#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.

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.

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.