AI should elevate your thinking, not replace it

The eloquence with which this point gets (repeatedly) made is continuing to improve each next time I read it. However, I still feel like we haven't nailed it. That is, we are not yet at the "aphorism" stage of the discourse (e.g. "the medium is the message", "you ship your org chart", "9 mothers can't make a baby in a month"), in which the most pointed version of this critique packs a punch in just a few words that resonate with the majority of people. That kind of epistemological chiseling takes years, if not decades. And AI certainly won't do it for us, because we don't know how to RL meaning-making.

Edit: 9 babies → 9 mothers

Is anyone tired of being told what AI is supposed to mean for the individual? As a software guy it's supposed to mean I am now a team lead of sorts. However all the people I see crowing about this never sought to become team leads in their career, nor did I.

Yet now suddenly everyone is supposed to want to become a team lead of sorts (ie. the agents becoming your team). I don't want to do that, I treat an AI agent as a pair in a pair programming unit. Nothing more, nothing less. If someone wants to treat it differently, good on them, but they have no place telling what works for thee works for me.

There are plenty of engineers that couldn't work without a modern IDE or in languages without memory management.

Or without the ability to use a library from GitHub / their package manager.

It doesn't feel THAT much different to me.

"Engineer" as a term might drift. There are "web developers" that can only use webflow / wordpress.

I think AI can generally be utilized in two ways:

1) you use it to help write code that you still “own” and fully understand.

2) you use it as an abstraction layer to write and maintain the code for you. The code becomes a compile target in a sense. You would feel like it’s someone else’s code if you were asked to make changes without AI.

I think 2) is fine for things like prototypes, examples, references. Things that are short lived. Where the quality of the code or your understanding of it doesn’t matter.

I think people get into trouble when they fool themselves and others by using 2) for work that requires 1). Because it’s quicker and easier. But it’s a lie. They’re mortgaging the codebase. And I think the atrophy sets in when people do this.

Easier said than done. once you are given a lazy way to do things faster and easier and mostly better, it's hard to go back. this is by design. there is no turning point. this addiction is as strong as drugs I feel.

The way I use AI now feels more exhausting than the programming I did for the last 20 years. I pose a problem, then evaluate proposals, then pick the one I think is the "right one"(tm), then see the AI propose a bunch of weird shit, then call it out, refine the proposal until it feels just about right (this is the exhausting part), then let it code the proposal. The coding will then run for 1-5 hours and produce something that would have taken me at least 2 or 3 weeks (in that quality).

After 5 hours or so of doing this planning, I'm EXHAUSTED. I never was exhausted in this manner from programming alone. Am I learning something new? Feels like management. :)

There are plenty of engineers, who simply can't think, AI will not change anything in this regard.

People who let AI do their thinking at any level never valued it in the first place. "Use it or lose it", as they say. The count of studies backing this up continue to rise and yet so do the articles saying LLM use in software development is fine because our value is in our thinking.

I am rebuilding numba. It is very hard for me to imagine doing it by hand. I tried it a couple of years ago but it was excruitiangly painful. It was slow and messy. So many small things that gets stacked on top of each other over years of abstraction.

I am doing it again using LLM. Legitimately, things that would have taken weeks is now done overnight. I still have to look at the code, at the generated C output, still have control over the architecture to make it easy for me and the LLM to work with in the future, etc

Is this replacing my thinking? I am not sure. I suppose I would have learnt a lot more about compilers/transpilers had I preserver through it for months with manual writes and rewrites but I would solely be working on this. Instead, I also had some time to write a custom NFS server support for a custom filesystem in Golang.

That why I don't use AI for any personal projects, I like to keep my mind sharp. Unless it's a projects that incorporates AI in some way, but don't use AI to code it. But at work I don't care, I do what I am paid for, if my manager wants me to entirely vibe code using Claude, his choice, I will not be the one paying for technical dept that creates.

No, AI is not creating that group of people. They already existed. They were the people who would google for StackOverflow snippets and copy+paste them without even reading the entire snippet, much less understand them. Same people, new tool.

No one uses it this way, despite what people say. They hit any sort of wall and then ask the robot. Thought ends.

> To be very frank if professional with 10 year experience they know the flow and logic to code if they use the AI they can make the code and improve they way they code but if new bee is coding he doesn't what the flow or logic he simply copy paste AI won't allow those people to think.

This is true. Speaking only based on personal experience. My team had started treating AI like a super intelligent being.

“AI suggested we do it that way”

And we’ve been degrading our systems rapidly for last several weeks. We’ve decided to pause and reflect and change how we use AI on tasks that are not dead simple.

