memory: record long-lived execution agents

MEMORY.md

@@ -38,6 +38,7 @@
 ## 7) Model policy (current preference)
 - Historical temporary preference once was: all subagents **primary** = `openai-codex/gpt-5.2`, **fallback** = `github-copilot/claude-opus-4.6`.
 - Current important exception / newer rule: **codex_worker** should use **primary** = `openai-codex/gpt-5.4`, prefer high/extra/xhigh thinking when available, and should **not auto-fallback** to another model. If its primary model is unavailable, report to Tao and let Tao decide the replacement model.
+- Additional long-lived execution agents initialized locally for repeat use: **docs_worker**, **qa_worker**, **ops_worker**.
 
 ## 8) Watchdog / automation policy
 - Tao preference: avoid watchdog-style auto-restart automation.

memory/2026-03-07.md

@@ -58,4 +58,5 @@
 - Preference: execution agents should get the strongest execution model; main should remain strong for PM/summary work, but not necessarily do the coding itself.
 - New delegation rule clarified: unless work is truly tiny and can be finished in one short pass, main should avoid personally editing/coding and should delegate implementation to `codex_worker` first.
 - New agent-splitting rule clarified: create multiple execution agents when work is parallelizable, responsibilities differ, contexts would otherwise get mixed, or separate validation/release tracks are needed; avoid splitting tiny or tightly coupled work.
+- Long-lived execution agents initialized locally: `docs_worker`, `qa_worker`, `ops_worker` (with dedicated agent dirs + workspaces + basic role files). `codex_worker` remains the default general execution worker.
 - This architecture is the current default, but Tao may revise it as needs change.