If you are looking for LLM agents that go off and do a bunch of
work on their own, you will be supremely underwhelmed. Anyone who went straight to building agents without a human in some large loop found that they were trying to make the LLM do things it was extremely bad at.
The right approach to build toward agents is to start with something that gives pretty good responses to prompts and build up an agentic mode to let it do more and more in response to each prompt. It should be thought of as extending how much you get per prompt, and doing so by chaining together components you've already worked at making to good at.
Cursor (the LLM powered VS Code fork) has an agentic mode and they are doing this the right way. The normal chat window is good at producing changes to your code, and at applying them, at looking at lints, at suggesting terminal commands, at doing directory listings or RAG on your codebase. Agentic mode is tying those together to do more of the work you want with fewer prompts from you.
The right approach to build toward agents is to start with something that gives pretty good responses to prompts and build up an agentic mode to let it do more and more in response to each prompt. It should be thought of as extending how much you get per prompt, and doing so by chaining together components you've already worked at making to good at.
Cursor (the LLM powered VS Code fork) has an agentic mode and they are doing this the right way. The normal chat window is good at producing changes to your code, and at applying them, at looking at lints, at suggesting terminal commands, at doing directory listings or RAG on your codebase. Agentic mode is tying those together to do more of the work you want with fewer prompts from you.