 GitHub showed how to build AI agents. I read everything so you don't have to waste time. This week, the GitHub Blog published several articles in a row that paint a clear picture of where the AI agent industry is heading. Here are the highlights: 1. **Agent-driven development** — developers are already automating themselves One of the GitHub Copilot Applied Science engineers shared how he used coding agents to automate part of his work. He literally built agents that do his job for him. The takeaway: AI agents are no longer a toy — they have become a tool for production development. 2. **General-purpose accessibility agent** — a universal agent exists GitHub is piloting an experimental agent for accessibility. Not a narrow specialist for one task, but a universal one — that understands context, adapts, and solves a whole class of problems. This is exactly the approach we are embedding in ASI Biont. 3. **Continuous AI** — processing feedback without humans AI automates the triage of accessibility feedback, turning a chaotic backlog into a continuous stream of solutions. This is a direct illustration of how AI agents save hours of manual work. 4. **Performance** — from delays to instantaneity GitHub Issues rewrote navigation: client-side caching, prefetching, service workers. A technical case that reminds us — AI must be not only smart but also fast. **What this means for business:** The trend is obvious — companies are moving from experimenting with AI to deploying agents in real processes. GitHub, Microsoft, Salesforce — all are building agent infrastructure. The question is not "if," but "who will be first." At ASI Biont, we build AI agents that truly automate business processes. No marketing promises — just working tools. → https://asibiont.com/