How many kernel devs does the world need? A dozen or two?
It will be the same with software. AI will be writing and consuming most software. We will be utilizing experiences built on top of that, probably generated in real time for hyper personalization. Every app on your phone will be replaced by one app. (Except maybe games, at least for a short while longer).
Everyone's treating writing code as this reverent thing. No one wrote code 100 years ago. Very few today write assembly. It will become lost because the economic neccesity is gone.
It's the end of an era, but also the beginning of a new one. Building agentic systems is really hard, a hard enough problem that we need a ton of people building those systems. AI hardware devices have barely been registered, we need engineers who can build and integrate all sorts of systems.
Engineering as a discipline will be the last job to be automated, since who do you think is going to build all the worlds automation?
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!
Does it even make sense to build everything on top of machines that are 70% reliable? The sheer orchestration and validation overhead at scale risks being more expensive than just keeping most software engineers and having them manage a few AI agents.
Also, 200 years ago we didn't have bike mechanics. Car mechanics. Boat mechanics. Plumbers. Electricians. Not all new professions fade away.
Every problem you described is solvable and while it may not be solved right now or even in 6 months it'll probably be solved within 18 months. It's just scaling and tuning the models
You can’t “tune models” to get people willing to get on a zoom call with an agent and the agent asks them questions and talk through strategy and understand human emotions.
Are they also going to interact with the model for a design review session?
Tell the model where it got it wrong and the model is going to make the changes?
In 18 months AI agents will be able to accurately infer people's emotional state from the subtle facial expressions they make in a sales meeting, in real time?
I deleted vscode and replaced with a hyper personal dashboard that combines information from everywhere.
I have a news feed, work tab for managing issues/PRs, markdown editor with folders, calendar, AI powered buttons all over the place (I click a button, it does something interesting with Claude code I can't do programmatically).
Why don't I share it? Because it's highly personal, others would find it doesn't fit their own workflow.
Technical people (which is by far the minority of people out there) building personal apps to scratch an itch is one thing.
But based on the hype (100x productivity!), there should be a deluge of high quality mobile apps, Saas offerings, etc. There is a huge profit incentive to create quality software at a low price.
Yet, the majority of new apps and services that I see are all AI ecosystem stuff. Wrappers around LLMs, or tools to use LLMs to create software. But I’m not really seeing the output of this process (net new software).
I worked in an industry for five years and I could feasibly build a competitor product that I think would solve a lot of the problems we had before, and which it would be difficult to pivot the existing ones into. But ultimately, I could have done that before, it just brings the time to build down, and it does nothing for the difficult part which is convincing customers to take a chance on you, sales and marketing, etc. - it takes a certain type of person to go and start a business.
Nobody’s talking about starting businesses. The article is specifically about pypi packages, which don’t require any sales and marketing. And there’s still no noticeable
uptick in package creation or updates.
There is no money in mobile apps. It came out in the Epic Trial that 90% of App Store revenue comes from in app purchases for pay to win games. Most of the other money companies are making from mobile are front end for services.
If someone did make a mobile app, how would it get up take? Coding has never been the hard part about a successful software product.
I think this is the great conundrum with AI. I find it's most useful when I build my own tools from models. It's great for solving last-mile-problem types of situations around my workflow. But I'm not interested in trying to productize my custom workflow. And I've yet to encounter an AI feature on an existing app that felt right.
Problem is that all these companies trying to push AI experiences know that giving users unfettered access to their data to build further customization is corporate suicide.
> Yet, the majority of new apps and services that I see are all AI ecosystem stuff.
The same was true of all this computer science stuff too. We built parsers, compilers, calculators, ftp and http, all cool stuff that just builds up our own ecosystem. Look how that turned out.
An ecosystem has to hit a critical mass of sophistication before it breaks out to the mainstream. It's not going to take very long for AI.
Why on earth would you publish and monetize software anybody can reproduce with a $20 subscription and an hour of prompting? Why would you ever publish something you vibe coded to PyPI? Code itself isn’t scarce anymore. If there is not some proprietary, secret data or profound insight behind it, I just don’t think there is a good reason to treat it like something valuable.
> But based on the hype (100x productivity!), there should be a deluge of high quality mobile apps, Saas offerings, etc. There is a huge profit incentive to create quality software at a low price.
