Ask HN: Those running agents 24/7, what's your workflow and what are they doing?

A Hacker News user running a SaaS business asked the community how developers operate AI agents 24/7, questioning what the agents actually do, how close the models are to the frontier, and what the setup costs. The poster said agents stop working once the day's last large assigned task finishes, and asked how users fit into the pipeline from idea to task to automated build to final human review, including how much context is provided and how to stop agents from proceeding without asking for clarity. The Ask HN thread had drawn 3 points and 1 comment as of the post.

In either a local AI or a hosted AI arrangements, I'm seeing lots of posts of people saying they have a need for agents 24/7, assuming they're in the software space. What are these agents actually doing? How close to the frontier are these models, and what does it cost? I run a SaaS business, but I feel like agents aren't really working for me as once the last large task finishes that I assign for the day. I have a huge backlog that I would like to automate but I'm struggling to comprehend how people get quality outputs from tasks and where the user is supposed to be in the pipeline and how things go from idea to task to automated build to what I assume is the final human intervention which is the review process. Top line, I'm assuming they're using some sort of issue tracking system like Linear or GitHub issues into either a cloud agent or a work tree where it's built out and tested? What about for things that aren't bug or issue based, but are actually features? How much context do you provide? How do you stop the AI just running with things instead of asking for clarity when required, etc. Is there actually a net positive benefit to this setup, or do you end up just having to patch all of the work that was done autonomously overnight most of the time? Comments URL: https://news.ycombinator.com/item?id=49653369 https://news.ycombinator.com/item?id=49653369 Points: 3 Comments: 1