrations for observability and compliance.

AI Engineering with the Google Gemini 2.5 Model Family - Philipp Schmid, Google DeepMind

Jul 11, 2025 · 1:44:51

In this workshop, Philipp Schmid from Google DeepMind demonstrates AI Engineering with the Gemini 2.5 model family, focusing on using Gemini 2.5 Flash via a free API tier for hands-on coding tasks including text generation, multimodal processing of images, audio, and PDFs, function calling with structured outputs, and integration with MCP servers. The session covers setting up API keys in AI Studio, uploading files via the Files API (free for 1 day), and controlling thinking budgets (0–24,000 tokens) to manage cost and reasoning depth. Schmid shows how Gemini natively processes videos at 1 frame per second for accurate timestamp extraction and how PDFs are handled by combining OCR text with image understanding. He introduces native tools like Google Search with grounding metadata, code execution, and URL context, and explains how MCP servers can be used seamlessly with the Gemini SDK for tool calling. The workshop also covers parallel vs sequential function calling, the Agent Development Kit (ADK), and the upcoming asynchronous function calling for the Live API, providing a practical path from simple generation to agentic workflows.