Simplify Entra POC Setup with Entra-POCAdvisor

From Microsoft Community Hub, Supercharge Your Dev Workflows with GitHub Copilot Custom Skills, by sachoudhury "The Problem Every team has those repetitive, multi-step workflows that eat up time: Running a sequence of CLI commands, parsing output, and..." https://lnkd.in/e_rtQdBQ

The Azure Office of the CTO Incubations team recently used GitHub Copilot in a way that I think many engineering teams will find useful: identifying and fixing discrepancies between code and documentation and ensuring that tutorial documentation is complete and accurate. The team behind Drasi, our open-source data change processing platform, faced a common challenge. As features evolve rapidly, documentation can easily fall out of sync. By leveraging GitHub Copilot’s ability to reason across both source code and markdown files, they were able to automate the discovery of these documentation bugs. It’s a great example of using AI not just to write new code, but to maintain the integrity and clarity of an entire project. You can read the full breakdown of their workflow and the results on the Microsoft Open Source blog: https://lnkd.in/gXx33VXh

This is really great, documentation is key to everything and if we can find the gaps and bugs as we all rapidly make changes, improvements and add new features, it ensures we have greatly and up to date documentation.

Great use of AI to solve a everyday issue with keeping everything in sync between code and documentation. How many times have inherited code and the documentation is several versions behind?

🚀 From Zero to AI-Driven Dataverse Development in 15 Minutes Remember when setting up a new Power Platform dev environment meant hours of CLI commands, authentication headaches, and reading through endless documentation? Those days are over. I just published a complete guide to installing and configuring Microsoft Dataverse Skills for GitHub Copilot and Claude Code. This isn't theory—it's a production-grade walkthrough that accounts for real enterprise constraints. What you'll learn: ✅ PAC CLI authentication patterns that actually work in enterprise environments ✅ Enabling the Dataverse MCP server in Managed Environments (and why that matters) ✅ Installing the plugin in both GitHub Copilot and Claude Code ✅ Building your first complete Dataverse solution from a single natural language prompt ✅ Troubleshooting the 5 most common setup errors (so you don't have to) The payoff? By the end of the tutorial, you'll have an AI agent build an entire project tracking system—tables, columns, relationships, security roles, and sample data—from one sentence of intent. No manual schema design. No portal clicking. No script debugging. This is Part 2 of my Dataverse Skills series. If you're a Power Platform developer or solution architect exploring AI-assisted development, this is your practical starting point. 📖 Read the full guide:  https://lnkd.in/dKTYYe2Z What's your biggest pain point when setting up new Power Platform environments? Drop a comment—I'd love to hear what slows you down. Microsoft Power Platform Community Power Platform Weekly Power Platform Dev Weekly #PowerPlatform #MicrosoftDataverse #GitHubCopilot #AICoding #DevelopersLife #LowCode #EnterpriseDevelopment #PowerPlatformCLI #DevTools #CodingAgents

GitHub Copilot's discount pricing era is ending. Microsoft is moving ALL subscribers to token-based billing in June 2026. The pricing math is a real shift for heavy users. New structure: ↳ Business: $19/user/month + $30 pooled AI credits ↳ Enterprise: $39/user/month + $70 credits ↳ Then pay-per-token after that Old pricing was roughly 2x-5x cheaper than raw token costs. This isn't a small tweak. April 2026 was the warning shot: new Pro/Pro+ sign-ups paused, tighter rate limits, Claude Opus pulled from lower tiers. AI compute costs have nearly doubled weekly since January. GitHub had to act. So what should you actually do? If you're a heavy Claude user, skip Copilot for that. Claude Max (5x or 20x plans) is better value. If you're primarily on OpenAI or Gemini models, a direct plan with those providers is now more cost effective than routing through Copilot. Corporate teams already on Business/Enterprise feel this less. You had pooled usage anyway. Copilot still wins on multi-model access and IDE integration. But discounted "premium request" pricing is done. I evaluate these tools constantly. My honest take: know your model usage before June, then route your spend accordingly. The free lunch is over. Budget accordingly.

