I don’t really understand agents. I just don’t get why we need to pretend we have multiple personalities, especially when they’re all using the same model. Can anyone please give me a usecase, that couldn’t be solved with a single API call to a modern LLM (capable of multi-step planning/reasoning) and a proper prompt? Or is this really just about building the prompt, and giving the LLM closer guidance by splitting in…
Additionally, in self-hosted environments, using an agent-based approach can be more cost-effective. Simpler or less computationally intensive tasks can be offloaded to smaller models, which not only reduces costs but also improves response times.
That being said, this approach is most effective when dealing with structured workflows that can be logically decomposed. In more open-ended tasks, such as "build me an app," the results can be inconsistent unless the task is well-scoped or has extensive precedent (e.g., generating a simple Pong clone). In such cases, additional oversight and iterative refinement are often necessary.