DESIGN: MVP demo bar + model selection layer (tier map, LiteLLM aliases, auto-pick v1)

DESIGN.md

@@ -93,3 +93,32 @@ by humans/legacy stacks — interaction layer must not require the harness;
 interface can come later without redesign. MCP servers we run get replaced
 by these Go CLIs behind a minimal MCP adapter, killing the docker/python
 MCP fleet.
+
+## MVP demo bar (Charles, 2026-08-28 ~19:00)
+Fire up the harness (screen or docker) and run a turn whose prompt is
+"tell me about yourself" routed through LiteLLM; the GLM 5.3 self-
+description comes back and lands as the REPORT. That is the MVP. The
+0800 checklist (compile, dry-run, real single-turn, LSP wired, studies)
+builds toward it; the demo itself is this one exchange.
+
+## Model selection layer (Charles, 2026-08-28 ~19:00)
+Claude-Code-style model picking for the harness and its subagents:
+the harness chooses the right model per body of work (overall + per-task).
+GLM fleet is wide; use it deliberately.
+- Inventory on proxy today (12): glm-4.5{,-air,v}, 4.6{,v}, 4.7{,-flash},
+  5, 5-turbo, 5.1, 5.2, 5.3. No glm-5.3-flash configured yet; flash-class
+  today = glm-4.7-flash. Adding 5.3-flash later = one LiteLLM model_list
+  entry, zero code change (see aliases).
+- v0 (tonight, skeleton): static TASK CLASS -> MODEL TIER map in
+  harness.toml. Classes: study/read -> flash tier; code/architecture ->
+  flagship (glm-5.2/5.3); review/summarize/writeback -> mid (5-turbo/5.1);
+  vision when needed (4.6v/4.5v). Config-only, no heuristic code.
+- Aliases are the contract: harness requests `mopac-study`, `mopac-code`,
+  `mopac-review` ... LiteLLM resolves alias -> concrete model. Swapping
+  models (e.g. 4.7-flash -> 5.3-flash when live) = proxy config edit only.
+- v1 (post-pilot): auto-selection — cheap flash model classifies each
+  incoming TASK (Redmine issue text) and picks tier + model before the
+  main turn spends anything; subagent spawns inherit class-based routing
+  with per-tier budget caps (LiteLLM vkeys already enforce spend).
+- Telemetry: every REPORT logs model used + tokens + cost via LiteLLM
+  spend APIs, so routing decisions are auditable and tunable.