Yes, you should learn coding if you want to. You should learn anything you want to learn.

I refuse to give my intellect over to the machine just to blindly consume its homogeneous excretions. I will keep doing what I've always done regardless of how well an AI could do it. I don't need to justify doing so, and neither do you, nor does anyone. It's OK to be a human.

I'd like to share my own experience, which perfectly illustrates Paul Graham's point.

I was trying to fix a bug in ART using Frida. I admitted I knew nothing about the intricate details or tricks of ART. I couldn't even understand why the original author wrote the code in a certain way. Feeling lost, I turned to GPT. But because I couldn't understand the AI's complex reasoning, I couldn't guide it. The AI stubbornly blamed a conflict between Frida and JVMTI and ran in the wrong direction for an hour with zero progress.

Eventually, I gave up on the AI and decided to debug it myself. I couldn't afford to read the whole ART codebase to understand the full context. But in the AI era, the cost of getting a quick summary is near zero. With AI helping me grasp the big picture, I pinpointed the actual bug: a compilation callback issue during ART's transition between runnable and native states.

Before, finding this bug would have required days of reading ART's code. Now, with AI helping me understand something I'm completely unfamiliar with, it took just 1 hour.

My key takeaway: AI is incredibly useful, but if you just say "I don't understand, you keep going," you'll be stuck forever. You still need to learn things.

This is exactly why we should still learn to code. AI is a powerful tool for lowering the cost of understanding, but it cannot replace the human ability to judge, guide, and intervene. You need to know enough to be the manager.

> Should we still learn coding?

As an intellectual exercise, sure.

I don't have a crystal ball, but in my opinion, if you are asking in the context of employment, I think it's very hard to know, and I'd probably recommend against it if you are starting from scratch. Right now, I think that having experience with coding helps me work much more effectively alongside LLMs. Given the progress in the last five years though, I can't be certain that I will be needed in another 10 years. I already recommend against majoring in computer science with the goal of becoming a software engineer. I don't think that the role will go away, but the number of people needed might be much smaller in 10 years, and I wouldn't want to be a new grad in that kind of market.

> If you already know how to code, do you keep learning?

I'm sure others feel differently, but personally, I find it quite annoying to learn new things right now. 5 years ago, if someone came out with a new tool for say, durable workflows, or a new JS framework, I knew that they poured many days of labor and love into the project. They spent many hours thinking through what they were building and the tradeoffs and edge cases. Now, there's just an avalanche of new projects out there and it's hard to separate the wheat from the chaff. Personally, I'm more focused on developing soft skills right now.

Yes, I think people should still learn to code. Why? Well, a few reasons really:

First, if the AI is unavailable, you at least have a backup plan. You can make changes to your website or web app even if Claude or Codex or whatever else is available. That's useful if you're using third party services.

Secondly, it lets you delve into the code and understand where things have gone wrong if the agent gets stuck in a loop or keeps making poor decisions. If you let the AI handle everything, then you're up a creek without a paddle if said AI gets stuck and can't make any progress.

Finally, it's sometimes quicker and more efficient to make a change without using AI, especially if it's a small scale one. Lots of times I've wanted to add a new form field or tweak some random CSS rule, and being able to do that myself made things a lot quicker.

My experience working with programmers for decades (as an individual contributor, team lead, architect, release engineer, engineering manager) is that great programmers are rare and most programmers are good enough and a few flunk out. Since AI is trained on "the internet" it sees and learns a lot of bad habits, poor coding examples, shortcuts, oversimplified solutions, and therefore, by default, produces code that can be improved. To use AI coding agents effectively, you must be able to spot bad code, suggest better approaches, add guardrails, tests, checks, guidance, etc. to keep the agents on track and improve their output. If you do not deeply understand data structures, algorithms, idioms, best practices, footguns, design patterns, etc., you cannot help the agents provide better code.