Feels almost too on-the-nose to write "Betteridge's Law of Headlines" but the answer is obviously no. Look no further than the farce of their made-up "graph" of cost over time with no units or evidence.
Good write-up. I don't disagree with any of his points, but does anybody here have practical suggestions on how to move forward and think about one's career? I've been a frontend (with a little full stack) for a few years now, and much of the modern landscape concerns me, specifically with how I should be positioning myself.
I hear vague suggestions like "get better at the business domain" and other things like that. I'm not discounting any of that, but what does this actually mean or look like in your day-to-day life? I'm working at a mid-sized company right now. I use Cursor and some other tools, but I can't help but wonder if I'm still falling behind or doing something wrong.
Does anybody have any thoughts or suggestions on this? The landscape and horizon just seems so foggy to me right now.
> but wonder if I'm still falling behind or doing something wrong.
This is normal with all that is going on in the industry and the AI/ML hype. But, one should not allow that to lead to "analysis paralysis".
> specifically with how I should be positioning myself. ... Does anybody have any thoughts or suggestions on this?
You have a stable job; hence your entire focus (for now) should be to "grow" in your job/organization. This means taking more responsibilities both technical/non-technical and demonstrating your long-term commitment to management. On the technical side, start with "full stack development" both frontend and backend so you can contribute end-to-end to the entire product line. Learn/Use all available tools (AI and otherwise) to demonstrate independent initiative. Step up for any tasks which might not have a owner (eg. CI/CD etc.). Keep your boss/higher-ups informed so as to maintain visibility throughout the organization. Learn more about the problem domain, interact more with Marketing/Sales so as to become the liaison between Engineering and rest of the organization/clients.
Generally, all higher management look for initiative and independent drive so that they can delegate work with the assurance that it will be taken care of and that is what you need to provide.
Use the best tools, the lowest tier of Claude Code is perfect for the stuff you do at home in the evenings and weekends. It's also by far the best at being a "pair coder" as it's chatty and tells you what it's doing and doesn't get confused if you hit ESC and tell it to do something else.
Build your own tools, need a small utility? Use an LLM to create it with you.
Create LLM-focused tools and adjust your workflows to be LLM-friendly.
I personally have a Taskfile setup that follows the same formula regardless of language. "task build" runs lint+test+build. Test and lint are kinda self-evident. All output is set to minimum, only errors are verbose (don't waste context on fancy output).
I also have tools for LLMs to use to find large code files, large and overly complex functions etc.
All project documentation lives in docs/ as markdown files with Mermaid charts.
This way I can just have the general "how to use a taskfile" instructions in my global WHATEVER.md and it'll work in every project.
Learn project management. Working with LLMs is exactly like project managing a bunch of smart and over eager junior coders who want to use every trick and pattern they learned at school for every tiny shell script.
Do a few test projects where you just pretend you're a non-techinical project lead and know WHAT you want but not HOW you want it done. Plan the project, split it into tasks (github tasks or beads[0] both work pretty well). Then have the LLM(s) tackle the tasks one by one and test the end result like a non-techical PM would do in a demo. Comment, critique and ask them to change stuff that doesn't work.
If you can afford it, bring in an outside consultant (Codex or Gemini), both of which are _really_ good at evaluating large codebases for duplication, test coverage, repetition, bad patterns etc. Give their responses verbatim to Claude and ask what it thinks about them.
Working with LLMs is a skill you just need to use to get a feel for it, it's not a science and more like an art. For example I can "feel" when Claude is doing its thing and being either overeager or trying to complete a task while ignoring the burning pile of unit tests it leaves behind and interrupt. it before it gets too far.
I don’t know if it’s 90%, but I’m shipping in 2 days things that took 2-4 weeks before.
Opus 4.5 in particular has been a profound shift. I’m not sure how software dev as a career survives this. I have nearly 0 reason to hire a developer for my company because I just write a spec and Claude does it in one shot.
It’s honestly scary, and I hope my company doesn’t fail because as a developer I’m fucked. But… statistically my business will fail.
I think in a few years there will only be a handful of software companies—the ones who already have control of distribution. Products can be cloned in a few weeks now; not long until it’s a few minutes. I used to see a new competitor once every six months. Now I see a new competitor every few hours.
This article mentions cost to ship, but ignores that the largest cost of any software project isn't consumed by how long it takes to get to market, but by maintenance and addition of new features. How is agentic coding doing there? I've only seen huge, unmaintainable messes so far.
I think this reflects one of the biggest fallacies behind LLM adoption; the idea that reducing costs for producers improves the state of affairs for consumers too. I've seen someone compare it to the steam engine.
