I love Karpathy's posts because they're so on point. He's not only a leading expert in his field, but he also manages to capture the zeitgeist with his statements. But this post is particularly impactful.
Since December, (agentic) coding has undergone a significant transformation, one could even say a qualitative leap. Before, it was a matter of iterative improvements, but since the end of last year, it has demonstrated its true value in a completely different way. Or, in Karpathy's words:
"It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since. (...) As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel."
Two points on this that need to be repeated again and again because they are often still misunderstood.
1) The very basic truth: this is the worst it will ever be. From here on out, things will get better. Even if the status quo were to remain as it is, it would be serious. But what we have today is the worst it will ever be.
2) The pace of progress is constantly increasing. It is exponential. And that's the crucial point: from December to February, more happened than in a very long time. And this trajectory will likely (almost certainly) continue.
If points 1) and 2) are true, it is simply impossible to foresee and predict how this will affect society and all essential areas. As much as I welcome and approve of this, the near future is unpredictable. That's all I wanted to say.
It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow.
Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes.
As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now.
It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.