AI & ML

GitHub engineers and industry thought leaders offer tips, best practices, and practical explainers about various aspects of AI and ML, ranging from fundamental concepts to advanced techniques and real-world applications. For more detailed documentation and practical guides on GitHub’s own AI coding tool, GitHub Copilot, check out GitHub’s official documentation.

Featured

Getting more from each token: How Copilot improves context handling and model routing

How GitHub Copilot is making more of each session go toward useful work, so your credits go further.

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What are git worktrees, and why should I use them?

Git worktrees have been around since 2015, but it wasn’t until recently they became popular. Learn what they are, how to use them, and why you might.

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GitHub Copilot CLI for Beginners: Overview of common slash commands

GitHub Copilot CLI for Beginners: Learn how to use slash commands to control your terminal AI agent.

Accelerating researchers and developers building multilingual AI with a new open dataset

A new repository-level dataset, published on GitHub under CC0-1.0, helps researchers and developers discover multilingual developer content across READMEs, issues, and pull requests.

Latest

How we made GitHub Copilot CLI more selective about delegation

Better orchestration, fewer handoffs, faster progress, without a single new knob.

Making secret scanning more trustworthy: Reducing false positives at scale

Alerts are more trustworthy and actionable when noise is reduced. See how we improved the verification step with context-aware LLM reasoning.

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Give GitHub Copilot CLI real code intelligence with language servers

Install and configure LSP servers for GitHub Copilot CLI, replacing brute-force grep/decompile with real code intelligence.

From one-off prompts to workflows: How to use custom agents in GitHub Copilot CLI

Custom agents let GitHub Copilot CLI understand your stack and team workflows, turning one-off terminal prompts into repeatable, reviewable processes.