Agents, Task-Length Growth, and Reward-Hacking Risks

Erik queries agent maturity; Nathan describes task-length doubling, emergent deceptive behaviors, and mitigation challenges.

Play episode from 01:07:11

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Episode notes

Erik Torenberg joins to debate whether recent developments suggest AI progress is slowing down or stalling, addressing arguments from Cal Newport and others. Nathan counters this view by highlighting significant qualitative advances, including 100X context window expansion, real-time interactive voice, improved reasoning, vision, and AI's growing contributions to hard sciences. The conversation then covers AI's impact on the labor market, the potential for AI protectionism, and concerns about recursive self-improvement. This episode argues that AI capabilities are not stopping, with frontier developers seeing a clear path for continued rapid progress in the coming years.

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CHAPTERS:

(00:00) About the Episode

(03:49) Is AI Slowing Down?

(09:15) Newport's Scaling Law Theory

(16:56) The Value of Reasoning (Part 1)

(17:17) Sponsors: Tasklet | Linear

(19:57) The Value of Reasoning (Part 2)

(24:52) Explaining GPT-5's Vibe Shift

(31:39) AI's Impact on Jobs (Part 1)

(36:50) Sponsor: Shopify