> There is No Shortcut to Judgment

> This is the part that some people may not want to hear --

> There is no generated explanation that transfers mastery into your brain without you doing the work. > There is no way to outsource reasoning for long enough that you still end up strong at reasoning.

This is in relation to early-career engineers, but I wonder why people think this won't apply to mid- and late-career engineers. Are they not also constantly learning things on the job? Are they not thus shortcutting their own understanding of what they are learning day-to-day?

This is so spot on and I’ve been harping on this for about two years based on my own professional experiences. The surprising thing, though, is that upper management is ostensibly cool with incompetent people using AI to produce things that are clearly not accurate and have no idea whether it is or not. I believe this is because upper management themselves believe AI is much more accurate in its current form than it is. It’s not clear what if anything will change this but I believe many organizations are rotting from within because they no longer have stringent requirements.

I think the great advantage of AI in software is that it enables you to create code faster. I think that the great disadvantage is that it tempts you to create code incredibly faster.

AI is creating problems. This isn’t one of them. Engineers are going to now think at a higher level of abstraction. No one misses coding in assembly.

AI isn’t creating the problem, it is just showing the problem. Those who did not want to learn before AI did so reluctantly, mixing Google and SO. Now they ask AI. An existing problem found a new solution.

Personally, I really enjoy using AI. I have created my own cascade workflow to stop myself from “asking one more question”. Every session is planned. Claude and Codex can be annoying as hell (for different reasons). Neither is sufficiently smart for me to trust them. I treat them as junior devs who never get tired, know a lot of facts but not necessarily how to build.

Before AI I would spend multiple days mapping out my database tables and queries while now I ask AI to propose multiple different approaches and I pick the best one. But then on the other hand I’m working on 10 features at the same time and have to carefully look through them. But I can see that I’m totally dependent on the AI now. Creating a full plan by yourself feels like a waste of time, since you know the AI can create the same or better plan in a split second. So when Claude is down, I end up not being productive at all.

https://news.ycombinator.com/item?id=47916430 Check this out on LLMS security.

Very apt headline, IMHO.

I have been an ardent opponent of AI since it came up a few years back. I refuse to vibe code and I refuse to let AI think for me. I won't be an AI controller.

However, two days ago I found a nice, personal use case for AI: Advanced writing checks (grammar checks, mostly, and some rewordings) in Word using a rather expensive app.

I write a lot of US English, despite it not being my native language, and AI is now helping me to write much better than I did before. Also, I discovered that I am much worse at writing Danish than I was believing. In fact, I think I am better at writing US English than at Danish, that's a bit surprising as I am a Dane.

No AI was used during the writing of this entry, but I dearly love the writing tool already! I have heard similar stories from friends who say that AI is very good at summarizing long documents and stuff like that.

So, I personally think that AI CAN elevate one's thinking. I am learning more about Danish and US English grammar every day, now, than I did during a decade before. Writing is suddenly so fun because it involves growing my skills.

Is it wise to understand everything that AI does for you?

Let’s say a person has 10 units of learning per week. Is the author actually claiming that that person must not deliver any results beyond their 10 units?

It makes some sense to have say 20 units of results and prioritize which ones to fully comprehend.

I suspect APIs / libraries / languages / platforms will have more churn due to AI. New platform new system need to learn. Once every 5 years might become every year or even more frequent. That would be a sort of inflation of knowledge and skills. It would affect the decision making about how to spend one’s 10 units per week.

Wrote a similar take on it here:https://thefriendlyghost.nl/chinese-room-ai/

CoRecursive had a really good episode about this last August:

"Coding in the Red-Queen Era" https://corecursive.com/red-queen-coding/

Hard disagree. I feel like I'm thinking a lot more now because I have so many parallel projects going on at the same time. AI has allowed me to really, truly create in a way that I've never done before. Yes, my coding skills probably aren't as sharp as they used to be, but my system design skills are at an all time high. Don't blame the tool.

This is a huge concern and I fully agree with the post. Even though one might think I am not fully giving into AI, this was always the case etc. It still affects YOU and everyone else. 1. Software, often, isn't built in vacuum. Lots of companies are shoving AI down throats like it or not. Most Bigtech is heavily using metrics to get to 100% AI generated code. Reviewing is a nightmare. 2. New entrants (new grads etc) are largely AI first and are losing out on the safety and reliability aspects that are enforced automatically when you learn coding without AI.

IMO, teams need to agree on a set of principles on AI usage, concrete examples of where and how to use it. Perhaps its much more useful in parts of your system that's faster evolving and doesn't have too much core logic like testing frameworks etc

Simply discarding it as 'yet another tool' is part of the problem.