With the steam engine, though, consumers made a trade-off: You pay less, and get (in most cases, I presume) a worse product. With LLMs and other machine learning technologies, maybe if you're paying for the software there's a trade-off (if the software is actually cheaper anyway), but otherwise it doesn't exist. It costs the same amount of money for you to read an LLM-generated article as to read a real one; your internet bill doesn't go down. Likewise for gratis software. It's just worse, with no benefit.
Hacker News is full of producers, in this sense, who often benefit from cutting corners, and LLMs allow them to cut corners, so obviously there are plenty of evangelists here. I saw someone else in this comment section mention that gamers who are not in the tech industry don't like "AI". That's to be expected; they're not the producers, so they're not the ones who benefit.
To reinforce that point: we've got the world's most prominent AI promoting company (MSFT), that has finally realized that Windows Explorer is too slow to start.
And this company, with all the formidable powers of AI behind them, can find no way to optimize that other than pre loading the app in memory. And that's for a app that's basically a GUI for `ls`
> written an entire unit/integration test suite in a few hours
It’s often hard to ground how “good” blog writers are, but tidbits like this make it easy to disregard the author’s opinions. I’ve worked in many codebases where the test writers share the authors sentiment. They are awful and the tests are at best useless and often harmful.
Getting to this point in your career without understanding how to write effective tests is a major red flag.
> I'm sure every organisation has hundreds if not thousands of Excel sheets tracking important business processes that would be far better off as a SaaS app.
Far better off for who? People constantly dismiss spreadsheets, but in many cases, they are more powerful, more easily used by the people who have the domain knowledge required to properly implement calculations or workflow, and are more or less universally accessible.
And often the are unmaintainable because the original author left the company and the users don’t really know what the spreadsheet does which leads to unrecognized bugs and errors especially in spreadsheets with lots of data
Let's not forget: it's pretty unlikely that two orgs come up with the same administration/data-analyis for which they use those spreadsheets, so most of those proposed SaaS applications would have just one customer.
Spreadsheets are absolutely the right solution for a great many problems. The important thing to recognize is when a problem has outgrown a spreadsheet solution. That’s usually when you start to use a spreadsheet as a database, or when it has more than a handful of users.
It’s a rare spreadsheet that survives its original creator.
Spreadsheets are powerful, but often abused. They are great for economics but horrible for logic.
Most medium to large complex spreadsheets are better implemented in a high level programming language.
Spreadsheets seem useful for people that are scared of programming syntax but quickly become so much less maintainable and janky that I believe its almost always easier to just start with learning to program already.
Ai saves me like an hour per month tops. I still don't understand the hype. It's a solution in search of a problem. It can't solve the hard coding problems. And it doesn't say when it can't solve the essay ones either. It's less valuable than resharper. So the business value is maybe $10 a month. That can't finance this industry.
Had the cost of building custom software dropped 90%, we would be seeing a flurry of low-cost, decent-quality SaaS offering all over the marketplace, possibly undercutting some established players.
From where I sit, right now, this does not seem to be the case.
This is as if writing down the code is not the biggest problem, or the biggest time sink, of building software.
Astute observation. From where I sit, the market (at least for business software; I am not very familiar with the consumer market) seems to be wide open, and businesses in the 5 - 200 employee range seem to be particularly underserved.
The marketplace for software for single-owner shops or 1-5 employee size places does seem to be quite strong, and then there's enterprise software, but small business seems to have a software marketplace that is atrociously bad. Here is the typical thing a prospective customer asks me to fix for them:
- They are using some piece of software that is essential to their business.
- There really isn't much good competition for that software, and it would be a large cost to convert to another platform that also has all the same downsides below.
- The software vendor used to be great, but seems to have been sold several times.
- The vendor has recently switched to a subscription-only model and keeps on raising subscription prices in the 12% or so range every year, and the cost of this has started to become noticeable in their budget.
- They were accustomed to software being a capital investment with a modest ongoing cost for support, but now it's becoming just an expense.
- Quality has taken a nosedive and in particular new features are buggy. Promised integrations seem quite lacking and new features/integrations feel bolted on.
- Support is difficult to get ahold of, and the formerly good telephone support then got replaced by being asked to open tickets/emails and now has been replaced by an AI chatbot frontend before they can even open a ticket. Most issues go unresolved.
There are literally millions of software packages in existence, and the bulk of them by numbers are niche products used by small businesses. (Think of a software package which solely exists to help you write custom enhancements for another software package which is used by a specific sector of the furniture-manufacturing business, to get an example.) The quality of this sector is not improving.
This is a field that is absolutely ripe for improvement. If the cost of building software really were dropping 90%, this would be a very easy field to move into and simply start offering for $6,000 a year the product that your competition is charging $12,000 a year for, for an inferior product. Before you bring up things like vendor lock-in or the pain of migration... why can't you write software to solve those problems, too? After all, the cost of writing a migration tool should be 90% cheaper now, too, right?
