Build a code-first AI agent eval harness in 2026 that scores task completion, tool selection, cost, latency, safety, and determinism — with CI gates and a 30-payload safety corpus.
MCP vs A2A in 2026: learn what each AI agent layer does, where AGENTS.md fits, and how to design agent systems without protocol confusion.
Stop AI-generated code from reaching production unchecked. A practical framework for detection, policy-as-code, sandboxed execution, and risk-tiered review gates.
Learn how to build production-grade MCP servers that connect AI agents to your internal databases, APIs, and tools with proper security, validation, and deployment.
Learn how AI coding agents work in 2026, why MCP matters, and how GitHub Agent HQ and Xcode are changing modern software development.
Step-by-step TypeScript tutorial to build an AI agent eval harness with CI gating. Score task completion, tool selection, cost, latency, safety, and determinism end-to-end.
Learn how to lock down AI coding agent pipelines with detection, policy-as-code, security scanning, sandboxed test execution, risk-tiered review gates, and audit logging.
Step-by-step tutorial to build an MCP server beyond hello-world with PostgreSQL, authentication, query sandboxing, and Docker deployment.
Learn how to set up MCP-powered coding agents in GitHub Copilot and Xcode, connect tools, run real tasks, and review output safely.
Learn how to extend GitHub Copilot coding agent with MCP tools, connect external context, validate tool use, and keep permissions safe.