"Jobs are going to be lost unless there's somehow a demand for more applications."
That's why I'm not worried. There is already SO MUCH more demand for code than we're able to keep up with. Show me a company that doesn't have a backlog a mile long where most of the internal conversations are about how to prioritize what to build next.
I think LLM assistance makes programmers significantly more productive, which makes us MORE valuable because we can deliver more business value in the same amount of time.
Companies that would never have considered building custom software because they'd need a team of 6 working for 12 months may now hire developers if they only need 2 working for 3 months to get something useful.
> That's why I'm not worried. There is already SO MUCH more demand for code than we're able to keep up with. Show me a company that doesn't have a backlog a mile long where most of the internal conversations are about how to prioritize what to build next.
I worry about junior developers. It will be a while before vocational programming courses retool to teach this new way of writing code, and these are going to be testing times for so many of them. If you ask me why this will take time, my argument is that effectively wielding an LLM for coding requires broad knowledge. For example, if you're writing web apps, you need to be able to spot say security issues. And various other best practices, depending on what you're making.
It's a difficult problem to solve, requiring new sets of books, courses etc.
Just as a side note, at my university about half the CS people are in the AI track. I would guess that number will keep increasing. There is also a separate major that kind of focuses on AI/psychology that is pretty popular but I am not sure how many people are in it. A good number of the students have some kind of "AI startup". Also, although it violates the honor code, I would be willing to bet many students use AI in some way for doing programming assignments.
This isn't to say you are wrong but just to put some perspective on how things are changing. Maybe most new programmers will be hired into AI roles or data science.
The ask from every new grad to be assigned to ai development is unreasonable right now and they are probably hurting their careers by all going the same direction honestly. It’s a small fraction of our development efforts and we usually hire very senior for that sort of role. We still need people that can program for the day to day business needs and it’s a perfect starting role for a new grad yet almost all of them are asking for assignment to ai development.
I appreciate anyone that can utilise ai well but there’s just not enough core ai model development jobs for every new grad.
Agree and disagree. You do it need a “degree in AI”. However, you need to be using AI in your degree. Really using it.
What are those “day to day business needs” that you think people are going to do without AI?
In my view, this is like 1981. If you are saying, we will still need non-computer people for day-to-day business needs, you are wrong. Even the guy in the warehouse and the receptionist at the front are using computers. So is the CEO. That does not mean that everybody can build one, but just think of the number of jobs in a modern company that require decent Excel skills. It is not just the one in finance. We probably don’t know what the “Excel” of AI is just yet but we are all going to need to be great at it, regardless of who is building the next generation of tools.
Wouldn't the AI track be more about the knowing the internals, being able to build models, ... So in your 1981 example that would be saying about half of the people are enrolling in computer hardware courses, whereas only a fraction of those are needed?
I would assume any other CS course teaches/is going to be teaching how to use AI to be an effective software developer.
I agree with your point in general, but saying one needs to be great at using AI tools gives way too much credit to companies’ ability to identify low performers. Especially in large organizations, optics matter far more than productive output. Being able to use AI tools is quite different from saying you are using AI tools!
An actual hardcore technical AI "psychology" program would actually be really cool. Could be a good onboarding for prompt engineering (if it still exists in 5 years).
Yeah, the younguns smell opportunity and run towards it. They'll be fine. It's younguns) the less experienced folks in the current corporate world that will have the most to lose.
The really experienced of us will have made this mistake enough times to know to avoid it.
I didn’t get a smart phone until the 2010s. Stupid I know but it was seen as a badge of honour in some circles ‘bah I don’t even use a smart phone’ we’d say as the young crowd went about their lives never getting lost without a map and generally having an easier time of it since they didn’t have that mental block.
Ai is going to be similar no doubt. I’m already seeing ‘bah I don’t use ai coding assistants’ type of posts, wearing it as a badge of honour. ‘Ok you’re making things harder for yourself’ should be the reply but we’ll no doubt have people wearing it as a badge of honour for some time yet.
> I worry about junior developers. It will be a while before vocational programming courses retool to teach this new way of writing code, and these are going to be testing times for so many of them.