Microsoft just quietly shipped something that tells you more about the future of enterprise software than any keynote announcement. They published a Claude Code plugin, filed under their own GitHub org, that lets you build, test, and troubleshoot Microsoft Copilot Studio agents as YAML. From your terminal. With a slash command. Microsoft owns GitHub. They own Copilot. They could have made this VS Code-only, locked to Copilot subscriptions, guarded behind Azure SSO. Instead: open source, MIT license, explicitly compatible with Anthropic’s Claude Code, ships under `microsoft/`. Every major enterprise platform is converging on agents-as-code: 🔷 Salesforce: Agentforce agents as metadata, deployable via SFDX 🟠 AWS: Bedrock Agents as CloudFormation templates 🔵 Google: Vertex AI Agents as YAML 🟢 Microsoft: Copilot Studio agents as YAML + this CLI ⬛ ServiceNow: AI Agent Studio as declarative JSON The “low-code wizard” works for the first 10 agents. For the 50th agent, you need: - Version control (which click broke production?) - Code review (who gave that agent access to all customer PII?) - Testing (does this still work after the knowledge base update?) - Promotion workflows (dev → staging → prod) - Batch updates (47 agents all need the same security patch) Low-code gives you zero of that. YAML-in-Git gives you all of it. The detail that makes this actually usable: schema validation. The Copilot Studio YAML format changes. An agent that generates YAML against an outdated schema fails silently when you push. The plugin validates before you waste time debugging. That’s the difference between “plausible demo” and “actually useful in production.” Your agent count is about to go up by 10x. The teams that figure out governance, versioning, and testing now won’t be drowning when it happens. The teams that don’t will be. 🔗 Full article: https://lnkd.in/dfys9yFq Enterprise integration leads: are your automation workflows in version control? Or are they living in a wizard that nobody fully understands anymore? #MicrosoftCopilot #CopilotStudio #EnterpriseSoftware #AgentsAsCode #LowCode #AIIntegration #EnterpriseAI

Microsoft has temporarily suspended new GitHub Copilot account sign-ups amid a capacity crunch. -Key reason: overwhelming demand and abuse have pushed operational limits. -Copilot is a major AI tool empowering developers worldwide. -Microsoft plans to shift to token-based billing for better usage management. How will this pause affect the developer community and AI coding adoption? 🚀🤔

GitHub Microsoft Copilot is now restricting signups and resources on all plans, mostly because of long-running parallel computing initiated by stuff like OpenClaw and Geoffrey Huntley's very useful RalphWiggins-style development processes. They're just the latest in a long conga line of similar companies doing the same things. The austerity ahead of us is going to cripple or destroy dev shops and business models that bet the farm on essentially unlimited AI access. We've progressed so far with AI that we've gone back in time to the mainframe timeshare computing model. It was fun while it lasted! https://lnkd.in/e_aBJZv7 #AI #Development #GitHub #Copilot #Microsoft

Not all Copilots are the same—and confusing them could cost you productivity and the right AI support for your work. GitHub Copilot and Microsoft Copilot may share a name, but they serve very different purposes. GitHub Copilot is designed primarily for developers. It acts as an AI pair programmer inside code editors, helping with code suggestions, debugging, and faster development workflows. It’s deeply integrated into software development environments and focuses on writing and improving code efficiently. On the other hand, Microsoft Copilot is built for broader productivity. It works across tools like Word, Excel, PowerPoint, and Windows, helping users with writing, data analysis, presentations, and everyday office tasks. Instead of focusing only on coding, it supports general work and business productivity across the Microsoft ecosystem. Understanding this difference can completely change how you choose and use these tools in your workflow. But there are deeper distinctions in features, integration, and real-world use cases that are worth exploring. Read the full breakdown here to get a clearer picture: https://lnkd.in/gRK_RET3⁠