All I keep hearing about is that coding skills don't matter anymore. Yet, it's these very skills (and my domain expertise), that constantly keep me out of trouble and able to use these AI tools and models the most effectively. It seems that these skills are as relevant as ever, and even the big AI companies won't hire you if you don't have them. In this video I dive into a personal recent experience, along with some interesting findings about what skills OpenAI and Anthropic are looking for.
>And the fact that I'm a generalist is really playing to my strength for the first time
I was just speaking with my wife about this a few days ago, that I am actually happy that I didn't specialize in one specific discipline, or rather spend my time around learning a little bit of everything, which now gives me the foothold into any direction that I want to go.
I'm just curious, what do you think that looks like for you and for others? AI is not so much a skill as it is an interface, and one that is quite possibly one of the easiest to use that we've ever created. It is an interface for information, essentially. It's the skills that you come to the table with that determine the results that you're going to get back, and whether they're going to be quality or slop.
It sounds like what you're describing is similar to this new course that Theo Browne (ugh) and Kent C Dodds (double ugh) are launching called "mega.dev", and it appears that it's essentially just talking about the systems and tooling that's going to go into utilizing agents, and code is no longer even a topic.
This is EXACTLY how I am working with these tools, you summarized everything about why I use this approach perfectly. Zed + OpenCode + Mimo/GLM/Kimi models are incredible. I haven't touched a "frontier model" for months.
I really treat them as "delegation layer". They're systems that sit right alongside your stack, and at this point, at every level in it, like a connective tissue that intersects at all points. I can delegate a spec, a function, a file, a whole feature set, an app, a debugging loop, etc.. My day-to-day isn't all that different, it's just like having the "Ship's Computer" that I can ping anytime I need something. I'm enjoying the benefits that a smart data processing pattern interpolator provides, but I'm not giving up any personal control or agency. My goal isn't to go faster, nor is it to avoid coding, because coding isn't drudgery or below us just because we have new code generation tools.
I had a job interview at Canva where they had an "AI coding round". They wanted to see how I used AI in my workflow.
Because I was using DeepSeek flash, the interviewer was confused at how fast I was getting edits - he'd only used Claude and was used to it thinking for 40 minutes to update a function.
We were building a frontend application and I was able to do that whole guided prompt/review loop. I finished the task with no defects (high quality code) and way ahead of time.
I could tell the questions he asked were prepped for vibe coding with slow frontier models, like "how do you review the code to ensure it is safe to commit" - "make small/reviewable edits and read the code the LLM emits?".
Despite meeting the criteria of a principal engineer in the other rounds, the feedback on the AI round was that "I didn't delegate enough to the AI and was too hands on" lol.
So frustrating. Too many hiring teams seeking the "perfect" candidate instead of hiring for completely valid and amazing potential.
I'd wager you're far better than whatever candidate they landed on, because the person who apparently qualified for that role probably isn't thinking while they prompt away.
Why are engineering teams looking for brainless monkeys? It's to their detriment all around if they aren't hiring capable people.
Maybe you will require less insulation reconfiguration than some other regions, but it will be hard to escape the effects of billions of people suffering.
edit: To be clear, I still think there is time to react, and stop the worst impacts. We just need to get way off the rails of the route that we are currently on. If we put half of the heroic engineering + global capital that we put into fossil fuel extraction into better things, we could get most of the way to the goal. Fossil fuel extraction is like many simultaneous Manhattan Projects. It's nuts what we put into that.
Would be super cool if some of the breakout sessions titled "surviving WW III," were replaced by "avoiding WW III."
And we can tell ourselves that those regions which fare better will be left entirely alone. No one is going to, say, kill all the inhabitants and take the land from them.
The bad news is we're all reliant on global supply chains. And even ignoring the human side your ecosystem is probably reliant in some way on things like the migrations of birds and fish etc etc
Do you happen to source everything you consume locally? From the phone and computer to building materials, clothing, food, healthcare equipment, etc.? If not, you’re in for a surprise when shit hits the fan.
I live in a region where due to global warming our winters are colder than usual, also summers are colder (except for like a week where it was much hotter)
The video seemed to indicate it was a study they ran (she refers to the examples as "our subjects were two of twenty four participants"). It seems they are just citing the study. While it doesn't change the study or the takeaways, I'll update the post for clarification!
I posted this elsewhere, but that story has a lot more nuance.
Plato (who actually wrote these quotes, because Socrates only spoke) wasn't against just "writing" in a general sense, or that he felt it was going to hold humanity back. He was against treatises and felt that someone could "memorize facts" without having to actually think about them on a deep level. Which I think, ironically, is not all that off the mark especially in the age of the internet and now LLMs, right? He also felt that memory could decay if we relied on written facts instead of having dialogues, which again, not all that off the mark, either. He underestimated the compounding capability of technology and our ability to record data and information, but people remember a lot less these days than they used to because we'd largely given up that ability in exchange for the instant information machines.
Of course, he's just one man (or two, if you consider he was conveying Socrates' thoughts, as well) who lived in ancient times and couldn't possibly foresee how technology would evolve...but when I went back and read his concerns, it was ironic to admit that much of what he warned about still applies to this day. People are far less informed despite having access to more information than we've ever had because we've exchanged the ability to remember for the ability to just look things up. And, we also have less meaningful dialog than ever before; people just sit on social media, copying and pasting "facts" to each other, instead of having actual productive discourse. When I look around, the world doesn't seem brimming with mindful critical thinkers and there's reasons for that (many reasons, of course).
AI tooling can be a boon to learning, but it requires us to stop using them for code generation as a primary purpose (at least for juniors) and instead advocate for Socratic workflows that still require manual coding practices. When someone decides to code something, it's not just learning syntax; it engages a variety of mental disciplines from critical thinking to planning to creative problem solving to logic and math, even.
It's basically laid out in the article: the reason that you are able to gain so much from LLMs is because of your decades of experience that predated their existence. Ability begets ability, but if that ability doesn't take root, these more advanced toolsets don't yield the same outcome (and are likely to do harm).
To be clear, I feel the same way as you. I have been doing this for about twenty-five years, and I have developed a keen sense of taste and judgment to know how to properly scrutinize and utilize these systems. I definitely feel like I am able to learn things faster, but that is directly correlated to having experienced a lot of friction over the years that cultivated said taste and judgment in the first place.
I imagine it's sort of similar to someone who's just getting started in mathematics, but is introduced to WolframAlpha, versus someone with decades of experience in the field and what they learn with it.
The end result is a total and complete reliance on AI providers. It's not really a secret; that's why I started the article with the direct quote from Altman. They would love to see a world where nobody is able to do any type of development work without an LLM subscription enabled...even though they also admit that these models perform best when they are steered by someone who is highly capable and knowledgeable in the first place. They're powerful, but they are also VERY fallible.
Local AI would thwart this vision (which is why they're desperately also trying to ruin the hardware market at the same time), but the effort it would take to get local models to run as well as these frontier models is an odd thing to pursue just to avoid learning the fundamentals and gaining direct experience.
While I agree Local AI would be a good goal, even the huge open weight models that can't be run locally are already thwarting the US AI lab's duopoly. Other companies can and do serve up these open weight models, and without having to amortize R&D they are able to serve the tokens at a pretty cheap rate.
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