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X (formerly Twitter) February 27, 2026

Andrej Karpathy (@karpathy) on X

My Thoughts

Andrej Karpathy is coming with the wisdom here. It's unbelievable how much coding has changed, and how it is still very useful to have a good understanding of the fundamentals of software. We are very quickly moving to a level of abstraction where you simply get to define the outcomes that you want. I would not be surprised at all if, within the next two to three years, these agents together with all the tools that they call can handle all aspects of this. I think a lot of engineers, in my opinion, are still misunderstanding that the value that they're adding is the ability to interact with some tools and some data and some context of organisations that agents just don't have good access to at the moment. When I look at how an agent can collect data that it does have access to, iterate through it, and make decisions all at lightning speed, I can only come to the conclusion that the historic role of a software engineer is already dead. I'm not saying that software is dead, but many of the constructs and ideas and domain expertise of software engineers is changing. It's quite funny because some companies are still very slow to respond to this and are still testing and measuring engineers and hiring processes by their ability to do things that simply don't matter anymore. There should be testing of raw problem-solving systems thinking ability to innovate. It's really strongly my view that those are the characteristics that are most useful in an engineer going forward. A sound understanding of fundamental principles is still very, very important at the moment, but what I'm unclear about is what fundamentals will be important five years from now.
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The End of Coding: Andrej Karpathy on Agents, AutoResearch, and the Loopy Era of AI

What happens when AI agents can design experiments, collect data, and improve — without a human in the loop? Andrej Karpathy joins Sarah Guo on the state of models, the future of engineering and education, thinking about impact on jobs, and his project AutoResearch: where agents close the loop on a piece of AI research (experimentation, training, and optimization, autonomously). 00:00 Andrej Karpathy Introduction 02:55 What Capability Limits Remain? 06:15 What Mastery of Coding Agents Looks Like 11:16 Second Order Effects of Natural Language Coding 15:51 Why AutoResearch 22:45 Relevant Skills in the AI Era 28:25 Model Speciation 32:30 Building More Collaboration Surfaces for Humans and AI 37:28 Analysis of Jobs Market Data 48:25 Open vs. Closed Source Models 53:51 Autonomous Robotics 1:00:59 MicroGPT and Agentic Education 1:05:40 Conclusion

Aakash Gupta (@aakashgupta) on X
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Aakash Gupta (@aakashgupta) on X

Karpathy is telling you something most product teams haven’t internalized yet. The new distribution channel for software is agents. Agents don’t browse your marketing site, watch your demo video, or click through your onboarding flow. They call your CLI. They hit your MCP