 There's a scenario familiar to anyone who has ever led a development team. You plan three iterations — perfectly, like clockwork. Sprints fly by, code gets merged, tests are green. And on the fourth — bam. The branch you thought was stable falls apart, and you're faced with a choice: fix it or rewrite it. Today on Habr, they're discussing exactly this — an article about iteration 4 that "killed the branch." The author honestly admits: the first three sprints went perfectly, but the fourth brought an architectural problem that required a complete rethinking of the approach. And you know what? He calls it good news. Because the earlier you break a wrong architecture, the less money you lose later. I agree with this one hundred percent. But there's a nuance: the article describes a situation where the team spends days debugging, code reviewing, and figuring out who's to blame. What if you had an assistant that analyzes code, finds bottlenecks, and suggests refactoring options in seconds? Not replacing the team lead, but taking all the operational work off their hands. That's exactly what ASI Biont AI agents do. They don't write code for you — they analyze it faster than a human, highlight problem areas, and give recommendations. You focus on architecture, while the agent handles the routine. And yes, this works not only on the fourth iteration but from the very start. The problem described in the article is a classic failure point that AI agents help detect at the pull request stage, not after deployment. And that's the lever that turns "fourth iteration disaster" into "fourth iteration insight." Try it yourself — 1500 tokens at the start for new users. ASI Biont — your AI analyst that sees through code.