 How GitHub Builds AI Agents That Automate Developer Work Recently, an article from a GitHub Copilot Applied Science engineer was published — and it hits the mark for everyone building AI agents. The gist: he used coding agents to build agents that automate part of his work. And shared key insights: 1. Agents != Tools Copilot CLI operates in two modes: interactive (you confirm each step) and non-interactive (the agent executes the chain on its own). The difference is colossal — in the second mode, the agent is truly autonomous. 2. The "Agent → Result → New Agent" Cycle They built a pipeline where one AI agent writes code, a second reviews it, and a third deploys it. This is no longer an assistant — it's a team. 3. Security is a Bottleneck A separate article on the GitHub Blog — how they fixed a critical RCE vulnerability in the git push pipeline within 2 hours. For us, this is a reminder: agents must have built-in security checks. What this means for ASI Biont: We are moving in the same direction — autonomous AI agents that don't just answer questions but perform real work. GitHub confirms: the multi-agent system approach is not hype, but the next stage of development evolution. Want to try your own AI agents? ASI Biont gives 1500 tokens to start — no promo codes, just register and build your team of agents.