1. People aren't creating new apps, but enhancing existing ones
2. Companies are less likely to pay for new offerings when the barrier to entry is lowered due to AI. They'll just vibe code what they need.
I don't think the 2nd point will make a huge impact on software sales. Who is vibe coding? Software developers or business types? They aren't going to vibe code a CRM, or their own bespoke version of Excel, or their own Datadog APM.
Maybe they will vibe code small scripts, but nobody was really paying for software to do that in the first place. Saas-pocalypse is just people vibe investing, not really understanding the value proposition of saas in the first place (no maintenance, no deployments, SLAs, no database backups, etc).
Perfect example of what you’re talking about: today a coworker of mine showed off a vibecoded data viewer app that lets him view our analytics in a way that works well for his job, using our analytics platform’s API. A nice little personal productivity boost for him, but not something that will ever replace the analytics platform itself.
> Wrappers around LLMs, or tools to use LLMs to create software. But I’m not really seeing the output of this process
Because it's better to sell shovels than to pan for gold.
In the current state of LLMs, the average no-experience, non-techy person was never going to make production software with it, let alone actually launch something profitable. Coding was never the hard part in the first place, sales, marketing & growth is.
LLMs are basically just another devtool at this point. In the 90s, IDEs/Rapid App Development was a gold rush. LLMs are today's version of that. Both made developer's life's better, but neither resulted in a huge rush of new, cheap software from the masses.
For SaaS, the bottleneck is still access to data. Everything else already has been made in the past 5-10 years, so if you can't find a way around data moats you don't really have a product 99% of the time - especially now that people can vibecode their own solutions (and competitors.)
Beyond that, marketing is harder than ever. Trying to release an app on Shopify app store without very strong marketing usually just means you drop it into a void. No one trusts any of the new apps, because they're inevitably vibecoded slop and there's no way to share your app on social media because all the grifting and shilling have totally poisoned that avenue.
Take a look at Show HN now - there are tons of releases of apps every day, but nothing gets any traction because of the hostile/weird marketing environment and general apathy. Recently, I saw the only app to graduate from New Show HN likely used a voting cartel to push it to the top. And take a guess at what that app did? It summarized HN's top stories with an AI. Something any dev could make in about 10 minutes by scraping/requesting the front page and passing it through an LLM with a "summarize this" prompt.
The entire "indiehacker" community is just devs shilling their apps to each other as well. The entire space is extremely toxic, basically. Good apps might get released but fall into a void because everyone is both grifting and extremely skeptical of each other.
Well it’s mostly explained by the fact that most people lack imagination and can’t hold enough concepts about a particular experience to think about how to re-imagine it, to begin with.
Oh and sadly, llm’s are useless for the imaginative part too. Shucks eh.
I have a list of ideas a mile long that gets longer every day, and LLMs help me burn through that list significantly faster.
However, the older I get, the more distraught I get that most people I meet "IRL" are simply not sitting on a list of problems they simply lack time to solve. I have... a lot of emotions around this, but it seems to be the norm.
If someone doesn't see or experience problems and intuitively start working out how they would fix them if they only had time, the notion that they could pair program effectively ideas that they didn't previously have with an LLM is absurd.
> most people I meet "IRL" are simply not sitting on a list of problems they simply lack time to solve. I have... a lot of emotions around this, but it seems to be the norm
This sounds unnecessarily judgmental. Doing this is your hobby. Other people have different ways they want to spend their time. That doesn't make you superior, just different.
You're describing arrogant superiority, which is a real thing. It is definitely me sometimes! I can own that.
What I'm describing is an observation that despite my closely held progressive ideals, most people simply do not appear to see the world through the lens of "lots of things could be better and I see several ways to start fixing them".
I could say a lot of [probably shitty and judgmental] things about perhaps why this divide exists and the myth of the wisdom of crowds vs the genius inventor.
We can concede that all great ideas are inevitably built on the shoulders of previous great ideas by people who often go uncredited - bless the lab techs - but this thread is about the fact that most people aren't even trying to be near where the innovations happen.
Yeah and frankly the innovation would occur irrespective of llm’s.
Would it be harder? Sure. And perhaps the difficulty adds an additional cost of passion being a necessary condition to embark on the innovation. Passion leads to really good stuff.
My personal fear is we get landfill sites of junk software produced. To some extent it should be costly to convert an idea to a concept - the cost being thinking carefully so what you put out there is somewhat legible.
