Real-world AI agents are mostly retry loops, not autonomous reasoners

A developer who has run automation systems widely marketed as AI agents says the reality of production deployment differs sharply from industry claims. According to their experience across thousands of tasks, roughly a third of runtime is spent re-executing the same actions due to page re-renders, selector changes, or anti-bot barriers like Cloudflare. The most persistent challenges are not reasoning or planning but mundane obstacles such as captchas, cookie banners, and phone verification steps that require human intervention. The developer argues that truly reliable agents are deliberately narrow in scope, with clear success conditions and comprehensive logging, while complex multi-step reasoning agents tend to fail most often. Their key takeaway for builders is to prioritize robust infrastructure and budget heavily for retry logic, as that is where the bulk of actual execution time is spent.