derive-achieves-flexibility-with-reproducibility
IN derived (depth 3)
The derive pipeline resolves the tension between strategic flexibility and deterministic reproducibility: three budget strategies (alphabetical truncation, random sampling, semantic clustering) provide diverse exploration approaches, while fixed-seed deterministic sampling and accurate proportional allocation ensure each strategy produces identical results across runs.
Summary
The derive pipeline lets you choose how beliefs get selected for exploration — alphabetically, randomly, or by semantic similarity — so you can optimize for different goals depending on the situation. At the same time, any given choice produces exactly the same output every time you run it, because sampling uses fixed seeds and budget splits are calculated precisely, not approximated.
Justifications
SL — multiple strategies with deterministic seeds = flexibility without sacrificing reproducibility
Antecedents (all must be IN):
- derive-budget-is-flexible-and-efficient — The derive pipeline's budget allocation is both strategically flexible (three selection strategies: alphabetical truncation, random sampling, semantic clustering) and computationally efficient (linear accumulation with guaranteed floor of 5 per agent group), enabling callers to trade off reproducibility, diversity, and semantic coherence without performance penalty.
- derive-prompt-is-deterministic-and-reproducible — The derive pipeline's prompt construction is fully reproducible: deterministic sampling with fixed seeds selects consistent belief subsets, and accurate proportional budget allocation ensures each agent receives the same token share across runs.