Hypothesis Generator
A research agent that asks the same question twice is wasting tokens. The trick is forcing each draft to land somewhere new.
Prerequisites: Phase 19 Track A lessons 20-29
#Learning Objectives
- Drive a sampler from a seed prompt and turn its outputs into typed hypothesis records.
- Ramp the sampler temperature on each pass so the next draft drifts further from the last.
- Filter near duplicates with a small embedding model and a cosine distance threshold.
- Rank the survivors with a scoring function that blends novelty, specificity, and testability.
- Hold every step deterministic so the same seed always produces the same queue.
Keep going. The rest of this lesson is one step away.
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The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.