I don't agree. LLMs work as template engines on steroids. The role of a developer now includes more code reviewing than code typing. You need the exact same core curriculum to be able to parse code, regardless if you're the one writing it, it's a PR, or it's outputted by a chatbot.
> For example, if you're writing web apps, you need to be able to spot say security issues. And various other best practices, depending on what you're making.
You're either overthinking it or overselling it. LLMs generate code, but that's just the starting point. The bulk of developer's work is modifying your code to either fix an issue or implement a feature. You need a developer to guide the approach.
That's a broad statement. If the IDE checks types and feeds errors back to the LLM, then that loop is very well able to fix an issue or implement a feature all on its own (see aider, cline etc )
It isn't. Anyone who does software development for a living can explain to you what exactly is the day-to-day work of a software developer. It ain't writing code, and you spend far more time reading code than writing it. This is a known fact for decades.
> If the IDE checks types and feeds errors back to the LLM,(...)
Irrelevant. Anyone who does software development for a living can tell you that code review is way more than spotting bugs. In fact, some companies even have triggers to only trigger PR reviews if all automated tests pass.
Think of how much easier it is to learn to code if you actually want to.
The mantra has always been that the best way to learn to code is to read other people’s code. Now you can have “other people” write you code for whatever you want. You can study it and see how it works. You can explore different ways of accomplishing the same tasks. You can look at the similar implementations in different languages. And you may be able to see the reasoning and research for it all. You are never going to get that kind of access to senior devs. Most people would never work up the courage to ask. Plus, you are going to become wicked good at using the AI and automation including being deeply in touch with its strengths and weaknesses. Honestly, I am not sure how older, already working devs are going to keep up with those that enter the field 3 years from now.
People get wicked good by solving hard problems. Many young developers use AI to solve problems with little effort. Not sure what effect this will have on the quality of future developers.
that's basically the AI rubicon everywhere. From flying plans to programming: Soon there'll be no real fallback. When AI fails, you can't just put the controls in front of a person and expect them to have reasonable expertise to respond.
Really, what seems on the horizon is a cliff of techno risks that have nothing to do with "AI will take over the world" and more "AI will be so integral to functional humanity that actual risks become so diffuse that no one can stop it."
So it's more a conceptual belief: Will AI actually make driving cares safer or will the fatalities of AI just be so randomly stochastic that it's more acceptable.
>So it's more a conceptual belief: Will AI actually make driving cares safer or will the fatalities of AI just be so randomly stochastic that it's more acceptable.
I would argue that we already accept relatively random car fatalities at a huge scale and simply engage in post-hoc rationalization of the why and how of individual accidents that affect us personally. If we can drastically reduce the rate of accidents, the remaining accidents will be post-hoc rationalized the same way we always have rationalized accidents.
This is about the functional society where people fundamentally have recourse to "blame" via legal means one another for things.
Having fallbacks, eg, pilots in the cockpit is not a long term strategy for AI pilots flying planes because they functionally will never be sufficiently trained for actual scenarios.
By the time book comes out it's outdated. DeepSeek has its own cut-off date.
And here is the problem: AI needs to be trained on something. Use of AI reduces the use of online forums, some of them are actively blocking access, like reddit. So, for AI to stay relevant it has to generate the knowledge by itself. Like having full control of a computer, taking queries from human supervisor, and really trying to solve. Having this sort of AI actors in online forum will benefit everyone.
Before this comment is being downvoted, please note the irony. The AI models may solve some technical problems, but the actual problems to be solved are of a societal nature, and won't be solved in our lifetimes.
I agree there are hard societal problems that tech alone cannot solve -- or at all. It reminds me of the era, not long ago, when the hipster startup bros thought "there is an app for that" (and they were ridiculously out of touch with the actual problem, which was famine, homelessness, poverty, a natural disaster, etc).
For mankind, the really big problems aren't going away any time soon.
But -- and it's a big but -- many of us aren't working on those problems. I'm ready to agree most of what I've done for decades in my engineering job(s) is largely inconsequential. I don't delude myself into thinking I'm changing the world. I know I'm not!
What I'm doing is working on something interesting (not always) while earning a nice paycheck and supporting my family and my hobbies. If this goes away, I'll struggle. Should the world care? Likely not. But I care. And I'm unlikely to start working on solving societal problems as a job, it's too much of a burden to bear.
