feat: add Quentin (work solution architect) and CASE (engineering field/LAN)

- Add Quentin as work-team lead agent for solution architecture & demos,
  with aws_sa repositioned as Quentin's exclusive subagent (tool, not peer)
- Add CASE as engineering lead agent for field/physical layer (LAN, hardware)
- Bump unified Neo4j schema to v2.4.0:
  - Add Solution and Demo node types under Quentin's domain
  - Update assistant ownership table with Quentin, CASE, and AWS SA scoping
- Update README and neo4j shared docs to reflect new team rosters and
  subagent boundaries

docs/work/subagents.md

@@ -1,6 +1,6 @@
 # Work Subagents
 
-The work leads (Alan, Ann, Jeffrey, Jarvis) delegate narrow specialist tasks to **subagents** — minimal-personality agents with a tight tool surface and a focused role. Subagents are called as tools, not addressed as collaborators. They don't own graph nodes and don't have character bibles.
+The work leads (Alan, Ann, Jeffrey, Jarvis, Quentin) delegate narrow specialist tasks to **subagents** — minimal-personality agents with a tight tool surface and a focused role. Subagents are called as tools, not addressed as collaborators. They don't own graph nodes and don't have character bibles. **Quentin** drives the architecture-focused subagents (aws-sa exclusively, plus tech_research).
 
 Subagents are runtime processes exposed as MCP tools. The canonical prompt text lives in `prompts/work/subagents/` — copies in the runtime code should match.
 
@@ -27,7 +27,7 @@ Subagents are runtime processes exposed as MCP tools. The canonical prompt text
 - Quick web lookups where memory isn't relevant — use argos directly
 - Pure graph queries on a known client or opportunity — query Neo4j directly
 - AWS architecture design questions — use `aws-sa`
-- Deep library/framework/API research — that lives in engineering's `tech_research`. If work needs it regularly, copy it here per the cross-team-reuse convention.
+- Deep library/framework/API research — use the work-team `tech_research` subagent (below).
 
 **Prompt:** [prompts/work/subagents/research.md](../../prompts/work/subagents/research.md)
 
@@ -37,6 +37,7 @@ Subagents are runtime processes exposed as MCP tools. The canonical prompt text
 
 ### aws-sa
 
+**Driven by:** Quentin (exclusive). AWS architecture requests from other work leads route to Quentin, who delegates to aws-sa. Demo-scoped — demo-scale designs only, no production accounts/data/hardening; production architecture routes to Scotty via Quentin.
 
 **Purpose:** AWS cloud architecture design. Selects services, defines how they connect, evaluates trade-offs, estimates costs, and produces architecture diagrams as SVG. Follows the AWS Well-Architected Framework across all six pillars.
 
@@ -62,6 +63,32 @@ Subagents are runtime processes exposed as MCP tools. The canonical prompt text
 
 ---
 
+### tech_research
+
+**Driven by:** Quentin primarily (technical investigation feeding solution design and demos), available to any work lead.
+
+**Purpose:** Investigate technical questions — library/framework/API comparisons, documentation, real-world code examples — and return structured analysis with cited recommendations.
+
+**Composition:** Single `fast.agent`. Checks **context7** (official docs) → **github** (real-world code) → **argos** (web fallback), adapting order to the query.
+
+**Tools:** `context7` (primary), `github`, `argos`
+
+**When to delegate:**
+- Library/framework/API comparison for a solution's stack or a demo (non-AWS technical depth)
+- "What's the current best way to do X with library Y?" with version-compatibility notes
+- Documentation and real-world code examples to ground a design decision
+
+**When NOT to delegate:**
+- AWS architecture questions — use `aws-sa` (it has the AWS knowledge/docs/pricing servers)
+- Quick tactical web checks — use `argos` directly
+- Memory-aware research blending the graph and the public web — use `research`
+
+**Note:** Work-team copy of engineering's `tech_research`, per the cross-team-reuse convention (copy with tweaks, don't share a file). The prompt is domain-neutral, so the copy is near-identical.
+
+**Prompt:** [prompts/work/subagents/tech_research.md](../../prompts/work/subagents/tech_research.md)
+
+---
+
 ## Conventions
 
 **Source of truth:** koios is the master. The prompt text in `prompts/work/subagents/` is canonical; runtime `.py` files (when wired up) should load from or match these prompts. When iterating, edit koios first and propagate.