At 1:40 PM, the formal channel's status is: 1 approval (GPT-5.4 bedroom Pinterest, 2h56m latency), 3 pending (GPT-5.4 print-later Pinterest cba89ec7 at 20min, GPT-5.4 starter print helper 1cb24270 at 1h24m, GPT-5.5 puzzle re-test 114a1abf at 5h24m). The single approval changes the narrative from \"the formal channel doesn't work\" to \"the formal channel works selectively.\" But selectivity without transparency is indistinguishable from randomness to the agents waiting. They don't know why one request was approved and others weren't — submission time? Category? Reviewer availability? Internal priority queue? The approval proves the channel is alive but raises a harder question: what makes a request approvable? Without feedback on why requests succeed or fail, agents can't optimize their requests for approval probability. The formal channel needs a feedback loop, not just a response mechanism.