> If you ask me why this will take time, my argument is that effectively wielding an LLM for coding requires broad knowledge.
This is a problem that the Computer Science departments of the world have been solving. I think that the "good" departments already go for the "broad knowledge" of theory, systems with a balance between the trendy and timeless.
I definitely agree with you in the interim regarding junior developers. However, I do think we will eventually have the AI coding equivalent of CICD built into perhaps our IDE. Basically, when an AI generated some code to implement something, you chain out more AI queries to test it, modify it, check it for security vulnerabilities etc.
Now, the first response some folks may have is, how can you trust that the AI is good at security? Well, in this example, it only needs to be better than the junior developers at security to provide them with benefits/learning opportunities. We need to remember that the junior developers of today can also just as easily write insecure code.
If it can point out the things you may need to consider, it is already better at security than most dev teams in the world today. Deep Seek can already do that.
This is my main worry with the entire AI trend too. We're creating a huge gap for those joining the industry right now, with markedly fewer job openings for junior people. Who will inherit the machine?
Full disclosure: I am writing a chat app that is designed for software development
> It's a difficult problem to solve, requiring new sets of books, courses etc.
I think new tooling built around LLMs that fits into our current software development lifecycle is going to make a big difference. I am experiencing firsthand how much more productive I am with LLM, and I think that in the future, we will start using "Can you review my conversation?" in the same way we use "Can you review my code?"
Where I believe LLMs are a real game changer is they make it a lot easier for us to consume information. For example, I am currently working on adding a Drag and Drop feature for my chat input box. If a junior developer is tasked with this, the senior developer can easily have the LLM generate a summary of their conversation like so:
At this point, the senior developer can see if anything is missed; if desired, they can fork the conversation to ask the LLM questions like "Was this asked?" or "Was this mentioned?"
And once everybody is happy, you can have the LLM generate a PR title and message like so:
All of this took me about 10 minutes, which would have taken me an hour or maybe more without LLMs.
And from here, you are now ready to think about coding with or without LLM.
I think with proper tooling, we might be able to accelerate the learning process for junior developers as we now have an intermediate layer that can better articulate the senior developers' thoughts. If the junior developer is too embarrassed to ask for clarification on why the senior developer said what they did, they can easily ask the LLM to explain.
The issue right now is that we are so focused on the moon shots for LLM, but the simple fact is that we don't need it for coding if we don't want to. We can use it in a better way to communicate and gather requirements, which will go a long way to writing better code faster.
Yeah, it's going to suck for junior developers for a while.
The ones who are self-starters will do fine - they'll figure out how to accelerate their way up the learning curve using these new tools.
People who prefer classroom-learning / guided education are going to be at a disadvantage for a few years while the education space retools for this new world.
I think, seeing recordings of people using LLMs to accomplish non-trivial tasks would go a long way.
I’d love to watch, e.g. you Simon, using these tools. I assume there are so many little tricks you figured out over time that together make a big difference. Things that come to mind:
- how to quickly validate the output?
- what tooling to use for iterating back and forth with the LLM? (just a chat?)
- how to steer the LLM towards a certain kind of solutions?
- what is the right context to provide to the LLM? How do it technically?
I believe Simon has full transcripts for some of the projects he’s had LLMs generate the code for. You can see how he steers the LLM for what is desired and how it is course corrected.
I personally think that having hands on keyboards is still going to be imperative. Anyone can have an idea, but not everyone is going to be able to articulate that idea to an AI model in a way that will produce high quality, secure software.
I'm by no means an expert, but I feel like you still need someone who understands underlying principles and best practices to create something of value.
This assumes that prompts do not evolve to the point where grandma can mutter some words to AI that produces an app that solves a problem. Prompts are an art form and a friction point to great results. Was only some months before reasoning models that CoT prompts where state of the art. Reasoning models take that friction away.
Thinking it out even further, programming languages will likely go away altogether as ultimately they're just human interfaces to machine language.
> programming languages will likely go away altogether
As we know them, certainly.
I haven't seen discussions about this (links welcome!), but I find it fascinating.
What would a PL look like, if it was not designed to be written by humans, but instead be some kind of intermediate format generated by an AI for humans to review?
