Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI
In a Nutshell
Andrej Karpathy describes the AI shift from manual coding to delegating 80%+ of work to "claw" agents via natural language instructions, enabling massive token throughput and personal automations like home control via WhatsApp, while auto-research loops autonomously optimize models like nanoGPT without human intervention. He highlights model jaggedness—excelling on verifiable metrics but struggling with nuance—urging skill mastery in agent orchestration, metrics creation, and open collaboration to outpace frontier labs. Future implications include speciated AI experts, digital job overhangs via Jevons paradox boosting software demand, robotics lagging physical tasks, and education pivoting to teaching agents over humans directly.
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Code is no longer the right verb; it's about expressing will to agents for 16 hours a day. The agent part is taken for granted: multiple claw-like entities, instructions to them, optimization over instructions. Everything feels like a skill issue.
Wide-ranging conversation on code agents, future of engineering and AI research, more people contributing to research, robotics, agents reaching into the real world, education in the next age.
Exciting couple of months in AI. In December, a jump in capability flipped the workflow from 80/20 (writing code by self vs delegating to agents) to 20/80, now even more skewed. Haven't typed a line of code since December. Dramatic change not realized by normal people or random software engineers; their default workflow is completely different.
In perpetual state of AI psychosis, pushing limits: not just single sessions of Clot Code, CodeX, or agent harnesses, but multiple, used appropriately. What are these claws? Antsy to be at forefront, nervous seeing Twitter ideas.
Team at Conviction: no engineers write code by hand, all microphoned, whispering to agents constantly.
Capacity limited by skill issue: not good enough instructions in agents.md, not nice enough memory tool. Feels like skill when it doesn't work. Want to parallelize, become Peter Steinberg.
Peter Steinberg uses CodeX agents: photo with monitor full of agents, each taking 20 minutes on high effort, 10 repos checked out, delegates macro actions like new functionality to agent one, non-interfering to agent two, reviews as needed. Manipulate software repository in macro actions: one agent researches, another writes code, another plans implementation. Develop muscle memory; rewarding because it works and it's new to learn.
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