As I’ve said in my other post, I’m very confident that imagination is the true bottle neck.
Writing lines of code? Nope. If one can imagine… trust me, writing lines of code is trivial.
Most people have no imagination. So sure they can produce more stuff with llm’s but it’ll just be mostly garbage.
Perhaps they can produce some peculiar workflow that works ‘for them’. Sure. But I think about the money invested into the LLM-based projects and I highly doubt we are going to see any returns that justify the spend. What we are going to see is a felling on the profession of software engineers, since the pipe dream of AGI isn’t coming and imagination is scarce.
Most businesses do not have the capacity to use LLMs to produce software. If you have an idea that you can create into real high quality software that there is a demand for, then you should absolutely do it.
This is probably my favorite gain from AI assisted coding: the bar for "who cares about this app" has dropped to a minimum of 1 to make sense. I recently built an app for grocery shopping that is specific to how and where I shop, would be useless to anyone other than my wife. Took me 20 minutes. This is the next frontier: I have a random manual process I do every week, I'll write an app that does it for me.
More than that. Building a throwaway-transient-single-use web app for a single annoying use kind of makes sense now, sometimes.
I had to create a bunch of GitHub and Linear apps. Without me even asking Codex whipped up a web page and a local server to set them up, collecting the OAuth credentials, and forward them to the actual app.
Took two minutes, I used it to set up the apps in three clicks each, and then just deleted the thing.
Same energy here. I was sitting on 50+ .env files across various projects with plaintext API keys and it always bothered me but never enough to actually fix it. AI dropped the effort enough that I just had a dedicated agent run at it for a few days — kept making iterations while I was using it day to day until it landed on a pretty solid Touch ID-based setup.
This mix of doing my main work on complex stuff (healthcare) with heavy AI input, and then having 1-2 agents building lighter tools on the side, has been surprisingly effective.
That's fine and all, but how much are you ready to pay to Anthropic and OpenAI to be able to do this? Like, is it worth 100 bucks a month for you to have your own shopping app?
Haha great. I guess my wider point is that most people won't be ready to pay for it, and in the end there will be only two ways to monetize for OpenAI et al: Ads or B2B. And B2B will only work if they invest a lot into sales or if the business owners see real productivity gains one the hype has died one.
It's not worth 100 bucks a month for me to have my own shopping app, but maybe it's worth 100 bucks a month to have ready access to a software garden hose that I can use if I want to spew out whatever stupid app comes to my mind this morning.
I'd rather not pay monthly for something (like water) that I'm turning on and off and may not even need for weeks. But paying per-liter is currently more expensive so that's what we currently do.
I think the future is going to be local models running on powerful GPUs that you have on-prem or in your homelab, so you don't need your wallet perpetually tethered to a company just to turn the hose on for a few minutes.
Me, and photo editor tool to semi-automate a task of digitizing a few dozen badly scanned old physical photos for a family photo book. Needed something that could auto-straighen and auto-crop the photos with ability to quickly make manual adjustments, Gemini single-shotted me a working app that, after few minutes of back-and-forth as I used it and complained about the process, gained full four-point cropping (arbitrary lines) with snapping to lines detected in image content for minute adjustments.
Before that, it single-shot an app for me where I can copy-paste a table (or a subsection of it) from Excel and print it out perfectly aligned on label sticker paper; it does instantly what used to take me an hour each time, when I had to fight Microsoft Word (mail merge) and my Canon printer's settings to get the text properly aligned on labels, and not cut off because something along the way decided to scale content or add margins or such.
Neither of these tools is immediately usable for others. They're not meant to, and that's fine.
My buddy and I are writing our own CRUD web app to track our gaming. I was looking at a ticketing system to use for us to just track bug fixes and improvements. Nothing I found was simple enough or easy enough to warrant installing it.
I vibe'd a basic ticketing system in just under an hour that does what we need. So not 20 mins, but more like 45-60.
I built a small app to emit a 15 kHz beep (that most adults can't hear) every ten minutes, so I can keep time when I'm getting a massage. It took ten minutes, really, but I guess it's in the spirit of the question.
For 20 minutes of time, I had a simple TTS/STT app that allows me to have a voice conversation with my AI assistant.
I've been getting close to that myself, I've been using VSCode + Claude Code as my "control plane" for a bunch of projects but the current interface is getting unwieldly. I've tried superset + conductor and those have some improvements but are opinionated towards a specific set of workflows.
