I'd like to know, just like Jon, how people are using swarms or lots of agents to do real work. What are your use cases? Please share. From the original post, here are the ones that stood out but I'd love to hear more: •Large-scale document processing: Processing standing orders (100+ pages each) for dozens of judges across federal trial courts. Previously done interactively in a terminal with Claude; now moving to more autonomous agents with API credits. (@adamdavidlong) •Parallel, independent tasks with separate contexts: Generating hundreds of SEO/AEO docs, live trading of eBay watches, and scraping Twitter for people to reply to. Emphasizes parallelization so each can be managed independently without context pollution. (@leoanthias ) •Long-running automated testing: Some tests take 4–12 hours each, so overnight scale makes sense. (@richgel999) •Compute-heavy work that overheats local machines: Building a game with multiple subagents left running overnight so it doesn’t melt a MacBook during the day. (@ChrisBarnes3D) •Slow verification / CI loops: Build → deploy on a clean OS → run full test suites → note issues. Test cycles themselves are slow, so longer runs are useful. (@AD1991234 and others) •Jobs that wait on the outside world: Scraping, checking inbox placement, retrying flaky APIs, watching competitor pages, aka things limited by calendar time rather than pure compute. One instance burns a queue; a swarm burns the calendar. (@ruhhvee) •Batch high-volume / personalized work: Custom emails (e.g. 1000/day) with proper research and quotes; semantic-level refactors or per-call-site reviews; personalized outputs for many customers. (@wkoszek and others) •Specialized / isolated agents: Separate agents for different domains (dev skills/MCPs vs. marketing/social research) purely to avoid context pollution and token waste. (@mariodian) •Loop-style or multi-project scaling: Treating work as backlog → execute → feedback/plan/research → more work, then either automating the feedback side or scaling horizontally across projects so agents stay busy. Some people shared actual tools/frameworks or weekend-long example loops. (@LKRBuilds and others)