A product discussed on AI Engineer.

Piloting agents in GitHub Copilot - Christopher Harrison, Microsoft
Jul 26, 2025 · 59:07
Christopher Harrison (Microsoft) demonstrates GitHub Copilot's agent capabilities for AI Engineers, arguing context is key to effective pair programming. He explains Copilot's modes—completion, chat, edit, local agent, and coding agent—and how Model Context Protocol (MCP) enables access to external tools like databases. Harrison shows how Copilot-instructions.md files provide project-specific guidance, and how coding agent runs within ephemeral GitHub Actions environments with strict security (no external access, only write to its own branch). He emphasizes that AI doesn't change DevOps fundamentals: tests still run locally and via PR workflows, and code review remains essential. The lab covers assigning issues to Copilot, configuring MCP servers, and using .instructions files for reusable patterns, with a repeat session at 3:30 PM.

Full Spec MCP: Hidden Capabilities of the MCP spec — Harald Kirschner, Microsoft/VSCode
Jul 18, 2025 · 14:53
Harald Kirschner from Microsoft/VSCode argues that MCP's full specification unlocks powerful stateful interactions beyond the common 'tools-only' implementations, transforming AI assistants into more contextual and efficient agents. He highlights underused primitives like resources for rich data context and sampling for server-requested LLM completions, demonstrated via a dungeon game where dynamic tool discovery adapts to game state. VS Code's upcoming full spec support includes dynamic tool discovery, user-defined tool sets, a debug mode for server development, and support for streamable HTTP to reduce stateful server churn. Upcoming features like elicitations will allow tools to request user input directly. Kirschner calls on developers to build progressive, full-spec servers and contribute feedback to the open ecosystem, emphasizing that client and SDK support will follow as usage grows.

The emerging skillset of wielding coding agents — Beyang Liu, Sourcegraph / Amp
Jun 30, 2025 · 35:06
Beyang Liu, CTO and co-founder of Sourcegraph, argues that coding agents are a real and high-ceiling skill, contrary to skeptics like Jonathan Blow and Eric S. Raymond. He presents design decisions for the agentic era: agents should directly edit files instead of asking permission, UIs should be minimal (like Amp's bare-bones VS Code extension and CLI), and fixed pricing should give way to usage-based models. In a live demo, Liu uses Amp to implement a custom icon for the linear connector in Amp's own codebase, demonstrating agentic search and sub-agents. He shares power-user patterns, including writing long prompts, constructing feedback loops with Playwright and Storybook, and running multiple agents in parallel—as exemplified by Jeff Huntley using Amp to build a compiler while sleeping. Liu emphasizes that agents should enable more thorough code reviews, not replace human understanding.
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