Silvia Rodenas Vaquero’s Post

🚀 What if your GitHub repo could improve itself? Join us for GitHub Agentic Workflows: Automation That Actually Reads the Room and see how AI agents can autonomously triage issues, fix CI failures, update docs, and improve tests—with just a markdown file and one command. 🔍 In this live demo, Ari LiVigni, Senior Learning Advocate at GitHub, will walk through: - From minimal workflow file → AI agent in action - Safe, sandboxed pipelines that deliver ready‑to‑review PRs - How to keep your repo on autopilot while staying fully in control 📅 May 7, 2026 ⏰ 9:00–10:00 AM PT 🎥 Live and on-demand at any time after wrap 👉 Register now: https://msft.it/6040QxqQE 📍 Explore the series: https://msft.it/6041QxqQ1 #MicrosoftReactor #learnconnectbuild #GitHubCopilot #AgenticWorkflows #AgentOrchestration #GHCP #Fleet

Good to see GitHub adding more transparency to their status page! The new 'Degraded Performance' state is smart – much better to distinguish between a glitch and a full outage. Also, publishing per-service uptime metrics and separating out Copilot AI model issues specifically is super helpful for us devs. It's the clarity we need when things aren't 100%. 🙌 #GitHub #DevTransparency

GitHub Copilot gets called an autocomplete tool. That undersells it significantly. Yes, it suggests code inline as you type. But the more interesting capability is what it does at the workspace level — it can read your entire codebase, answer questions about it, explain unfamiliar code, and act as an agent that spans multiple files. The numbers back up the adoption: 1.8M+ paid subscribers, integrations across every major IDE, and deep GitHub ecosystem access that no third-party coding agent can replicate natively. If you're evaluating AI coding tools, GitHub Copilot is the baseline everything else gets compared to. Full profile and alternatives → https://lnkd.in/ewkPwZeA

GitHub just changed the rules. And developers who push codes only from the terminal don’t even realize it yet. Starting April 24, GitHub will begin using Copilot interactions to train its AI models (except enterprise users). Yes… that includes: • your prompts • accepted / rejected code • how you edit suggestions • potentially context from your repos Even private ones indirectly. Dont worry it is easy to turn it off. 1. Go to GitHub Settings 2. Navigate to Copilot 3. Find “Allow GitHub to use my data for product improvements” 4. Turn it OFF That’s it. Are you someone who doesn’t care, or are you turning it off? Comment below. #AI #Github #DataPrivacy

"GitHub has announced that it will be shifting to a usage-based billing model for its GitHub Copilot AI service starting on June 1. The move is pitched as a way to 'better align pricing with actual usage' and a necessary step to keep Copilot financially sustainable amid surging demand for limited AI computing resources. GitHub Copilot subscribers currently receive an allocation of monthly 'requests' and 'premium requests,' which are spent whenever they ask Copilot for help from an AI model. But those broad categories cover many different AI tasks with a wide range of total backend computing costs, GitHub says." Read more: https://lnkd.in/gDZYifjn

Ollama and GitHub Copilot. Another important union for privacy and power in the terminal.... The AI development landscape gains another chapter in its evolution. The announcement that Ollama now supports GitHub Copilot CLI reinforces an integration movement seeking the balance between cloud intelligence and local processing security. To date, no one holds an exclusive path to efficiency, but this combination of tools certainly opens new doors for developers. What this integration allows you to do now: - Repository Exploration. You can use Copilot CLI to map codebases and understand complex structures with the support of local processing. - Terminal Automation. This union allows for task planning based on GitHub tickets where AI assists in editing files and installing dependencies more fluidly. - Privacy and Control. By using Ollama as a backend option, developers gain another layer of choice regarding where their sensitive context should be processed. My personal analysis on this movement In my view, what we are witnessing is the consolidation of a hybrid model. Copilot's support for Ollama is another step acknowledging that the future of corporate software will not be centered on a single closed solution. My predictive analysis is that the terminal will remain the primary command center, now powered by agents that respect the security perimeter of each project. True productivity does not stem from a single tool, but from the ability to integrate the best available solutions into your workflow. #Ollama #GitHubCopilot #AI #OpenSource #CTO #SoftwareDevelopment #Privacy #TechTrends #Coding

