E01¶


Research	R0023 — Counterproductive advice and prompt lifecycle
Run	2026-03-25
Query	Q004
Source	SRC02
Evidence	SRC02-E01
Type	Analytical

PEPR proposes a framework to predict prompt combination effects and select effective prompts per use-case.

URL: https://arxiv.org/html/2405.11083v1

Extract¶

PEPR (Prompt Exploration with Prompt Regression) proposes a framework to predict the effect of prompt combinations given results for individual prompt elements, as well as a simple method to select an effective prompt for a given use-case. This is the only peer-reviewed academic paper found that specifically addresses prompt regression — the problem of prompt modifications producing unexpected results.

The framework approaches prompt selection as a prediction problem: given known performance of individual prompt elements, predict how combinations will perform without exhaustive testing.

Relevance to Hypotheses¶

Hypothesis	Relationship	Strength
H1	Supports	An academic framework exists, published on arXiv/OpenReview
H2	Contradicts	This is more than tooling — it is a published methodology
H3	Supports	Addresses prompt element combination prediction but not full lifecycle (no deprecation, maintenance, or cross-model migration)

Context¶

PEPR is narrowly focused on prompt regression prediction rather than full lifecycle management. It does not address versioning, deployment, or deprecation. Its value is as proof that academic interest in prompt management methodology exists, even if the coverage is limited.