“The Problems with Deliberate Practice” — @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
Cedric’s friendly critique of the Ericsson deliberate-practice literature. DP works beautifully in well-defined domains (chess, music, sport) where clear feedback exists. In wicked domains (business, design), naïve attempts to apply DP fail because the feedback signal is delayed, noisy, and partly social. Adapt before applying.
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 Problems with Deliberate Practice by Cedric Chin (Commoncog). 3323 words. Filed 2026-04-19 as part of Start-Here + Business-Expertise-Triad backfill cohort.