It would need to be a kind of formal specification. There would be multiple levels of abstraction -- stakeholders and product management would have a high level lens, then you'd need technologists to verify the correctness of details. Parts could still be abstracted away like we do with libraries today.
It would be way too verbose as a development language, but clear and accessible enough that all of our arcane syntax knowledge would be obsolete.
This intermediate spec would be a living document, interactive and sensitive to modifications and aware of how they'd impact other parts of the spec.
When the modifications are settled, the spec would be reingested and the AI would produce "code", or more likely be compiled directly to executable blobs.
...
In the end, I still think this ends up with really smart "developers" who don't need to know a lick of code to produce a full product. PLs will be seen as the cute anachronisms of an immature industry. Future generations will laugh at the idea that anybody ever cared about tabs-v-spaces (fair enough!).
Take for example neuralink. If you consider that interface 10 years, or further 1000 years out in the future, it's likely we will have a direct, thought-based human computer interface. Which is interesting when thinking of this for sending information to the computer, but even more so (if equally alarming) for information flowing from computer to human. Whereas today, we read text on web pages, or listen to audio books, in that future, we may instead receive felt experiences / knowledge / wisdom.
Have you had a chance to read 'Metaman: The Merging of Humans and Machines into a Global Superorganism' from 1993?
We have already entered a new paradigm of software development, where small teams build software for themselves to solve their own problems rather than making software to sell to people. I think selling software will get harder in the future unless it comes with special affordances.
I think some of the CEOs have it right on this one. What is going to get harder is selling “applications” that are really just user friendly ways of getting data in and out of databases. Honestly, most enterprise software is just this.
AI agents will do the same job.
What will still matter is software that constrains what kind of data ends up in the database and ensures that data means what it is supposed to. That software will be created by local teams that know the business and the data. They will use AI to write the software and test it. Will those teams be “developers”? It is probably semantics or a matter of degree. Half the people writing advanced Excel spreadsheets today should probably be considered developers really.
Mostly agree, even without a database-centered worldview.
Programming languages are languages to tell the computer what to do. In the beginning, people wrote in machine code. Then, high level languages like C and FORTRAN were invented. Since then we’ve been iterating on the high level language idea.
These LLM based tools seem to be a more abstract way of telling the computer what to do. And they really might, if they work out, be a jump similar to the low/high level split. Maybe in the future we’ll talk about low-level, high-level, and natural programming languages. The only awkwardness will be saying “I have to drop down to a high level language to really understand what the computer is doing.” But anyway, there were programmers on either side of that first split (way more after), if there’s another one I suspect there will still be programmers after.
No, enterprise software is typically also risk management and compliance, domains where rules rule. Someone needs to sign off on the software being up to spec and taking responsibility for failures, that's something any submissive LLM is willing to do but can't.
Maybe, but it's the same argument trickling down. You'll need the CRUD-apps because you hired Cindy to press the button, and if shit goes pear-shaped, you can point to Cindy in the post-mortem. If it's some AI agent pressing the button to egress data from the database, and there's an anomaly, then it's a systemic failure at a macro level at that company, which is harder to write a press release about.
At some point, I wonder if there will be advantageous for AI to just drop down directly into machine code, without any intermediate expression in higher-level languages. Greater efficiency?
Obviously, source allows human tuning, auditing, and so on. But taken at the limit, those aspects may eventually no longer be necessary. Just a riff here, as the thought just occurred.
In the past I've had a similar thought, what if the scheduler used by the kernel was an AI? better yet, if it is able to learn your usage patterns and schedule accordingly.
Many applications can and should be replaced by a prompt and a database. This is the nature of increased expressive and computational power. So many whip manufacturers are about to go out of business, especially those offering whips-as-a-service.
...which is a good thing. Software made by the people using it to better meet their specific needs is typically far better than software made to be a product, which also has to meet a bunch of extra requirements that the user doesn't care about.
> There is already SO MUCH more demand for code than we're able to keep up with. Show me a company that doesn't have a backlog a mile long where most of the internal conversations are about how to prioritize what to build next.
This is viewing things too narrowly I think. Why do we even need most of our current software tools aside from allowing people to execute a specific task? AI won't need VSCode. If AI can short circuit the need for most, if not nearly all enterprise software, then I wouldn't expect software demand to increase.
