“The Expertise of Evaluating Expertise” — @CedricChin
Why this is in the vault
Cedric’s tacit-knowledge series is the spine of his entire body of work — the argument that expertise in any wicked domain (business, agents, engineering) is pattern-matching that can only be acquired through reps with feedback. This directly shapes how RDCO trains AI agents (deliberate-practice loops) and how we develop the founder’s own deployment expertise.
The core argument
Members-only meta-essay: how do you tell if someone actually has the expertise they claim? Framework: ask for stories of specific decisions including the alternatives considered and why they were rejected — the texture of those stories reveals depth. Pattern-collectors can’t fake the texture; practitioners produce it effortlessly.
Mapping against Ray Data Co
Two load-bearing applications: (1) Agent training methodology — agents need the same perceptual-exposure + feedback-loop structure Cedric describes for human experts; we’re explicit about this in our agent-deployer pitch. (2) The founder’s own learning loop — every client deployment is a rep, the vault is the playback, Sanity Check is the forcing function for articulating what was learned.
Related
- 2026-04-15-commoncog-no-truth-in-business-only-knowledge
- 2026-04-15-commoncog-data-driven-will-not-skill
- 2026-04-15-commoncog-no-learning-dont-close-loops
Source: The Expertise of Evaluating Expertise by Cedric Chin (Commoncog). 4529 words. Filed 2026-04-19 as part of Start-Here + Business-Expertise-Triad backfill cohort.