30 stories
What happens when a proactive AI repository agent is deployed across 13 open source repositories? 578 issues closed, median 8x increase in issue closure velocity, and 10x in PR merge velocity — transforming largely dormant projects into actively maintained ones. The single most important factor?
A practical mental model for agents, workflows, and human-machine systems in agentic engineering.
Agents can power robust workflows by intelligently reacting to unexpected conditions, creating a new form of flexible resilience.
How do you maintain team velocity when AI-generated code needs cleanup? You have two choices: slow everyone down with more review hurdles, or let automated agentic processes clean things up after the fact. The second path is the key to velocity — and it’s now practical with repository automation.
tsb is a from-scratch TypeScript port of pandas, being built almost entirely by Autoloop — one iterative improvement at a time.
Repo Mind Light is follow-up work to Repo Mind. It keeps the same core ambition as Repo Mind: giving humans and coding agents a reliable, holistic understanding of a repository, not just isolated search hits, while preserving the same quality of repository understanding in a form that is easier to…
Glossy finished products are fun, but the real meat is hiding in the sketchbooks. Makers love to see the raw ideas, the struggle to make it work, and the tradeoffs made in service to shipping.
Automate research, development and anything else with a simple, goal-driven loop
What if formal verification could be fully automated — from researching the codebase, to writing specifications, to proving theorems in Lean 4 — all with near-zero human involvement? Lean Squad is a GitHub Agentic Workflow that does exactly this.
Why we need collaborative AI engineering tools, and a tour of Ace — a research prototype from GitHub Next that brings teammates and coding agents into one shared, multiplayer workspace.
Software engineering agents are increasingly capable at making local edits, but they still struggle to build a reliable mental model of a large repository.
What if you woke up every morning to find your repositories a little bit better than when you left them? A performance improvement here, a feature analysis there, an engineering upgrade you didn’t know was possible.
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