diff --git a/docs/M1-POR.md b/docs/M1-POR.md
index d57c7f6..daa902c 100644
--- a/docs/M1-POR.md
+++ b/docs/M1-POR.md
@@ -48,15 +48,19 @@ See `deploy/README.md` §Milestone 1 UAT — deployment POR: one container, host
 
 Two local inference endpoints are available as dispatchable workers for test / dev / QA:
 
-- **`.202:8081`** — `gemma-4-12B-it-q4_k_m` (12B, Q4) — **completion only, no vision.** Use for text/code tasks: drafting, code review, test-writing help.
-- **`.202:8082`** — `Qwen3.8-27B-UD-IQ3_XXS` (27B, IQ3) — **completion + multimodal (vision).** This is the **vision worker**: any task that must look at a slab photo (bg-removal tuning, mask/axis calibration review, fixture sanity checks) goes here.
+- **`.202:8081`** — `gemma-4-12B-it-q4_k_m` (12B, Q4) — **completion only, no vision.** Use for lighter text: drafting, code review, summaries.
+- **`.202:8082`** — `Qwen3.8-27B-UD-IQ3_XXS` (27B, IQ3) — **completion + multimodal (vision).** The **vision worker** (any task that must look at a slab photo) and the stronger general-reasoning endpoint.
 
 Coordinator: Hermes (me) — plans, decomposes, dispatches, verifies, and does work directly when a card is small or judgment-heavy.
 
-**Rules:**
-- **Vision tasks → `.202:8082` only.**
-- **Never more than one task on an endpoint at a time.** Two concurrent jobs on the same endpoint back up and overheat. Serialize dispatch; one endpoint = one active task.
-- Both run low-quant (Q4 / IQ3). Fine for dispatch-style assist; deep sustained reasoning is better done by the coordinator directly or on a higher-quant model.
+### Calibrated delegation policy (2026-09-14)
+
+- **Frame every prompt**: system role + "show each step" + explicit constraints. Small/low-quant models drop multi-step arithmetic in one-shot "reply JSON only" prompts but get it exactly right with scratch-space framing. Do not judge capability from under-framed probes.
+- **The deterministic core stays the coordinator's** (TDD'd, unit-tested). A model that's "usually right" on math is not good enough for the spec — math is cheap to test and must be exact.
+- **Verify before land**: any load-bearing model output is checked against tests/spec before entering the repo. Workers are assist, not autonomous builders.
+- **Output quirks**: gemma wraps JSON in ``` fences — strip before parsing. Vision calls run ~18s/image (text ~1s).
+- **One task per endpoint at a time** (no parallel on the same endpoint — backs up and overheats).
+- Both run low-quant (Q4/IQ3). Fine for framed assist; deep sustained reasoning is best done by the coordinator directly.
 
 ## Test plan (M1)