A persistent knowledge layer across all agents that maps what you know, what you're learning, and where your gaps are — then tells you about those gaps proactively.
The visual/exploration layer is a **knowledge graph** — relationships and connections, not just stored documents. This makes gap detection natural: missing edges in the graph *are* the gaps.
Domain separation:
- 🏫 **School** — 2890 bot (robotics team)
- 🏭 **Work** — PSB bots (brewery ops)
- 🎮 **Play** — crash-bot / HHS-Hackers crew
## Core Insight
Current agents are mostly command-and-reply. They don't do research, self-direct, or maintain persistent context between sessions. They feel like fancy autocomplete, not assistants.
The question: what would make them feel less like tools and more like... something with continuity?
## Architecture
### The Silo Problem
Three agent domains are intentionally isolated:
- 🏫 School (2890) — student data, competition strategy
- 🏭 Work (PSB) — brewery ops, business data
- 🎮 Play (HHS-Hackers) — crew knowledge, projects
The wiki needs to cross domains without breaking the walls. Solution: a librarian agent.
### Multi-Person Scaling
Same shared knowledge graph, different personal layers per person:
- Each person gets an entity page with confidence scores, scale preferences, learning style
- Shared facts (ESP32 specs, VLAN concepts) compound as every person's learning adds resources
- Access control maps to existing Discord server structure
- Kyle's CEH training → HHS-Hackers server
- Bruno's PathPlanner → 2890 server
- Your VLAN training → DMs or HHS-Hackers
- The compounding effect: every person's learning path makes the knowledge graph richer for the next person
### Professor Agent (The Teacher)
Not just a librarian — a **teacher** that:
1. Sees what you're working on (Pi-hole setup → VLANs coming next)
2. Assesses where you are ("almost none" on VLANs)
3. Finds resources matched to your scale (home lab, not enterprise)
4. Organizes into a learning path (training thread under VLAN)
5. Delivers proactively without being asked
The difference: A librarian says "here's everything filed under VLAN." A professor says "here's what you need right now, at your level, for your situation."
Running on Dell Aurora-R3 (i7-2600K, 32GB DDR3). File-based wiki = zero compute cost. Obsidian = client-side only, no server. Qdrant already running. Gap detection = lightweight heartbeat task. No roadblocks on the core build — only a real-time interactive graph server would strain this box, and Obsidian's local graph view sidesteps that entirely.
## Related
- Claw Empire (GitHub: GreenSheep01201/claw-empire) — separate project for later. Different problem space (orchestration/workflow), not the visual layer for this.
- Mission Control — already has agent topology, could be foundation
