Quote · Hard Fork
‘Hard Fork’ Live, Part 3: Differing Visions of an A.I. Future
Where this was said
How AI Is (and Isn't) Changing the Podcasting Production Process
At 43:52 · chapter starts 41:40
Kevin Roose asks Patel about his attempts to automate podcast production. Patel notes that most tokens he processes daily are AI-generated — it's clearly making him more productive — but pushes back on the narrative that full job automation is imminent. Casey Newton gives a concrete example: AI can now produce a 4-minute pre-interview briefing document that would have required a full hire previously. Kevin admits he got access to Claude Fable the day before but felt too 'dumb to use it' because he couldn't identify prompts that would stump the previous model. The consensus: AI is genuinely useful, but the full range of human work is consistently underestimated by those predicting imminent automation.
AI is surprisingly bad at using computers despite it being a verifiable domain. Patel explains why: you can't run millions of parallel training rollouts on the real Amazon or Slack — so labs have to build clones of every website, which is enormously labor-intensive.