Soon, your Copilot bill will tell you who burned the credits. It still doesn't show what they shipped with it. On June 1, 2026, GitHub switches every plan to usage-based AI Credits, with budget caps at the enterprise, cost centre, or user level. Useful. Stops at "which user." Copilot Budget fixes the next layer. Open source, MIT licensed. It reads what Copilot already logs locally and appends a receipt to every commit: feat: add OAuth2 login flow Copilot-Est-Cost: $0.41 Copilot-Model: claude_sonnet_4 1250/3800/1.00 The model line is `model input_tokens/output_tokens/premium_requests` — the exact units AI Credits will bill on after June 1. Already in your git history. `git log --grep="Copilot-Est-Cost"` across a branch = cost per feature. No external services, no telemetry. GitHub's budgets tell you WHO spent the credits. Commit trailers tell you WHAT FOR. Get both before the meter starts running. #OpenSource #DeveloperTools #FinOps #GitHubCopilot #AI

Our team uses GitHub Copilot with AGENTS.md files in each repository to give the AI context about our projects. Over time, we noticed the same dependency upgrade patterns being copy-pasted across multiple repositories: Framework migration steps Library compatibility matrices Known breaking changes and their fixes CI configuration patterns Instead of maintaining the same knowledge in 6+ places, we consolidated it into a single GitHub Copilot Agent Skill — a structured knowledge file that Copilot loads on demand when you need it. The result: 1,136 lines removed from scattered documentation files One source of truth, updated as we learn Today: the skill diagnosed a failing dependency upgrade in minutes — it already knew the root cause and the exact fix from the last time we solved a similar problem The real win isn't the line count. It's that next time someone on the team hits a dependency upgrade failure, the AI assistant already knows the solution from the last time we solved it. Knowledge that used to live in someone's head now lives in the toolchain. If you're using GitHub Copilot with AGENTS.md files, Copilot Agent Skills are worth looking into. Curious if others have found similar patterns for sharing AI context within a team. #GitHubCopilot #DeveloperExperience #DevOps #KnowledgeManagement

GitHub Copilot Shifts to Usage-Based Billing and Ends Annual Plans 📌 GitHub is overhaulng its Copilot pricing model, moving away from annual subscriptions toward a flexible, usage-based billing system driven by AI Credits. This transition reflects Copilot’s evolution into an agentic platform that consumes more compute resources through complex, multi-step workflows. Users should prepare for this shift by June 2026, as the new structure replaces fixed request limits with token-based consumption to better align costs with actual usage. 🔗 Read more: https://lnkd.in/dRJtSHra #Githubcopilot #Usagebasedbilling #Subscriptionmodel #Softwareasaservice

🔴 Going LIVE! Kayla Cinnamon, Senior Developer Advocate at Microsoft, is about to take the stage for her tutorial "GitHub Copilot Everywhere: CLI, VS Code, and the Cloud" at the Future of Data and AI: Agentic AI Conference! Join live: https://lnkd.in/dpNDdg74 If you're a developer looking to get the most out of GitHub Copilot across your entire workflow — this is the one to catch live. Real features, real trade-offs, no fluff. In this tutorial, you'll learn to: - Use GitHub Copilot across the CLI, VS Code, and cloud-based development workflows - Build real features end-to-end using Copilot across multiple surfaces - Understand the trade-offs between tools and when to switch - Apply practical patterns for integrating Copilot into your entire development loop #AgenticAI #FutureOfAI #AIConference #GitHubCopilot #DeveloperTools #Microsoft