I’ve noticed a pattern in a few projects I’ve worked on. A workflow starts out with one agent. Then it gets split into a planner, a researcher, and a few other specialized agents because the architecture seems cleaner that way. Sometimes it helps. But other times it just creates more handoffs, more things to debug, more latency, and more opportunities for something to go wrong. A couple of times, I’ve seen a workflow get simpler and more reliable after moving back toward a single agent with clearer instructions and better tooling. I’m not against multi-agent systems. There are definitely cases where they make sense. But I sometimes wonder whether they’re being introduced too early, before anyone has proven that the problem actually needs them. Has anyone else gone through that process and ended up simplifying an agent architecture instead of making it more complex? submitted by /u/Financial_Ad_7297
Originally posted by u/Financial_Ad_7297 on r/ArtificialInteligence