GitHub updates policy on AI model training with personal repos

GitHub Copilot is moving to Usage-Based Billing GitHub just announced that starting June 1 2026, Copilot will transition to a usage-based model powered by GitHub AI Credits. A few important details: ✦ Credits over Requests: Subscriptions now include a monthly credit allotment. Usage is calculated via tokens (Input/Output/Cached), similar to standard LLM APIs. ✦ Core features remain included: Standard code completions and “Next Edit” suggestions will not consume credits. ✦ Pooled Usage for Teams: Organizations can now pool credits across seats to eliminate wasted capacity and set granular budget caps. Why it matters: Base prices aren't changing, but the ceiling is lifting. This move enables more heavy-duty, agentic workflows while giving engineering leaders better transparency into their actual AI ROI. it’s time to start looking at those usage dashboards! 🙂 Full details here: https://lnkd.in/dUa-8hDU #GitHub #Copilot #GenAI #SoftwareEngineering #AI #DevOps

As AI agents become core to our development workflows, a new governance problem is emerging: fragmented, unversioned prompts scattered across IDEs and local environments — what I'd call Instruction Drift. The new gh skill command in GitHub CLI is a meaningful step toward solving this. It treats Agent Skills as first-class citizens in the software delivery lifecycle: Centralized Discovery & Management — Standardize agent capabilities across the engineering org, installed via a single CLI command from any GitHub repository. Supply Chain Integrity for AI — Skills are pinned using git tree SHAs and immutable releases, ensuring the skill an agent uses today is byte-for-byte identical to what it uses tomorrow. No silent updates, no non-deterministic failures. Open Interoperability — Built on the open 'agentskills.io' spec, skills work across GitHub Copilot, Claude Code, Cursor, Codex, Gemini CLI, and more. No vendor lock-in. One important caveat worth noting: skills are not verified by GitHub — always inspect before installing (gh skill preview). This is exactly the kind of governance control your platform teams should be building policy around. Currently in public preview, but the architecture signals where this is heading: from experimental AI scripts to auditable, versioned, production-grade agent infrastructure. Read the full changelog #GitHubCopilot #GitHubCLI #AIAgents #AgentSkills #PlatformEngineering #AIGovernance #SupplyChainSecurity #EnterpriseAI #SolutionArchitect #DeveloperTools #DevOps #GenerativeAI #SoftwareEngineering #OpenSource #AI #developers #DeveloperCommunity #GitHub

Understanding a new codebase shouldn’t feel like guessing. You open a GitHub repo… 300+ files… and no idea where to start. That’s exactly what Codebase Navigator is trying to fix. https://lnkd.in/gMfQC3sc Instead of digging through files, you can: → paste a GitHub URL → ask questions in plain English → instantly see how everything connects What makes it interesting is how it works. You don’t just get answers. You get: → a live dependency graph (built from real imports) → a code viewer with relevant lines → a repo explorer → and an AI that explains everything All updating together. Even better, it can run locally using tools like Ollama. No API keys. No cloud dependency. This changes how developers explore code. Instead of asking: “Where is this file?” You ask: “How does authentication work?” And see the full flow instantly. It feels less like searching… and more like navigating. Would you use something like this for large codebases? #AI #Developers #GitHub #Programming #OpenSource #MachineLearning

GitHub Copilot CLI brings AI assistance directly to your terminal. Instead of switching to a browser or code editor, you can ask questions, generate full-featured applications, review code, generate tests, and debug issues without leaving your command line. here is the beginner samples https://lnkd.in/g4RMVENQ #GenAI #AI #Github #Copilot

GitHub Copilot is moving from premium requests to token-based AI Credits on 1 June. The subscription prices have not changed. What has changed is what that money buys, and it is now entirely dependent on how your developers use the tools. A quick chat and a multi-hour agentic session used to count the same. Under token metering, they will consume vastly different amounts of the same budget. This follows weeks of sign-up freezes across individual and business plans, driven by the economic reality that agentic workflows were routinely costing GitHub more per session than users paid per month. Claude Code and Cursor have already been through this transition. The consistent lesson: the billing model is not the hard part. The hard part is model governance, budget controls, and usage visibility that goes beyond a monthly total. Most organisations are not ready for AI tool costs that vary with developer behaviour rather than headcount. The ones that get governance in place before 1 June will be fine. The ones that do not will find out in July. How are you preparing for token-metered AI development tooling? #GitHubCopilot #AIGovernance #EnterpriseAI

