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Microsoft MDASH multi-model agentic scanning harness — AI-powered vulnerability discovery finds 16 Windows CVEs including 4 Critical RCEs in a single Patch Tuesday cycle
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Microsoft’s AI Found 16 Windows CVEs — Including 4 Critical RCEs. Here’s How the Agentic Pipeline Actually Works

Microsoft's MDASH agentic scanning harness found 16 CVEs in the Windows networking stack — including 4 Critical RCEs affecting tcpip.sys, IKEv2, DNS, and Netlogon. As a Power Platform Solution Architect, this is the infrastructure your solutions sit on. This post explains how the pipeline works, what the architectural lessons are, and how to use this in client governance and security conversations.

Dataverse MCP server — 15 named tools giving AI agents grounded, auditable access to Power Platform data
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Dataverse MCP Server: The 15 Tools That Make Power Platform Agent-Ready

Microsoft formalized the Dataverse MCP server tool shape in June 2026 — 15 named tools that give any MCP-compatible agent grounded, auditable access to your Power Platform environment. This analysis covers the full tool surface organized by risk tier, how to configure clients in VS Code and Copilot Studio, the billing model, and a dedicated security and governance breakdown: Entra ID auth, RBAC, client allowlisting, audit gaps, prompt injection risks, and the delete-override danger in the sample agent instructions.

GitHub Copilot Plan agent in Visual Studio — structured AI-assisted development with a Markdown plan reviewed before code generation
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Think Before You Build: GitHub Copilot’s Plan Agent in Visual Studio — Structured AI-Assisted Development

GitHub Copilot's Plan agent, introduced in Visual Studio in May 2026, adds a deliberate planning phase before any code generation happens. Instead of watching AI modify files in unpredictable directions, you review and approve a detailed Markdown plan grounded in your actual codebase — before a single file changes. This guide covers how the Plan agent works step by step, how to write prompts that produce genuinely useful plans, and how to apply it to a real Dataverse plugin refactoring scenario with working before-and-after code examples.

Entire.io captures AI coding sessions as permanent checkpoints linked to Power Platform Git commits
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Entire.io for Power Platform Developers: Why AI Coding Sessions Need a System of Record

AI coding agents like Claude Code and GitHub Copilot generate Power Platform solutions at speed — but when the session ends, the reasoning behind every plugin stage, Client API pattern, and architecture decision disappears from the git history. Entire.io is a CLI-first system of record that captures those AI coding sessions as permanent, searchable records linked directly to your commits. This article explains why Power Platform developers need this more than most and how Entire fits into the full code-first development stack alongside microsoft/power-platform-skills and microsoft/Dataverse-skills.

VS Code vs Windsurf vs Cursor: The definitive 2026 AI coding editor comparison
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VS Code vs Windsurf vs Cursor: My Honest Take After 6 Months Using All Three

After spending hundreds of hours with all three editors, here's the bottom line: VS Code + Copilot is the reliable workhorse with unmatched ecosystem support. Windsurf + Cascade is the AI-native innovator with continuous context awareness. Cursor is the agentic middle ground with excellent tab completion and Composer mode. Each excels in different scenarios, and for Power Platform developers? The answer depends entirely on your workflow. Let me show you exactly how to choose.

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

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.

The Risk Decision Matrix for GitHub Copilot CLI Autopilot Mode in Power Platform
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The Risk Decision Matrix for GitHub Copilot CLI Autopilot Mode in Power Platform

GitHub Copilot CLI Autopilot mode reached GA in February 2026 — but for Power Platform, autonomous PAC CLI execution carries real risk. This article builds a scored Risk Decision Matrix mapping every PAC CLI operation to one of four zones: full Autopilot, conditional, Plan Mode only, or human-only. Includes a calculable Autopilot Safety Score formula, a ready-to-use AGENTS.md template, and preToolUse hook enforcement patterns grounded in Singapore IMDA, AWS, and McKinsey agentic governance frameworks.