Post-training pain points: messy parallel experiments, dependency hell, high GPU costs
Pitiful-Minute-2818 · reddit · 2026-07-30
An AI engineer on Reddit shares three major pain points in post-training:
- Messy parallel experiments: difficulty managing multiple architecture ideas simultaneously.
- Dependency hell: returning to old projects after months is painful.
- High GPU costs: no direct solution but a core issue.
He poses five questions to the community:
- Current workflow and biggest time sinks.
- Hardest decisions (base model, training method, reward, dataset, hyperparameters, etc.).
- How to measure success (automatic evaluation metrics).
- Experiences where training succeeded but real-world use failed.
- What would justify paying for an automated post-training system (fewer GPU hours, better benchmarks, faster turnaround, reproducibility).
Aims to validate demand for building post-training infrastructure tools.
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