"We use AI to build the tools because we use them in cursor or Visual Studio or code or wherever else people are making our stuff. I use AI a bunch." https://37signals.com/podcast/listener-questions/
"Today we’re introducing Fizzy. Kanban as it should be, not as it has been.
[...] we’ll host your account for just $20/month for unlimited cards and unlimited users. [...] And here’s a surprise... Fizzy is open source! If you’d prefer not to pay us, or you want to customize Fizzy for your own use, you can run it yourself for free forever." https://x.com/jasonfried/status/1995886683028685291
You are saying there aren't more low cost alternatives coming out
You also say writing code isn't the big problem (which I agree with)
But both can be true and in fact the reason is because the second is true! You aren't seeing the alternate because marketing is hard. People generally don't care about new products and aren't willing to save a little bit of money risking their time on something new
barrier to entry is more problematic than anything else
make something decent in the same space as an existing mega-corporation's tool?
prepare to get sued and they also steal your good ideas and implement them themselves because you don't have the money to fight them in court
The crap I build _replaces_ someone else's SaaS (or free open source) product.
They solve my exact problem and nothing else and they follow the ways I like to use my software, with no fancy Dockerised WebUIs etc.
I have exactly zero intention of putting any of that shit out there as any kind of service with user accounts and billing and all of the associated stress. A few of them might be something I could sell as a SaaS offering, but I'm not interested in it at all.
Most of them are on my Github though for anyone to get and use as they see fit, but then it's up to them if the vibe coded program does something it shouldn't :)
> Had the cost of building custom software dropped 90%, we would be seeing a flurry of low-cost, decent-quality SaaS offering all over the marketplace, possibly undercutting some established players.
Aha. Are developers finally realizing that just writing code doesn't make a business? We actually have a ton of SaaS companies being born right now but they're not making headway, because functionality and good code don't necessarily mean good businesses. Building a business is hard.
I have seen it commonly cited (although haven't bothered to check the actual sources, mostly because I believe they should be taken with a grain of salt) that developers spend somewhere in the ballpark of 50-60% of their time doing "coding work" - that is writing the code, thinking about the solution in terms of technical aspects, reading code reviews. The rest are meetings, coordination, administrative tasks, being blocked or whatever else you can think of. Even if, wishfully thinking, the value of the act of "coding work" fell by 90%, the act of doing "software engineering" work would still cost no less than 50% of what it currently does. Headlines like these are alarmist and have little substance.
Edit: I also feel stumped why so many people give in to this hype that LLMs are good at coding when they can't even do seemingly simple tasks of plain English language summarization accurately as evidenced in https://www.youtube.com/watch?v=MrwJgDHJJoE. If the AI summarizes the code in its own context incorrectly then it will not be able to write it correctly either.
from my perspective, this is exactly where we are. Have you ever watched starter story? There's hundreds of people with 5,6+ apps making 100k+ MRR. The VC model is broken because of it.
I keep seeing articles like these popup. I am in the industry but not in the “AI” industry.
What I have no concept of, is the current subsidized, VC funded, anywhere close to what the final product will be?
I always fall back to the Uber paradox. Yes it was great at first, now it’s 3x what it cost and has only given cabs pricing power. This was good for consumers to start but now it’s just another part of the k shaped economy.
So is that ultimately where AI goes? Top percent can afford a high monthly subscription and the not so fortunate get there free 5 minutes per month
I totally agree with you. I am working on a new platform right now for a niche industry. Maybe theres $10m ARR to make total in the industry. Last year, it wouldn’t be worth the effort to raise, hire a PM, a few devs, QA, etc. But for a solo dev like myself with AI, it definitely is worth it now.
I must be holding wrong then because I do use Claude Code all the time and I do think its quite impressive… still I cant see where the productivity gains go nor am I even sure they exist (they might, I just cant tell for sure!)
This is also one of my arguments. I'm exaggerating, of course, but to me it feels like major software products and services haven't been adding new features for years now. What we get with updates these days are new restrictions on use, and "streamlining", i.e. the removal of features. Usually with the justification that the effort to maintain them was too high.
I used to look at release notes excited about what new features I might get. Now I read them with some level of anxiety. I hope none of the inevitably removed features are ones I used.
The AI evangelist talks to me about 10×. Meanwhile, all the software I use is becoming less functional, less configurable, less powerful, less secure, less stable, and in general crappier by the day.
I've only been working with AI for a couple of months, but IMHO it's over. The Internet Age which ran 30 years from roughly 1995-2025 has ended and we've entered the AI Age (maybe the last age).
I know people with little programming experience who have already passed me in productivity, and I've been doing this since the 80s. And that trend is only going to accelerate and intensify.
