I hit a new personal best for longest running agent session with Agent 4!
Is there anyone else out there who can get Replit to work like this?
If so, I’d love to grab a virtual coffee and compare notes.
Not on replit, not as long, but I had codex do a long running task that was over an hour. The prompt was maybe 1k lines of markdown and the Plan mode took 10min of back and forth confirming things. I did six iterations of the prompt in order to finally get it cooking how I wanted.
*more impressive - that was only $60ish on Replit
Depends on the project. If it’s a production app probably not. If it’s experimenting and trying to get better with AI tool probably. I don’t know if I have any tasks that would take 8 hours. What actually got done @mikeamancuso?
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how did you get this data generated? @mikeamancuso
Hey everyone, thanks for the thoughtful replies!
That 8h 26m session turned out to be a spectacular success. I had one focused agent stay locked in the entire time on a single goal: running a continuous clean-code improvement loop.
Here’s how it worked:
- The agent pushed changes to GitHub → triggered SonarCloud and CodeQL analysis (smells, warnings, hotspots, bugs, etc.)
- It waited for the results (natural idle time during static analysis)
- Then it read the feedback and performed targeted refactors
- Then it looped back and repeated until the analysis came back essentially clean (“all perfect”)
I do a daily clean-code ritual because I was tired of the 70/30 split: spending ~70% of my time cleaning up after Replit’s “get it done fast” output and only 30% on actual enhancements and new features. Replit’s agent is great for speed and prototyping, but the accumulated quality issues made it hard to push apps past a certain complexity threshold without things getting messy.
This long, intentional quality-focused run completely flipped that ratio for me. No slop piling up, just steady, measurable improvement toward a tidy, high-quality codebase that’s always ready.
I totally get the hesitation around long-running sessions and the risk of technical debt—especially for production apps at scale. That’s exactly why I built the process around SonarCloud feedback and iterative refactoring instead of letting it run wild. It’s an experiment that’s now becoming part of my regular workflow.
Happy to share more details on the exact prompt structure or pipeline if anyone’s interested. Also down for that Replit dev group idea — sounds like a great way to swap these kinds of approaches.
What about you @pmz, @RocketMan, or anyone else — how do you usually handle quality control on longer agent runs?
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