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GreatsOfBharatha

GreatsOfBharatha is an Apple-platform product line for story-driven, place-driven historical learning experiences.

Its current center of gravity is the Shivaji Maharaj arc, built as a playable educational product that combines narrative, map learning, recall, and premium enhancement layers while keeping the core experience touch-first and accessible.

Current product focus

  • turn the Shivaji research/spec stack into a production MVP slice
  • build a 6-scene lesson flow with a strong first playable vertical slice
  • implement fort map pinning and place-learning interactions
  • add premium enhancements like haptics, motion, and optional intelligence layers without making them mandatory
  • keep GitHub issues, milestones, PRs, and CI as the main execution surface

Current build target

Production MVP slice with premium enhancement layers

That means:

  • the core experience must be understandable and completable without advanced hardware
  • sensors act as enhancement layers, not gates to understanding
  • implementation should move through durable repo artifacts, not chat-only planning

Product truth locations

Use this order when orienting:

  1. repo reality: code, docs/specs, docs/research, milestone and implementation docs, tests
  2. workspace product memory: memory/greatsofbharatha-product-durable.md, memory/greatsofbharatha-product-working-notes.md, memory/greatsofbharatha-knowledge-index.md
  3. live GitHub issue / PR / CI state
  4. current conversation instructions

Working model

  • product planning lives in GitHub Issues
  • delivery is tracked in GitHub Projects
  • roadmap slices live in Milestones
  • research is documented in docs/research/
  • specs are documented in docs/specs/
  • active work should link docs, issues, PRs, and validation evidence together

Current priority lanes

  • foundations: content schema, asset checklist, interaction/state contracts
  • core gameplay: lesson flow core, fort map system, reward/progress system
  • enhancements: sensor layer, Apple Intelligence hint/recap layer, optional orientation mode

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