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Explore in-depth articles and tutorials on generative artificial intelligence (AI) models, such as GANs and transformers, techniques to improve performance with RAG, and practical applications for generative AI in your projects. Just getting started? Check out our guide on generative AI .
Learn about the experimental general-purpose accessibility agent that GitHub is piloting.
Agentic workflows that run on every pull request can quietly accumulate large API bills. Here’s how we instrumented our own production workflows, found the inefficiencies, and built agents to fix them.
A practical guide to reviewing agent-generated pull requests: what to look for, where issues hide, and how to catch technical debt before it ships.
How to build the “Trust Layer” for GitHub Copilot cloud agent without brittle scripts or black-box judgements by using dominatory analysis.
Discover tips, technical guides, and best practices in our biweekly newsletter just for devs.
GitHub Agentic Workflows are built with isolation, constrained outputs, and comprehensive logging. Learn how our threat model and security architecture help teams run agents safely in GitHub Actions.
Most multi-agent workflow failures come down to missing structure, not model capability. Learn the three engineering patterns that make agent systems reliable.
AI is rewiring developer preferences through convenience loops. Octoverse 2025 reveals how AI compatibility is becoming the new standard for technology choice.
Think of Continuous AI as background agents that operate in your repository for tasks that require reasoning.
AI is designed to help you do what you love most, not replace your expertise. Discover how developer feedback and real-world experience are shaping AI coding tools that keep you in control.
Learn how custom instructions, reusable prompts, and custom agents help GitHub Copilot deliver more accurate results.