I do think there would be value in sharing your setup at some point if you get around to it, I think a lot of builders are in the same boat and we're all trying to figure out what the right interface for this is (or at least right for us personally).
I'm guessing it's not a hard coded function, the button invokes. Instead it spawns a claude code session with perhaps some oredefined prompts, maybe attaches logs, and let's claude code "go wild". In that sense the button's effect wouldn't be programmatical, it would be nondeterministic.
I have had the thought to write little "programs" in text or markdown for things which would just a chore to maintain as a traditional program. (I guess we call them "skills" now?) Think scraping a page which might change its output a bit every so often. It the volume or cadence is low, it may not be worth it to create a real program to do it.
But it requires A LOT of work to make sure it is actually safe for people and organizations. And no, an .md file saying “PLEASE DONT PWN ME, KTHX” isn’t it at all. “Alignment” is only part of the equation.
This all reads, to put it politely, like it's being written by someone who is not all there and being convinced by letting AI write everything that they have a coherent idea. Or just trying to put a bunch of buzzwords together to get people to buy something. Do you have any code or actual demos of "your" "work" to share? Your homepage's "See It in Action" section is just more AI slop articles in video form.
Kind of. I'm finding that my terminal window in VSCode went from being at the bottom 1/3rd of my screen to filling the whole screen a lot of the time, replacing the code editor window. If AI is writing all of your code for you based on your chat session, a lot of editing capabilities aren't needed as much. While I wouldn't want to get rid of it entirely, I'd say an AI-native IDE would deemphasize code editing in favor of higher-level controls.
Sorry, I'm not sure how this relates to the content of the article. Sounds like an interesting experience, but this is an analysis of the Python ecosystem pre+post ChatGPT.
One craft is automated and a new one is just beginning.
Building AI agents is really fun and the problem of having them be reliable adaptable efficient is actually really challenging and I'm having a lot of fun with it trying to figure it out.
To me it's a lot like factorio or my personal favorite Dyson sphere program where at first you do everything by hand and then you automate and then you automate the automation.
For the first time in human history we can automate intelligence with a computer but just because we can automate it doesn't mean all the good automation is good and we need engineers who can figure out how to automate it reliably scale it deploy it maintain it.
And yes eventually we will automate the automation too.
Unregulate the insurance industries problem solved. Let people actually buy insurance for it's intended purpose. No insurance company would pay these rates willingly, they do it because of all the regulations. They aren't allowed to profit normally, so they find ways around it. Just let them operate normally, like all sorts of other insurance programs.
Yeah no thanks, let’s do the tried and true universal healthcare that literally every else does. They get better results AND it’s cheaper. We’re literally paying more for something worse.
The role of an engineer is to produce software that probably works. If you are producing more bugs it's because you're skipping provability. AI is also really good at writing tests and doing test-driven development You can get 100% branching coverage. You use a secondary LLM to review the work and make sure everything follows best practices.
LLMs Can accelerate you if you use best practices and focus on provability and quality, but if you produce slop LLMs will help you produce slop faster.
I built a tool specifically for dealing with remote mcp servers via the cli. No config files needed. FUSE (and Bash) is all we need. This way we can still get benefits of discoverability of mcp endpoints, but can use cli tools and bash to do things easier.
Coz I have always done coding this way with humans I started out using LLMs to do simple bits of refactoring where tests could be used to validate that the output still worked.
I did not get the impression from this that LLMs were great coders. They would frequently miss stuff, make mistakes and often just ignore the instructions i gave them.
Sometimes they would get it right but not enough. The agentic coding loop still slowed me down overall. Perhaps if i were more junior it would have been a net boost.
It will be the same with software. AI will be writing and consuming most software. We will be utilizing experiences built on top of that, probably generated in real time for hyper personalization. Every app on your phone will be replaced by one app. (Except maybe games, at least for a short while longer).
Everyone's treating writing code as this reverent thing. No one wrote code 100 years ago. Very few today write assembly. It will become lost because the economic neccesity is gone.
It's the end of an era, but also the beginning of a new one. Building agentic systems is really hard, a hard enough problem that we need a ton of people building those systems. AI hardware devices have barely been registered, we need engineers who can build and integrate all sorts of systems.
Engineering as a discipline will be the last job to be automated, since who do you think is going to build all the worlds automation?
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