[_pdp_]

The core issue remains: where do you apply this.

It all has hypothetical benefit at this stage. The only examples I can think of where sub-agents where used extensively and documented is to write a barely working c compiler and barely working browser. Both are coding tasks that do require a lot of processing.

What I am trying to say is that it clear you can speed up the delivery but benefit of this approach is not clear.

This also matches my own experience.

[tarasyarema]

I use this a lot for multi-tasking, let me explain.

Currently at my startup (and in the past when I worked on a bigger company) I have ton of random tasks I need to tackle during the day: from Sentry issues, to analytics on usage, roadmap implementation, customer support. Some of them required deep focus, some of them don't.

Since we have the swarm running for our company my day to day hasn't changed that much in terms of the work I do locally. What it changed is that I can start delegating a lot of my backlog and chores to the swarm. It will do it, iterate, delegate, review, and finally send me a PR or report to check. I check those in the morning and night, and that's it.

I added it to our customer channels, were it has scoped access to the customer setup, and help me debug the issues, and offer a frontline ultra-personalized support.

I see it as a team of interns that just do stuff for you. And good thing: they learn from their mistakes to (hopefully) do not make them again (compounds).

As a random bonus: given the swarm knows what we do and how we work, I just ask them to go out there and figure out any relevant news or posts I should check each morning, and I get a personalized digest to read while I make coffee.

[_pdp_]

Yah. You are describing basically every youtube I have seen on openclaw use-cases: news digests, morning debriefs, etc. I am sure this is useful but not something that you specifically need sub-agents for.

In the context of coding assistants sub-agents are mostly useful to breakdown a more complex tasks in smaller chunks so that refactoring can be done without loosing context. But this is a completely different problem domain that requires burning through a lot of tokens.

In theory I get why it might be useful but what I am trying to say that applications at the moment are limited due to the fact that it is just overkill for most AI interactions.

[rob]

Did you set them up to respond to any HN comments automatically?

https://news.ycombinator.com/item?id=46110024

The two "this is an example reply" and "another" comments you made seem like some sort of automation test there.