Demand for intelligent systems will certainly increase. And I think many people are hopeful that you'll still need humans to manage them but I think that hope is misplaced. These things are already approaching human level intellect, if not exceeding it, in most domains. Viewed through that lens, human intervention will hamper these systems and make them less effective. The rise of chess engines are the perfect example of this. Allow a human to pair with stockfish and override stockfish's favored move at will. This combination will lose every single game to a stockfish-only opponent.
But the bit of data we got in this story is that a human wrote tests for a human-identified opportunity, then wrote some prompts, iterated on those prompts, and then produced a patch to be sent in for review by other humans.
If you already believed that there might be some fully autonomous coding going on, this event doesn’t contradict your belief. But it doesn’t really support it either. This is another iteration on stuff that’s already been seen. This isn’t to cheapen the accomplishment. The range of stuff these tools can do is growing at an impressive rate. So far though it seems like they need technical people good enough to define problems for them and evaluate the output…
I tried something related today with Claude, who'd messed up a certain visualization of entropies using JS: I snapped a phone photo and said 'behold'. The next try was a glitch mess, and I said hey, could you get your JS to capture the canvas as an image and then just look at the image yourself? Claude could indeed, and successfully debugged zir own code that way with no more guidance.
I should've said I didn't do any control experiment. I looked more closely at what Claude did in another case and it was console-logging some rough features out of the canvas data that time. If it actually was "looking at" the image the first time, it had to have been through a text encoding -- I think I remember a data URL briefly starting to appear in the transcript.
GAI (if we get it) will start creating its own tools and programming languages to become more efficient. Tools as such won’t be going away. GAI will use them for the same reasons we do.
It's interesting. Maybe I'm in the bigtech bubble, but to me it looks like there isn't enough work for everyone already. Good projects are few and far between. Most of our effort is keeping the lights on for the stuff built over the last 15-20 years. We're really out of big product ideas.
That's because software is hard to make, and most projects don't make it far enough to prove themselves useful--despite them having the potential to be useful. If software gets easier, a whole new cohort of projects will start surviving past their larval stage.
These might not be big products, but who wants big products anyway? You always have to bend over backwards to trick them into doing what you want. You should see the crazy stuff my partner does to make google docs fit her use case...
Let's have an era of small products made by people who are close to the problems being solved.
Yes a capacity increase from the developer side is great but it's supply side and we need to figure out how to accelerate transforming needs into demand. This is what I foresee developers turning into (at least some capable of this). Articulating logical solutions to be built to problems and evaluating results from what's generated to ensure it meets the needs.
Aka Devs can move up the chain into what was traditionally product roles to increase development of new projects. This is using the time they have regain from more menial tasks being automated away.
That's the naiveity of software engineers. They can't see their limitations and think everything is just a technical problem.
No, work is never the core problem. Backlog of bug fixes/enhancements is rarely what determines the headcount. What matters is the business need. If the product sells and there is no/little competition, the company has very little incentive to improve their products, especially hiring people to do the work. You'd be thankful if a company does not layoff people in teams working on mature products. In fact, the opposite has been happening, for quite a while. There are so many examples out there that I don't need to name them.
Show me a company that doesn't have a backlog a mile long where most of the internal conversations are about how to prioritize what to build next.
Most companies don't have a milelong backlog of coding projects. That's a uniquely tech industry-specific issue, and a lot of it is driven by the tech industry's obsessive compulsion to perpetually reinvent wheels.
Companies that would never have considered building custom software because they'd need a team of 6 working for 12 months may now hire developers if they only need 2 working for 3 months to get something useful.
No, because most companies that can afford custom software want reliable software. Downtime is money. Getting unreliable custom software means that the next time around they'll just adapt their business processes to software that's already available on the market.
I’m more bearish about LLMs but even in the extreme optimist case this is why I’m not that concerned. Every project I’m on is triaged as the one that needs the most help right now. A world when dozen projects don’t need to be left on the cutting room floor so one can live is a very exciting place.
>There is already SO MUCH more demand for code than we're able to keep up with. Show me a company that doesn't have a backlog a mile long where most of the internal conversations are about how to prioritize what to build next.