GitHub Copilot just made a quiet but significant move — and it reveals a structural problem worth understanding. This week, GitHub removed Claude Opus from its Pro plan entirely. Opus 4.7 is now Pro+ only, at a 7.5x premium request multiplier ("promotional" until April 30). For context: the standard Opus multiplier was 3x. That's a 150% price jump on their most capable model, with limited advance notice. New Pro and Pro+ sign-ups are also temporarily paused as of April 20. This isn't a pricing complaint. It's a trust and architecture problem. Copilot has evolved into a multi-model marketplace — GPT, Claude, Gemini, Grok all available. That's genuinely useful. But it also means Copilot doesn't control the economics of the models it resells. When Anthropic prices Opus at frontier rates, Copilot absorbs that cost and passes it on — unpredictably, mid-cycle, with multipliers that change without warning. Developers in GitHub's own community forums documented costs jumping from 1x to 3x overnight on Opus 4.5 with no prior communication. One team wrote: "seeing costs jump from 1x to 3x without any prior communication creates a difficult situation." This is the core tension: Copilot's strength is distribution — IDE integration, GitHub context, enterprise rollout. Its weakness is that it doesn't own the intelligence it's built on. For boilerplate and autocomplete, this is fine. But for agentic workflows, deep debugging, and architecture decisions — the tasks where model capability actually changes outcomes — unpredictable access to frontier models is a reliability problem, not just a pricing complaint. The teams I've seen migrate to Claude Code or direct API access aren't doing it for raw capability. They're doing it for predictability and control. As AI becomes load-bearing in engineering workflows, those two things will matter just as much as benchmark scores.

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

You've been training GitHub's AI for free. Your code. Your prompts. Your late nights. All of it. On April 24, 2026, GitHub's new Copilot policy goes live. Every developer on Free, Pro, and Pro+ gets opted in automatically. No warning. No consent. No payment. Here's exactly what GitHub is collecting: → Every prompt you type into Copilot → Every suggestion you accept or modify → Your file names and folder structure → Code context around your cursor → Your comments and documentation → How you navigate between files → Every Copilot chat conversation you've had The worst part? It's opt-out — not opt-in. They're betting you won't notice until it's too late. How to stop it before April 24: Go to github -> settings -> copilot Find "Allow GitHub to use my data for AI model training" Set it to Disabled Do this for every GitHub account you own Copilot Business and Enterprise users — you're protected. Free, Pro, Pro+ users — you are the product. Tag a developer who needs to see this. #github #developers #webdevelopment

GitHub Copilot Controversy Highlights Challenges in AI-Assisted Development The recent controversy surrounding GitHub Copilot and AI-generated pull request messages has sparked discussions about transparency and developer trust. As AI tools become more integrated into software development, maintaining clarity, accountability, and ethical use is becoming increasingly important. This case reflects the evolving dynamics between automation and human oversight in coding environments. 🔗 Read more: https://lnkd.in/gCkBBEPP #GitHub #Copilot #ArtificialIntelligence #SoftwareEngineering #DeveloperTools #TechIndustry #Innovation #TechGenyz

The End of Unlimited: Decoding GitHub's Move to Token-Based Billing For two years, we’ve enjoyed a flat-rate "Premium Request" system. As of June 1, 2026, GitHub is aligning with the rest of the industry (and its own compute costs) by moving to GitHub AI Credits.  1. What Stays the Same? • Base Subscription Prices: Copilot Pro remains $10/month, Business is $19/user, and Enterprise is $39/user.  • Unlimited Completions: Standard code completions and "Next Edit Suggestions" in the IDE still do not consume AI Credits.  2. What is Changing? Instead of a request limit, each plan now includes a credit allotment: • Copilot Pro ($10): Includes $10 in monthly AI Credits.  • Copilot Pro+ ($39): Includes $39 in monthly AI Credits.  • Promotional Bonus: For the first 3 months (June–Aug 2026), Business/Enterprise users get a massive boost ($30 and $70 in credits respectively) before it reverts to their base subscription price.  3. The New "Token Tax" Costs are now calculated by Token Consumption. This means a high-reasoning model like Claude Opus 4.7 or GPT-5.5 will "drain" your credits significantly faster than a lean model. • Input + Output + Cached tokens all count toward the total.  • Copilot Code Review will now consume both GitHub AI Credits and GitHub Action minutes.  4. Admin Controls Enterprise admins now have "Budget Mission Control." You can set spend caps at the organization or even user level. When a user runs out of credits, you can choose to either block additional usage or allow "Pay-as-you-go" overages. The Bottom Line: GitHub is effectively passing the "Compute Bill" back to the power user. If you use lean models for 80% of your work, your bill won't change. If you run heavy agentic workflows through Enterprise models, your "Unlimited" days are over. Are you ready to audit your team's token usage, or will you just increase the budget and hope for the best? Checkout 👉 https://lnkd.in/dpZ-zkys #githubcopilot