rafterydj

Maybe this is me being a little wet behind the ears, but I don't know if lifestyle businesses are really possible to start at the moment, given the uncertainty of the current software sector.

See this thread from a few days ago: https://news.ycombinator.com/item?id=48118727

The economics of software creation is changing, so it stands to reason how people engage with software will change too. Finding a niche may be a game of luck more than observation/perspiration at this stage, similar to discovering oil on your "barren" property rather than building a farm. As someone who's generally independent, though: I'd love to be wrong here!

That's really interesting. Are there any things you advocate for with respect to curtailing those practices? I hesitate to throw all liability on the individual, but I don't see how we can even legislate this category of behavior, much less enforce regulations on them.

+1 for any mention of Fred Brooks. I like your point about software as a whole not being a bottleneck. In the 1970s the hardware was co-evolving with business uses (it still is, but constraints were much more severe) leading to large headcounts on software projects that _absolutely_ had to work and _absolutely_ required uncommon expertise. Most people had no concept of a computer's capabilities, computer science was not as widely distributed.

One thing that I would point to today to show that the landscape is different - the average programmer/engineer/developer today has no actual admin staff. Fred Brooks' example team setup of "The Surgical Team" has more support staff than programmers. Anyone who responds to the questions like "who manages the calendar" and "who manages the documentation" will state that the engineers doing it themselves offer the best results. Same goes for designing test cases, performing rollbacks, etc.

The fact of the matter is that any self respecting engineer today works in an environment where pro-activity and self-sufficiency are prerequisites. Managing your calendar and workload, communicating to leadership and users, these are all common tasks that would have been another person a generation ago.

So when discussing writing code more efficiently and aiding in software development, what I am essentially seeing is more people trying everything they can to offload work that used to be another person's job anyway. If you care about communication - you offload coding standards. If you care about security - you offload feature refactors, and so on.

In my opinion, I think that at some point we'll either realize that we need highly competent people _and also_ regular people to help us ensure the work gets done to a good standard. Or, we will each eventually survive by working alone in a room with a suite of AI tools, and wonder why we're still making software in the first place.

Not sure why you're being downvoted, your comment seems interesting to me.

> Hacker news and r/programming is only good to get general ideas and keep up-to-date. The comments are almost worthless.

LOL can't disagree with that opinion.

For my money, while surely it must have been jarring, that experience would seem to say that on-device LLMs are more important programming tools than package repositories.

As another commenter said, the affordability of LLM subscriptions (or, as others are predicting, the lack thereof) is the primary concern, not the technology itself stealing away your skills.

I am far from the definitive voice in the does-AI-use-corrupt-your-thinking conversation, and I don't want to be. I don't want LLMs to replace my thinking as much as the next person, but I also don't want to shun anything useful that can be gained from these tools.

All that said, I do feel that perhaps "dumber" LLMs that work on-device first will allow us to get further and be better, more reliable tools overall.

Man, I completely agree with your thinking here. I've been trying to be more active in online communities, to try to discuss this exact idea.

LLM code can be leveraged, but pretending that tokens are just going to turn into money printers at some point is not productive. The primary source of software's value to an end user is the thought that was placed into it. Where does that go for the AI-natives? As you say, they are seemingly brute forcing software engineering, at least so far.

One thing I have been considering is how LLMs primarily change the "build vs buy" calculus for a fair number of software niches, particularly things like developer tooling and small libraries and packages. Partially due to a projected increase in supply chain attacks, and partially due to the changing standards of engineers. There's no longer anything stopping someone from working with an ugly or clunky syntax, presuming it's a well documented standard. So many "developer experience" tools are going to hit this - Tailwind primarily comes to mind.

It's a sort of "erosion" of niches in the current landscape - although to me this does not really work out for the worse in the long term, since again, the thinking in the process will need to just go somewhere else.

I feel the future includes the sentiments you describe. It was a little before my time professionally, but I grew up reading that kind of thinking.