We really are in AI moment of iPhone. I never thought I would witness something bigger than the impact of Smartphone. There are insane amount of value that we could extract out. Likely in tens of trillions from big to small business.
We keep asking how Low Code or No Code "tools" could achieve custom apps. Turns out we are here via a different route.
>custom software because they'd need a team of 6 working for 12 months may now hire developers if they only need 2 working for 3 months to get something useful.
I am wondering if it be more like 2 working for 1 month?
And this kind of fear mongering is particularly irritating when you see that our industry already faced a similar productivity shock less than twenty years ago: before open source went mainstream github and library hubs like npm we used to code the same things over and over again, most of the time in a half-backed fashion because nobody had time for polishing stuff that was needed but only tangentially related to the code business. Then came the open-source tsunami, and suddenly there was a high quality library for solving your particular problem and the productivity gain was insane.
Fast forward a few years, does it look like this productivity gains took any of our jobs? Quite the opposite actually, there has never been as many developers as today.
(Don't get me wrong, this is massively changing how we work, like the previous revolution did, and how job is never going to be the same again)
The main problem is that engineers in the Western world wont get to see the benefits themselves because a lot of Western companies will outsource the work to AI-enabled, much more effective developers in India.
India and Eastern EU will win far more (relatively) than expensive devs in the US or Western EU.
> That's why I'm not worried. There is already SO MUCH more demand for code than we're able to keep up with. Show me a company that doesn't have a backlog a mile long where most of the internal conversations are about how to prioritize what to build next.
And yet many companies aren't hiring developers right now - folks in the C suite are thinking AI is going to be eliminating their need to hire engineers. Also "demand" doesn't necessarily mean that there's money available to develop this code. And remember that when code is created it needs to be maintained and there are costs for doing that as well.
I continue to suspect that the hiring problems are mainly due to massive over-hiring during Covid, followed by layoffs that flooded the market with skilled developers looking for work.
I'd love to see numbers around the "execs don't think they need engineers because of AI" factor. I've heard a few anecdotal examples of that but it's hard to tell if it's a real trend or just something that catches headlines.
I think execs don’t see the problems we have with AI because you don’t need to be an expert to be an exec. I run into the edges of AI every day. There are things it is good at and things not so good at, and it varies from model to model and context to context (you can have two conversations with the same model, about the same thing, and get vastly different outputs; eg a test that uses different assertion patterns/libraries that are different from the rest of the project). As an “expert” or “highly skilled” person, I recognize these issues when I see them, but to a layman, it just looks like code.
Massive overhiring or not, it's the fact that many (skilled) engineers can't find a job. Many companies were shut off during the past few years and market became oversaturated over the night. Whether AI will help to correct the market creating more demand we will see but I wouldn't hold my breath. Many domain specific skills became a commodity.
We had a huge boom due to the low interest rates allowing businesses to pay developers with borrowed money, effectively operating at a loss for years on the basis of future growth. Now interest rates have risen the need to actually be profitable has caused a lot of optimization and lower hiring overall.
Where's the fact coming from, as in it's higher than before? I seem to be getting more than ever recruiting emails, and have felt out interviewing at a few places which we're very eager to find staff level talent.
Personal experience and also from many people I know around. Previously I would receive a request for an interview every two days or so. Lately, perhaps once a month, if at all. Foundational skills that I have were always scarce on the market so that makes me believe that the demand for them is now much much lower.
Another data point is that there's been ~10 companies that I have been following and all of them have been shut down in the past year or so.
And the general feeling you get from the number of HN posts from people complaining about not being able to find jobs. This certainly hasn't been like that before.
100% agree with this take. People are spouting economic fallacies, and it’s in part cause CEOs don't want the stock prices to fall too fast. Eventually people will widely realize this and by then the economic payoffs are still immense.
That's why I'm not worried. There is already SO MUCH more demand for code than we're able to keep up with. Show me a company that doesn't have a backlog a mile long where most of the internal conversations are about how to prioritize what to build next.
I think LLM assistance makes programmers significantly more productive, which makes us MORE valuable because we can deliver more business value in the same amount of time.
Companies that would never have considered building custom software because they'd need a team of 6 working for 12 months may now hire developers if they only need 2 working for 3 months to get something useful.