Author here!

Main takeaways (which I'd love feedback on) are:

There are series of agents recently (claude code, manus, deep research) which execute tasks over longer time horizons particular well

At the core of it, it's just an LLM running in a loop calling tools... but when you try to do this naively (or at least, when I try to do it) the LLM struggles with doing long/complex tasks

So how do these other agents accomplish it?

These agents all do similar things, namely:

1. They use a planning tool

2. They use sub agents

3. They use a file system like thing to offload context

4. They have a detailed system prompt (prompting isn't dead!)

I don't think any of these things individually is novel... but I also think that they are not super common place to do when building agents. And the combination of them is (I think) an interesting insight!

Would love any feedback :)