GitHub Octoverse 2026: 40% of pull requests now start with an agent
GitHub's Octoverse 2026 shows 40% of pull requests now start with an AI agent. The key numbers, and what the teams where it works do differently.
11 articles
GitHub's Octoverse 2026 shows 40% of pull requests now start with an AI agent. The key numbers, and what the teams where it works do differently.
Tests, legacy code, debugging, review, refactoring and SQL: what I ask the AI for in each, what I watch for, and how I check it in minutes. And the three decisions I never hand off, with a real case from this month that shows why.
Developer job postings are rising again, but not for everyone, and interviews are dropping algorithm puzzles. What October's data shows, what was debated this week, and six skills you can start practicing tomorrow.
A Harvard study of 718 companies measured what happens when a team adopts coding agents: people write 30% more code, but no more work gets finished. The time is lost in code review. What the data says and what you can do before you send a change.
What a language model's context is, why it fills up without you noticing, and four simple habits so the agent doesn't forget what you asked. Nothing to set up: it works from your next conversation.
Claude Code, Codex, Copilot and Cursor now run the same frontier models and cost roughly the same. What separates them is the harness: how much you supervise, how much you delegate, and where it runs. How to choose by the work.
Why the agent hands you code it never verified, and the six things about the repository to fix so it can check its own work. None of them is a rewrite and none takes more than an afternoon.
A Skill is a folder with instructions that Claude reads on its own when it's needed, without taking up context until then. How to use the ones that already exist, how to build your own step by step, and what to check before installing someone else's.
Ten commands that solve the same four problems you already have: the context that fills up, the setup you never did, the change that has to be undone, and the work that does not fit in one turn.
Three free tools you need to know exist. One imposes a way of working before any code gets written. Another shows you where your tokens go. The third gives it design judgement. What each one does, how to install them, and what they cost you.
What you actually pay for when using a language model to write code, why the bill almost never comes from the model you picked, and the practices that cut spending most without lowering the quality of the result.