I do think that the open web stuff, decentralized, or at least more decentralized than currently, is the path forward. I've been reading about the AT protocol and it recently becoming an official working group with the IETF.

I feel a second order effect of making decentralized social networking easier, is making individuals more empowered to separate from what they don't believe in. The third order effect is then building separate infrastructure entirely.

As sad as that can be - in my personal opinion it runs the risk of ending the "world wide" part of the web - it appears to be the only way society can avoid enriching the few beyond reason.

Well, redistributing their money is (in some cases disingenuously) exactly how they are able to pitch investors. "Sure, value my company at $10B and my shares make me $2B, but we're alllllll gonna make money when hit AGI!!!" That kind of thing.

Yeah, LOL. "Nothing leaves your machine except network payloads containing all of your personal data." Private and secure!

ChatGPT 3.5 came out coming on 4 years ago now. I don't think a human generation (~20-30 years) needs to be the benchmark here, but new juniors in the industry for a handful of years can be said to be a whole "generation". That how I was reading OP.

No, but what else is there to do?

If, despite best attempts for me to communicate facts to them within our common language, they still can not recognize basic truth or fact from their subjective truth? I don't really see that a problem for the speaker, but a problem for the listener.

That's no way that the opposite expectation can scale as a society. Otherwise we would all need to validate everyone else's words constantly with primary source documents. There must be some level of trust in order to communicate efficiently, surely.

Stuck it on my calendar, looking forward to it.

This reads like an LLM plagiarizing this video from Kurzgesagt:

https://youtu.be/pP44EPBMb8A?si=fSwWPOCnCsC1QEny

No, turning it around doesn't work because it's cause and effect.

"Present the facts and all the people will cheer and support stop using coal" -> correct

"If not it means stopping using coal is a bad idea?" -> incorrect, because people are against switching to renewables because of lies, not because of facts

Unsure why you're getting downvoted. I know politics is generally frowned upon here but this is absolutely relevant to the conversation.

Well, on the software design side, there's plenty of scenarios where undocumented behavior crops up on unexpected network interruption. In the example above, Windows can even pre-download updates on metered connections during one time period, then install those updates during another. The customers really can't take the blame for that, IMO.

I think overall society has rapidly deteriorated in software quality and it is mostly because of the devaluing of software design. No one expects quality from software, everyone "understands there are bugs", and some like to take advantage of that. And so the Overton window gets pushed in the direction of "broken forever good luck holding the bag if you use it" rather than the more realistic "occasionally needs to restart IFF you hit an issue and it takes less than <10 seconds and has minimal data loss".

I don't disagree about the core CS fundamentals - 100% the same page. I suppose this really boils down to a difference in what constitutes "training/education".

Any $PROGRAMMER_TITLE worth their salary can learn a new stack for a project, because they know the fundamentals. BUT there's still a lead time on being comfortable with new languages, frameworks, problem domains, etc. It's this kind of time and effort that I am trying to get at when discussing companies paying for training/education. It can be worth investing in your people if your goals are longer horizon.

I don't think it makes sense for companies to pay for their employees to learn basic data structures or other "prerequisite" fundamentals, though. That would be a large investment!

I've definitely felt this kind of way in the past. But these days I'm not so sure.

Setting aside the AI point about it, the idea of people becoming essentially irrelevant to the economy is an indictment on society. But I'd argue that the indictment really is towards what constitutes measurement in the economy. Not an indictment on society itself, or technology.

Sure, someone may not spend much money or produce much money, but if they produce scientific research or cultural work that is intangibly valuable it is still valuable regardless of whether economists can point to a metric or not. Same goes for the infinite amounts of contributions to our world from nature: what is the economic value of a garden snake or a beetle? A meaningless question when the economy can only see things in dollars.

I agree - I was mostly trying to think of an example against OP's rather facetious attitude towards the time and effort required to maintain engineering performance.

In my experience, a lot of the Rust fighting with the borrow checker is really just enforcing better quality code I should've been writing anyway.

