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Master Plan

Project Goal

Build an offline prototype that tests whether manual queue insertions improve short-term recommendation quality over a static seed-based queue.

Current Phase

Phase 1 complete: scope lock and specification scaffolded.

Exact Next Task

Start Phase 2 by choosing one dataset approach, defining the track feature schema, and creating the first synthetic session format without implementing recommendation logic yet.

What Must Not Change

  • Project goal
  • Python-only constraint
  • Offline simulation only
  • No frontend
  • No external music service API integration in V1
  • Baseline plus adaptive reranker only
  • Small-scope target of 12 to 20 focused hours

Deliverables To Keep In View

  • Clean repo
  • Concise technical writeup
  • Evaluation with charts or tables
  • LinkedIn or Medium-style summary post