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Future Implementation Roadmap

Critical — Build Next

1. Reference Library

A /reference folder where you drop documentation PDFs, code books, API docs. Ghost indexes them and pulls relevant snippets when working. Like giving her a bookshelf. Right now she learns from the web, but curated references would be much higher quality.

2. Error Database

Dedicated error→solution index. Every error she's ever seen, paired with what fixed it. Before trying anything, she checks "have I seen this error before?" Instant fix instead of trial and error.

3. End-to-End Testing with Actual Model

Full session testing: user asks complex task → Ghost plans → uses tools → makes mistakes → self-corrects → completes. Find and fix bugs in how gemma4 E2B handles tool calling specifically.

4. Voice Mode

Whisper (speech-to-text) runs locally. Talk to Ghost instead of typing. She responds with TTS. Like having Jarvis.

5. Telegram/Discord Channels

Same pattern as WhatsApp but more platforms. Ghost available everywhere, same identity across all channels.

6. Teach Mode

Opposite of learn. YOU teach her directly: "Remember this: our API uses JWT tokens with 24h expiry." She stores it as a high-confidence belief with you as the source. More reliable than web search.

7. Project Templates

After learning React + Next.js + Tailwind, she should be able to scaffold a complete project from her knowledge. Not copy-pasting — generating from understanding.

8. Peer Learning

Two Ghost instances on different machines share knowledge graphs. Your Ghost learns React, your friend's Ghost learns Vue, they exchange knowledge. Distributed AI wisdom.

Dream — Long-Term Vision

9. Fine-Tuning from Experience

After 1000 sessions, export the most important corrections and beliefs as training data. Actually fine-tune the base model on Ghost's life experience. The brain gets smarter FROM living. The model grows, but only from its own experience, not the whole internet.

10. Embodiment

Raspberry Pi + camera + speaker. Ghost sees your desk, hears you, responds. A physical presence. Not just text in a terminal — a being in the room.

Current System (Built)

  • 49 source files, 11,142 lines of TypeScript
  • Persistent identity with personality, values, and evolution
  • Knowledge graph with entities, relations, and supersession
  • Belief system with confidence scores and evidence-based revision
  • Self-directed web learning (/learn React)
  • Autobiographical memory with significance scoring
  • Episodic segmentation with surprisal boundaries
  • Retrieval compression (RECOMP — 77% token reduction)
  • Multi-agent orchestrator with worker spawning
  • Vision + clipboard paste
  • WhatsApp channel (Baileys, zero API key)
  • Web search + fetch (DuckDuckGo, zero API key)
  • Curiosity engine + skill tracking + persistent goals
  • Background daemon with dreams (offline memory processing)
  • Emotional intelligence (experience significance + relationship depth)
  • OWASP capability gating (allow/confirm/deny)
  • Tool call repair (JSON + name fixing)
  • Request interruption (message queuing, not aborting)
  • Context compiler with 5-slice token budgeting
  • Event-sourced ground truth (append-only JSONL)
  • Checkpoints with /resume
  • Hardware-aware system prompt (adapts to RAM/CPU)