
5 Reasons You Should Still Learn To Code
With AI doing so much of the coding and software development that's happening these days, do humans still need to learn all of these computer programming skills?
It's a big question for a lot of people who are making career choices, and for leaders and talent developers, too.
I'm going to take a stab at answering this question using resources like a recent edition of the AI Daily Brief podcast that I listen to with Nathaniel Whittemore, where he broke a lot of this down.
I've also heard a lot of input from movers and shakers all over the industry about that essential question – should people still learn to code?
But before I do that, I'd like to go back to the term 'vibe coding' – the idea that humans Illustrate the broad strokes of a program, and use AI to complete the details. Vibe coding doesn't mean that you're completely removed from the coding process. But it does mean automating a lot of this work.
That said, here are some of the reasons I've heard most commonly expressed for people continuing to learn programming languages.
Input from Steve Jobs and others promoting the practice of coding resonates in the context of the tasks that career professionals have to do.
'Everybody in the country should learn how to program a computer,' the now-deceased tech mogul said. 'It teaches you how to think.'
In a way, that says it all.
'Certainly, there's an argument that in a world where even more of our world is mediated by code, the particular genre of thinking that coding enables is even more valuable,' Whittemore adds.
In the podcast, Whittemore also talks about people who know how to do a queue sort or write a hash table may be better at using AI to code than others who don't.
Here's another argument for humans coding – the AI doesn't have all of the contextual details about your business. Unless you've connected something through an API, or entered a whole lot of data, the human still knows more about the enterprise activity than the computer does. So there are some aspects that AI won't be as capable at.
Basically speaking, although AI can excel at code syntax and logic and reasoning, it reaches a limitation when it comes to creativity.
I'll use another example from the podcast, where Whittemore talked about how computers and AI may not be able to come up with new programming languages.
He also invoked the new hot slogan from Andre Karpathy that 'English is the hottest new programming language,' but suggested that we can still utilize the syntax from languages like Python and C.
Many experts in the field have also pointed out that humans can be essential in helping with debugging and fixing glitches in code.
The example that Whittemore uses is working with the tool Lovable to create a codebase.
When something goes wrong, he notes, it's important to be able to get in there and fix it.
So that's another reason for human involvement in coding processes.
Now that I've enumerated those arguments for community coding, let's talk about how this is approached in the industry.
Later in the podcast, Whittemore talked about how senior developers may use AI instead of junior developers, and there might not be any junior developer jobs left. So should people stop learning to code if they won't be able to get a job as a junior developer? That, he says, is missing the big picture.
'Learning to code to get a junior developer job seems a little insane right now,' he says. 'On the flip side, I think that there is basically nothing higher leverage than you can be doing right now than learning this new vibe coding paradigm.'
Don't learn the traditional way, he urges, learn differently, and combine your coding knowledge with a knowledge of how the modern world works – how to create things, how to move the needle with so much creative power at your fingertips.
I'll leave out the part about predictions by notable entrepreneurs, like Dario Amodei's suggestion the AI will be doing 90% of coding soon, or Sundar Pichai saying that Google relies on AI for 25% of its codebase. Whittemore lays out some of the arguments for and against larger percentages of AI responsibility for code, and you can find that in the audio itself.
Whittemore ends that particular podcast with a neat reference to an atavistic literary movement, combining it with AI, and not for the first time, either. Not too long ago, I looked up the word 'shoggoth' as it's used in the AI community, and found out it's a Lovecraft term referring to something like an amorphous blob in AI parlance.
Whittemore, for his part, talks about how he used AI to generate a game like the classic Oregon Trail that GenXers played on school library computers featuring monochrome stick drawings. He took that model, he said, and applied it to the Lovecraftian world for an interesting look at AI-generated game development.
He also apparently worked on new sets of Magic the Gathering resources.
All of that shows us how these things work in aid of greater human creativity.
'Don't tell us,' Whittemore says. 'Show us.'
So there you have it – several reasons to still be involved in knowing the syntax and use of modern programming languages, even though AI can do a lot of it by itself.

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