Point still stands. You're going to take up the mantle for suggesting a computer science degree from 2000 completely qualifies someone for work in 2026? No further education needed?

How wildly dismissive of the foundation of the X$ billion dollar software industry. You think humans just stumbled into writing code by accident or something?

How does building agentic systems, a "really hard" problem, not just end up a "regular code" problem? Because that is what it is. A distributed systems problem with non-deterministic run lengths. How do you switch agent contexts? Similar to how you solve regular program context switching. How do you search tool capabilities and verify them? How do you effectively manage scheduled tasks?

Oh, look, you've just invented the operating system kernel. Suddenly, those 'dozen or two' experts don't seem so archaic after all!

This argument falls apart if you consider what field we're talking about. At what point would going to school for 5 years give you the whole education you actually needed? Does learning C in 1995-2000 prepare you for Rust in 2026? No, and it shouldn't, but work needs done, so _yes_ there is a dollar amount of value for educating your workforce that has already been vetted and already knows the context for your business goals. Asking what that number is completely misses the point.

I mean, sure, for programming macros. Or programming quick scripts, or type-safe or memory-safe programs. Or web frontends, or a11y, or whatever tasks for which people are using AI.

But if you peel back that layer to the point where you are no longer discussing the code, and just saying "code X that does Y"... how big is X going to get without verifying it? This is a basic, fundamental question that gets deflected by evaluating each case where AI is useful.

When you stop being specific about what the AI is doing, and switch to the general tense, there is a massive and obvious gap that nobody is adequately addressing. I don't think anyone would say that details are irrelevant in the case of life-threatening scenarios, and yet no one is acknowledging where the logical end to this line of thinking goes.

I see this line of thought put out there many times, and I've been thinking: why do people do anything at all? What's the point? If no one at all is even reviewing the output of coding agents, genuinely, what are we doing as a society?

I fail to see how we transition society into a positive future without supplying means of verifying systemic integrity. There is a reason that Upton Sinclair became famous: wayward incentives behind closed doors generally cause subpar standards, which cause subpar results. If the FDA didn't exist, or they didn't "review the output", society would be materially worse off. If the whole pitch for AI ends with "and no one will even need to check anything" I find that highly convenient for the AI industry.

Hey look, someone else has the exact same problem I do! I even use Excalidraw for diagramming as well, and have been wondering about how best to generate them according to some kind of binary format.

I definitely think there's a middle ground here, that the commenter to which you are replying may also be alluding. If a human is scanning resumes, job titles tend to be more important than the company, although both are obviously relevant.

So yes, if one is "Senior VP - Engagement Optimization" at e.g. Draft Kings, that would imply a level of culpability for "gambling experience = do not hire".

But if the title is "call center support - kelshi - 6 mo. contract"? Sure. I don't think the policy needs to be as stringent as all that.

Not necessarily disagreeing with either perspective, since they don't seem incompatible to me.

What an interesting glimpse into the blogosphere. That post in particular is interesting, given the much larger discussions that followed it on essentially the same topic: how to decide what people can and can not say when there are those who ruin the commons. I'm thinking of Twitter/X's Community Notes feature and the many reputation mechanisms people put in place, and the subsequent griping of community politics that arise from those mechanisms...

Hey, that sounds like OpenAI!

Super interesting. I don't know why, but something about this comment made something click for me, as an "AI fatigued" engineer.

From the view you describe, it seems AI just lets you experiment faster, when all you want to do is experiment. You find product market fit easier, you empower designers more, etc. Much easier to iterate and find easy wins from alternative designs - as long as your fundamentals work!

Only problem is that you are experimenting in public, so the massive wave of new AI generated features come to the public from everywhere at once. Hence the widespread backlash.

Not to mention, the core job function when you are experimenting is different from what defines a lot of hard technical progress: creating new technologies, or foundational work that others build on, is naturally harder and slower than building e.g. CRUD services on top of an existing stack. Deep domain expertise matters for selling, deep programming expertise matters for stability. I don't know, curious where the line will end up getting drawn.