Copilot Studio's GitHub Copilot harness organizes agent tools into three types: connectors, MCP servers, and workflows. Here's when to use each and how to set them up.

Skills make agent capabilities reusable and shareable; Memory gives agents per-user persistent context. Both are exclusive to the GitHub Copilot harness and change how you structure complex agents.

The GitHub Copilot harness replaces the classic node-based canvas with a four-tab authoring surface. Here's what each tab does and how to structure your agent configuration.

Microsoft's GitHub Copilot harness — now generally available in Copilot Studio — is a fundamentally different agent runtime built for complex multi-step work. Here's what changed and what it means.

Most organisations have an AI governance policy and no implementation — here's what governance looks like when it's actually running at the engineering team level.

The skills that were table stakes for senior engineers two years ago are depreciating fast — here's where to invest your learning time heading into 2027.

Voice-driven AI in engineering workflows isn't science fiction anymore — here are the patterns that actually work and the ones that don't.

Standard retro formats weren't designed for teams where AI tools write significant portions of the code — here's what to add and why it matters.

The fine-tuning vs. RAG debate has a different answer in 2026 — 200k+ context windows and widely available fine-tuning APIs have shifted where each approach makes sense.

The AI stack has a supply chain attack surface most teams aren't thinking about — here's what to audit and how to defend it.