TL;DR: I'm not really here for troubleshooting advice for CGPT (though I'd accept pointers if anyone has them) but really just to report my experience for posterity that completely FOSS software and models are working near flawlessly while stacks that I'm actually paying for are fkng failing me the most! For the past two monts, I've been testing out the viability a CGPT-lead workflow which includes CGPT + Astra [medium] (PM/Lead), DSH + QFN-oQ5e-mtp + oMLX (engineer), CC + GLM-5.3 via z.ai Coding Max sub (engineer). I like the workflow because it's completely hands-off, completely voice-driven, and I can see the outputs in GH, sprint demos, and running code in my desktop + phone browsers. Love that part. Again I have all three models linked to my GitHub private repo and that works great. Also AWS which works just fine. All three are also running in monitor or goal loops. The order of reliability has been: 1) DSH, 2) CC, 3) CGPT. DSH hands down is super solid and I'm still just running v0.7.1-rc1. 5min loop, QFN checks in reliably to our shared GH issue, picks up new work, provides great updates, does what I ask of it for days and days without fail. No problems there almost at all. CC is a close second but I've caught it's 15min loop failing at least twice (possibly timeouts) in the past 6 weeks. Model + harness is strong, but losing time to failed loops just blows. CGPT monitor loop can only be run hourly at most, but is supposed to trigger work (that sometimes never gets done) and I've found the hourly loop paused more than once. Sometimes 12+ hours go by and I check in only to find the monitor has paused itself (??) no logs or explanations, just paused. The desired workflow is that work gets done 24/7 and frankly the CGPT stack is failing hard there.. Somedays it's on it, 24 hours straight of checkins, and other days it's off. I thought I might be hitting limits on my $20/month Plus plan so bumped to the $100/month Pro plan and it almost seems to have gotten even worse. I'm not sure how Altman thinks this is going to turn into a $1-2T business but it's no small wonder that they're barely breaking into duo-deca billions in gross revenue. I'm so glad now that I invested into local hardware (1 x M2U 192GB and 1 x M3U 512GB) because if this is the future of cloud AI then I'd say that we safely have little to worry about.   submitted by   /u/layer4down [link]   [comments]