diff --git a/pipeline/test_loop_engineering_meta_prompt.py b/pipeline/test_loop_engineering_meta_prompt.py
index 7ac9c21..fb86286 100644
--- a/pipeline/test_loop_engineering_meta_prompt.py
+++ b/pipeline/test_loop_engineering_meta_prompt.py
@@ -23,6 +23,9 @@ def test_loop_engineering_meta_prompt_locks_safety_fields():
         "Team manages agents",
         "vault/proxy credential injection",
         "YouTube `hLUGXO5DSpo`",
+        "Product work with coding agents",
+        "human taste and systems thinking",
+        "YouTube `P3KDebPTUrw`",
         "External research anchors",
         "NVIDIA Secure Agent Workspace",
         "Infisical Agent Vault",
diff --git a/plans/meta-prompts/loop_engineering.md b/plans/meta-prompts/loop_engineering.md
index 135bd16..eaf4901 100644
--- a/plans/meta-prompts/loop_engineering.md
+++ b/plans/meta-prompts/loop_engineering.md
@@ -85,6 +85,18 @@ Every autonomous work-agent plan must include:
 
 Reference: Latent Space, "The Blueprint for Autonomous Work Agents" with Gavriel Cohen / NanoClaw (YouTube `hLUGXO5DSpo`).
 
+## Product work with coding agents note
+
+When implementation gets cheap, do not delete product discipline. Plans should use prototypes to explore, but still preserve the product loop:
+
+- PRD/spec captures why, users, constraints, and success criteria;
+- prototype makes options concrete and testable;
+- human taste and systems thinking review whether the result fits the whole product;
+- scheduled/background agents may gather context, but promotion still needs receipts and review;
+- role boundaries can flex, but ownership, decision rights, and phase state must stay explicit.
+
+Reference: Lenny's Podcast, "OpenAI Codex lead on the new shape of product work" with Andrew Ambrosino (YouTube `P3KDebPTUrw`).
+
 ## External research anchors
 
 Ground agent plans against external production guidance, not just video notes: