#deskilling

Argues that "orchestrator" workflows in agentic coding create a paradox of supervision — effectively supervising an agent requires the very coding skills that atrophy from over-relying on it — and adds vendor lock-in and unpredictable token costs as compounding risks. Proposes demoting AI to a secondary role: use it for planning and research, but keep manually coding 20-100% of implementation and never generate more than can be reviewed in one sitting.

I love the line that a higher level of ambiguity is not a higher level of abstraction, and the Jeremy Howard quote at the end. It ties back to the "dark flow" article I have saved — Rachel Thomas's gambling-addiction parallel to vibe coding, the same slot-machine-lever feeling.

Rachel Thomas draws a sharp parallel between vibe coding and gambling addiction, coining "dark flow" to describe how AI coding agents produce the feel of productive focus without real growth. A METR study found developers perceived a 20% speedup while actually working 19% slower — a nearly 40% gap between felt and actual productivity.

I keep coming back to this one. The irony is that this entire site and workflow are agentic — which makes Thomas's warning feel personally implicating rather than abstract. Howard is even quoted directly here, making it a natural companion to his Nvidia interview on Jeremy's Wager.

Jeremy Howard challenges the industry framing of AI adoption as a low-risk bet, arguing that outsourcing thinking to agents causes active de-skilling. He advocates for a human-centric approach where AI amplifies understanding rather than replacing it.

I call Howard's critique 'Jeremy's Wager' — the idea that going all-in on agents isn't a safe Pascal's Wager but a dangerous gamble where the hidden cost is active de-skilling. If AGI doesn't arrive as predicted, you're left with diminished skills and an organization running on spaghetti code nobody understands. His alternative maps directly onto Answer.ai's pedagogy of understanding over abstraction.