This is why I feel like its fine that AI stay as inaccurate as it is.

I learn so much arguing with it.

> split people into two nebulous groups

shows both groups using AI differently. Hard to continue reading the article that excludes your group entirely.

I don’t get why we shouldn’t outsource our thinking to the AI. As it becomes more capable, eventually it will be more competent than the average engineer. At that point companies should be _requiring_ the AI to make the larger decisions. By the end of this year AI might be better than all but the very best engineers. Then what?

> Going back to the analogies: This is like copying answers through university and then showing up to a job that requires independent thought.

That's exactly what is happening now. I wouldn't even call it an analogy, I'd call it an example of where AI is already having a baleful effect. FWIW I don't disagree with the article's thesis or the examples: yes, absolutely, if used well AI can elevate engineers in exactly this way and it behooves us engineers to use it in that way. We can also say that the deliberate design of the AI systems we are constantly being exhorted to use inclines them towards work-slop and abdicated thinking.

On the point of avoiding the struggle of learning, I think it's easy to swing too far the other direction and go back to not using modern development tools. I think it is doing a new learner a disservice by saying something like "don't use GDB/REPL/AI tool to learn, since you'll never learn the fundamentals". I think all of these tools allow for learning, if that's how the learner engages with them. So I hope that AI becomes integrated in the learning process, as far as it accelerates and doesn't replace understanding.

A.I. is creating engineers who can't WORK without it

Absolutely. When used correctly, it can become a tool for pulling our minds out of the gutter of pedantic pocket lint and distracting ephemera and keep it in a space where it is intellectually rewarding and fruitful. It can help you grasp a code base more quickly. It can help you debug things more effectively. But that's up to how you use it.

If all you do is point your LLM at your Jira tickets, then you are failing to be an engineer. I mean, if that's all you are doing, then who needs you? One of the most important things to learn is what the right questions to ask are and what the right decisions to make are when guiding the LLM, as well as the ability to judge the output it produces.

Theory of Bounded Rationality and its implications is something they should teach everyone.

For couple of last weeks, I use AI to speedup my thinking process. Instead of think about something to come up to conclusion, I let AI brainstorm for me and then select. Not for everything, but I found it faster with AI. Having taste on select the ai output is important though.

I’ve never been busier and more challenged than I am now.

Employees should elevate your thinking not replace it.

Yes.... and I can't think without compiled languages. Missed out on assembler.

Becoming dependent on a technology is to be expected. I'm pretty sure 95% of us are dependent on packaged meat and don't know how to hunt.

I think there are engineers that can’t think without AI. But the best think with it. Unfortunately, we are now living in a day and age where simply ignoring AI is no longer an option.

It’s weird I have basically a free private tutor in any subject and I use it a lot.

Yet nothing has actually changed.

95% of the population is educated to think inside of the box and just rely on repetition/memorization. There’s not a lot of thinking happening in this world outside of a very small group of people. AI is not going to change that reality at least not until we educate our children for the AI age.

For all we know, we're in the early stages of making traditional (software) engineering obsolete. As in, we don't know if the role of software engineer as we know it today will still exist in 10-15-20 years.

I mean, right now we're at the stage where any user can get AI to make you software to solve very specific things - almost no technical knowledge needed.

My prediction is that first will software engineers be rendered obsolete. After that, small businesses will disappear, as users can simply get those products/services directly via AI.

We are in a transition phase where you need systems and coding skill but you can't be sufficiently productive without AI.

First, it was pencil and paper. Then it was calculators. Then computers! It’s a slippery slope, this technology business.

Meh, there’s plenty that rise in their careers while being mediocre.

‘AI’ is my newest litmus test for whether who I’m engaging with should be taken seriously or not.

‘AI’ doesn’t exist, and LLMs have vanishingly narrow legitimate justifiable use cases. Any output from one is intrinsically, explosively, imprecise, and can’t be trusted to be build upon without specialist treatment. I’m yet to identify any application of a LLM which can rationally be mistaken for intelligence.

Anyone who persists in referring to LLMs as ‘AI’ is either betraying they don’t understand what they’re talking about, or they’re invested too deeply in an active grift.

Huberman: Your brain has a region that only grows when you do things you don't want to do

...or as I interpret it your brain grows only when it does things that are difficult.

If you remove the difficulty, it will atrophy into a hum of a mindless chit-chat.

Engineering the data structures and control flows from scratch is a completely different than asking an LLM to scaffold them for you.

Bellissimo