alt Hacker NewsI don't understand. If you have a model that can do bash examples already (your subagents), then why would you need to train a model?
Or are the subagents generating your training data using a closed/paid model?
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computerex • today at 8:08 PM
The models he is using to generate training data are presumably commercial models. He is distilling their bash knowledge into a much smaller model he can run locally fast and cheap.
A very small, highly specialized model can use negligible resources (CPU, energy) to accomplish the same task.
For everyday work that happens frequently it's better to have a tiny specialized model instead of making billable API calls or turning your laptop into an 80W space heater for 20 seconds to run a general purpose model.
The large models can be used to generate synthetic training data. Tell them to make up 100,000 tasks paired with the resulting output as a 1-time cost. Then use that to train a small model.
Think of it as distillation, but focused on a specific task.