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Work IQ APIs intelligence layer diagram showing M365 data flowing into a semantic context engine and out to AI agents
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Work IQ APIs: Microsoft’s New Intelligence Layer for Enterprise Agents Is Now Generally Available

June 15, 2026June 15, 2026AI & Copilot, Power Platformby

Work IQ is Microsoft's new intelligence layer for Microsoft 365, announced at Build 2026 and going generally available June 16, 2026. It gives agents — and the developers building them — a way to work with business context rather than raw data: 2x faster than traditional APIs, 80% fewer tokens, 10 MCP tools instead of hundreds, and full M365 tenant security. This post covers the architecture, the five core advantages, how to get started with the MCP server and CLI today, and what it means for Power Platform developers building on Dataverse and M365.

GitHub Agentic Workflows automating repository management and Power Platform development — AI agents handling issue triage, documentation, testing, and deployment
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GitHub Agentic Workflows: The Next Evolution of Repository Automation for Power Platform and Enterprise Developers

March 30, 2026June 17, 2026AI & Copilot, Claude, GitHub Copilot, Pcfby

Traditional GitHub Actions workflows are powerful but deterministic — they can only do what you explicitly tell them. GitHub Agentic Workflows change that. Launched in February 2026, they bring AI coding agents (Copilot CLI, Claude Code, Codex) into GitHub Actions with natural language specifications, security guardrails, and human review. Instead of writing imperative YAML, you describe outcomes in plain language and let AI agents figure out the implementation. This guide explores the six core automation categories and practical applications for Power Platform developers managing PCF controls, Dataverse solutions, and ALM pipelines.

agents.md best practices for GitHub Copilot specialist agents
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Stop Writing Vague AI Prompts: The Developer’s Playbook for Mastering agents.md in 2026

February 28, 2026February 28, 2026AI & Copilot, GitHub Copilotby

Your AI agent just modified the wrong file. Again. Before you blame the model — when did you last check what instructions you actually gave it?
Most developers hand a powerful coding agent a vague persona and wonder why results are inconsistent. GitHub's analysis of 2,500+ repositories reveals the uncomfortable truth: the gap between agents that work and agents that guess comes down to one file you're probably not writing correctly.
In this guide: the six pillars of a high-performing agents.md, a production-ready Dataverse plugin agent template, and the maintenance habit that keeps your AI sharp as your codebase grows. Your agent is only as good as the manual you write for it.