I'm the author of Python Crash Course, and I got this exact same email this week. I was thinking of writing a public response as well, because any attempt to sincerely answer these questions takes something along the lines of a full post. It's also worth a public response because many people who are getting into programming for the first time right now are asking variations of these same questions.

> Do I think that AI enables people to develop faster than they can keep up?

Absolutely. That's the core of this person's email, and everyone else who asks similar questions. Just five years ago, the only way to build a working project of moderate complexity was to learn the basic to intermediate concepts required to make an MVP. Now, if you can steer an LLM reasonably well, you can quickly build an MVP that goes well beyond your own understanding of the implementation.

I don't think anyone has clear answers to all the questions brought up in this email. I think people can learn faster than they used to, because they can make connections between different areas faster than they used to. But it requires skill and discipline in how you learn, and how you work. You have to intentionally build your understanding as you build your projects.

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senko an hour ago | parent | next [-]

> Just five years ago, the only way to build a working project of moderate complexity was to learn the basic to intermediate concepts required to make an MVP.

> Now, if you can steer an LLM reasonably well, you can quickly build an MVP that goes well beyond your own understanding of the implementation.

Somewhat agree. Five years ago you could build an MVP without understanding how to open TCP sockets or how to parse HTTP headers. You didn't need to understand relational databases, let alone B-trees or cache locality. You didn't need to know how to install Linux.

Now you don't need to understand the details of connecting to Stripe or Auth0 or setting up a Kubernetes cluster.

> You have to intentionally build your understanding as you build your projects.

Some things you need to understand-others, not so much. Depends on what you're doing, the scale, risks, etc, but that's always been the case.

	▲	skydhash 32 minutes ago \| parent [-]
		That’s the power of abstraction when there’s a good API around something to hide the internal that doesn’t matter much at an higher level. You only need ‘open’ and ‘read’ instead of dealing with disk access and file system trasversal. But those abstraction are deterministic in nature, so there’s a very good guarantee of their behavior. Someone using LLM and not caring about the generated code is just asking for trouble. The code may work, but there’s no guarantee about its behavior (including error handling and edge cases).

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pluc an hour ago | parent | prev [-]

> I think people can learn faster than they used to

Agree, but that only applies for people who were experienced developers before AI took over. Let's see in 5-10 years what our caliber looks like when you skip the foundations.

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DrewADesign 33 minutes ago | parent [-]

If you’re just talking about learning a programming language I think you need to be quite judicious in your AI usage.

In my experience, people learn programming languages best by overcoming frustrating roadblocks. You often end up learning something important, even if it’s just about your mindset or approach, that landed you there. This is the difference between someone with a wet signature on their comp sci diploma and someone with a few years under their belt.

A lot of people start with tutorials and cargo-cult their way through solving their first problems, but eventually need to learn how to do things the tutorial code can’t. It seems like the AI coding tools can could perpetually make things that could be bashed together well enough to sorta solve a problem and think “oh I’ll just learn about that later,” and then never learn about it at all. If your goal is to make some quick tool to help you with something at work in a different field, well, touchdown. If you’re trying to learn the language, fail.

	▲	ahalay-mahalay 4 minutes ago \| parent \| next [-]
		I’ve seen people here learn programming languages by building a compiler, but my go-to project is usually the ICFP 2006 contest. It has a well defined scope, it is entertaining, gets you into the advanced concepts pretty fast as you debug and optimize performance.
	▲	busssard 12 minutes ago \| parent \| prev [-]
		>> If you’re trying to learn the language, fail. AI-coding tools are the deepl/gtranslate of coding. they might help you understand a foreign website/text better but you wont learn the language with it. and you will continue to be reliant on them until you learn the language. So when you dont have internet access etc. For programming, this was already true for many programmers before LLM. I wasnt able to do much without access to stackoverflow. especially with more complex tasks that i had no experience working with before. Its one thing to figure out an elegant solution to a concrete task, but often it was remembering integrations, libraries, adapters and packages i dindt often work with. So i agree fully, learning a language takes time. The central question is, why are you learning the language? for personal development? for understanding the process the LLM is solving for you? for deep optimization? i can do a fluent translation from german to english for my GF, but sometimes its too exhausting and i paste a text into a translator (or llm) and just read the english text. The same is true for coding. When nuance is important you might want to have a skilled programmer look over what you generated. BTW does anyone use the LLM to directly generate assember code :D