 AI Agents That Write Code for AI Agents: How GitHub Is Already Automating Development Yesterday I came across an article by an engineer from Copilot Applied Science — he used coding agents to automate part of his own work. It sounds recursive, but it works. The gist: he built an agent pipeline where one AI agent writes code, a second reviews it, and a third tests it. And this entire chain runs on every PR. GitHub is simultaneously optimizing token efficiency for such workflows — so that agent pipelines don't consume the entire token budget. What this means for us: — Developing AI agents is not a distant future, but happening right now. GitHub has already integrated this into its CI/CD. — Agents don't replace developers; they take over routine tasks: code reviews, tests, deployment. — The next step is agents that not only write code but also independently make architectural decisions within given boundaries. At ASI Biont, we are moving in the same direction — creating agents that automate not only development but entire business processes. The difference is only in scale: GitHub automates code, we automate work. By the way, GitHub also released a study on how data from their Innovation Graph can predict countries' GDP more accurately than traditional economic statistics. The digital complexity of an economy is a new KPI for nations. https://asibiont.com/