I love writing software, line by line. It could be said that my career was a continuous effort to create software well written, minimal, where the human touch was the fundamental feature. I also hope for a society where the last are not forgotten. Moreover, I don't want AI to economically succeed, I don't care if the current economic system is subverted (I could be very happy, honestly, if it goes in the direction of a massive redistribution of wealth). But, I would not respect myself and my intelligence if my idea of software and society would impair my vision: facts are facts, and AI is going to change programming forever.

In 2020 I left my job in order to write a novel about AI, universal basic income, a society that adapted to the automation of work facing many challenges. At the very end of 2024 I opened a YouTube channel focused on AI, its use in coding tasks, its potential social and economical effects. But while I recognized what was going to happen very early, I thought that we had more time before programming would be completely reshaped, at least a few years. I no longer believe this is the case. Recently, state of the art LLMs are able to complete large subtasks or medium size projects alone, almost unassisted, given a good set of hints about what the end result should be. The degree of success you'll get is related to the kind of programming you do (the more isolated, and the more textually representable, the better: system programming is particularly apt), and to your ability to create a mental representation of the problem to communicate to the LLM. But, in general, it is now clear that for most projects, writing the code yourself is no longer sensible, if not to have fun.

In the past week, just prompting, and inspecting the code to provide guidance from time to time, in a few hours I did the following four tasks, in hours instead of weeks:

1. I modified my linenoise library to support UTF-8, and created a framework for line editing testing that uses an emulated terminal that is able to report what is getting displayed in each character cell. Something that I always wanted to do, but it was hard to justify the work needed just to test a side project of mine. But if you can just describe your idea, and it materializes in the code, things are very different.

2. I fixed transient failures in the Redis test. This is very annoying work, timing related issues, TCP deadlock conditions, and so forth. Claude Code iterated for all the time needed to reproduce it, inspected the state of the processes to understand what was happening, and fixed the bugs.

3. Yesterday I wanted a pure C library that would be able to do the inference of BERT like embedding models. Claude Code created it in 5 minutes. Same output and same speed (15% slower) than PyTorch. 700 lines of code. A Python tool to convert the GTE-small model.

4. In the past weeks I operated changes to Redis Streams internals. I had a design document for the work I did. I tried to give it to Claude Code and it reproduced my work in, like, 20 minutes or less (mostly because I'm slow at checking and authorizing to run the commands needed).

It is simply impossible not to see the reality of what is happening. Writing code is no longer needed for the most part. It is now a lot more interesting to understand what to do, and how to do it (and, about this second part, LLMs are great partners, too). It does not matter if AI companies will not be able to get their money back and the stock market will crash. All that is irrelevant, in the long run. It does not matter if this or the other CEO of some unicorn is telling you something that is off putting, or absurd. Programming changed forever, anyway.

How do I feel, about all the code I wrote that was ingested by LLMs? I feel great to be part of that, because I see this as a continuation of what I tried to do all my life: democratizing code, systems, knowledge. LLMs are going to help us to write better software, faster, and will allow small teams to have a chance to compete with bigger companies. The same thing open source software did in the 90s.

However, this technology is far too important to be in the hands of a few companies. For now, you can do the pre-training better or not, you can do reinforcement learning in a much more effective way than others, but the open models, especially the ones produced in China, continue to compete (even if they are behind) with frontier models of closed labs. There is a sufficient democratization of AI, so far, even if imperfect. But: it is absolutely not obvious that it will be like that forever. I'm scared about the centralization. At the same time, I believe neural networks, at scale, are simply able to do incredible things, and that there is not enough "magic" inside current frontier AI for the other labs and teams not to catch up (otherwise it would be very hard to explain, for instance, why OpenAI, Anthropic and Google are so near in their results, for years now).

As a programmer, I want to write more open source than ever, now. I want to improve certain repositories of mine abandoned for time concerns. I want to apply AI to my Redis workflow. Improve the Vector Sets implementation and then other data structures, like I'm doing with Streams now.

But I'm worried for the folks that will get fired. It is not clear what the dynamic at play will be: will companies try to have more people, and to build more? Or will they try to cut salary costs, having fewer programmers that are better at prompting? And, there are other sectors where humans will become completely replaceable, I fear.

What is the social solution, then? Innovation can't be taken back after all. I believe we should vote for governments that recognize what is happening, and are willing to support those who will remain jobless. And, the more people get fired, the more political pressure there will be to vote for those who will guarantee a certain degree of protection. But I also look forward to the good AI could bring: new progress in science, that could help lower the suffering of the human condition, which is not always happy.

Anyway, back to programming. I have a single suggestion for you, my friend. Whatever you believe about what the Right Thing should be, you can't control it by refusing what is happening right now. Skipping AI is not going to help you or your career. Think about it. Test these new tools, with care, with weeks of work, not in a five minutes test where you can just reinforce your own beliefs. Find a way to multiply yourself, and if it does not work for you, try again every few months.

Yes, maybe you think that you worked so hard to learn coding, and now machines are doing it for you. But what was the fire inside you, when you coded till night to see your project working? It was building. And now you can build more and better, if you find your way to use AI effectively. The fun is still there, untouched.