The main point that people are having a hard time seeing, probably due to denial, is that once problem solving is solved at any level with AI, then it's solved at all levels. We're lost in the details of LLMs, NNs, etc, but not seeing the big picture. That if AI can work through a todo list, then it can write a todo list. It can check if a todo list is done. It can work recursively at any level of the problem solving hierarchy and in parallel. It can come up with new ideas creatively with stable diffusion. It can learn and it can teach. And most importantly, it can evolve.
Based on the context I have before me, I predict that at the end of 2026 (coinciding with the election) America and probably the world will enter a massive recession, likely bigger than the Housing Bubble popping. Definitely bigger than the Dot Bomb. Where too many bad decisions compounded for too many decades converge to throw away most of the quality of life gains that humanity has made since WWII, forcing us to start over. I'll just call it the Great Dumbpression.
If something like UBI is the eventual goal for humankind, or soft versions of that such as democratic socialism, it's on the other side of a bottleneck. One where 1000 billionaires and a few trillionaires effectively own the world, while everyone else scratches out a subsistence income under neofeudalism. One where as much food gets thrown away as what the world consumes, and a billion people go hungry. One where some people have more than they could use in countless lifetimes, including the option to cheat death, while everyone else faces their own mortality.
"AI was the answer to Earth's problems" could be the opening line of a novel. But I've heard this story too many times. In those stories, the next 10 years don't go as planned. Once we enter the Singularity and the rate of technological progress goes exponential, it becomes impossible to predict the future. Meaning that a lot of fringe and unthinkable timelines become highly likely. It's basically the Great Filter in the Drake equation and Fermi paradox.
This is a little hard for me to come to terms with after a lifetime of little or no progress in the areas of tech that I care about. I remember in the late 90s when people were talking about AI and couldn't find a use for it, so it had no funding. The best they could come up with was predicting the stock market, auditing, genetics, stuff like that. Who knew that AI would take off because of self-help, adult material and parody? But I guess we should have known. Every other form of information technology followed those trends.
Because of that lack of real tech as labor-saving devices to help us get real work done, there's been an explosion of phantom tech that increases our burden through distraction and makes our work/life balance even less healthy as underemployment. This is why AI will inevitably be recruited to demand an increase in productivity from us for the same income, not decrease our share of the workload.
What keeps me going is that I've always been wrong about the future. Maybe one of those timelines sees a great democratization of tech, where even the poorest people have access to free problem solving tech that allows them to build assistants that increase their leverage enough to escape poverty without money. In effect making (late-stage) capitalism irrelevent.
If the rate of increasing equity is faster than the rate of increasing excess, then we have a small window of time to catch up before we enter a Long Now of suffering, where wealth inequality approaches an asy...
But you need: a staff level engineer to guide it, great standardization and testing best practices. And yes in that situation you can go 10-50x faster. Many teams/products are not in that environment though.
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[ 2.1 ms ] story [ 107 ms ] threadNo, no, and no.
I hear vague suggestions like "get better at the business domain" and other things like that. I'm not discounting any of that, but what does this actually mean or look like in your day-to-day life? I'm working at a mid-sized company right now. I use Cursor and some other tools, but I can't help but wonder if I'm still falling behind or doing something wrong.
Does anybody have any thoughts or suggestions on this? The landscape and horizon just seems so foggy to me right now.
This is normal with all that is going on in the industry and the AI/ML hype. But, one should not allow that to lead to "analysis paralysis".
> specifically with how I should be positioning myself. ... Does anybody have any thoughts or suggestions on this?
You have a stable job; hence your entire focus (for now) should be to "grow" in your job/organization. This means taking more responsibilities both technical/non-technical and demonstrating your long-term commitment to management. On the technical side, start with "full stack development" both frontend and backend so you can contribute end-to-end to the entire product line. Learn/Use all available tools (AI and otherwise) to demonstrate independent initiative. Step up for any tasks which might not have a owner (eg. CI/CD etc.). Keep your boss/higher-ups informed so as to maintain visibility throughout the organization. Learn more about the problem domain, interact more with Marketing/Sales so as to become the liaison between Engineering and rest of the organization/clients.
Generally, all higher management look for initiative and independent drive so that they can delegate work with the assurance that it will be taken care of and that is what you need to provide.
Build your own tools, need a small utility? Use an LLM to create it with you.
Create LLM-focused tools and adjust your workflows to be LLM-friendly.
I personally have a Taskfile setup that follows the same formula regardless of language. "task build" runs lint+test+build. Test and lint are kinda self-evident. All output is set to minimum, only errors are verbose (don't waste context on fancy output).
I also have tools for LLMs to use to find large code files, large and overly complex functions etc.
All project documentation lives in docs/ as markdown files with Mermaid charts.
This way I can just have the general "how to use a taskfile" instructions in my global WHATEVER.md and it'll work in every project.
Learn project management. Working with LLMs is exactly like project managing a bunch of smart and over eager junior coders who want to use every trick and pattern they learned at school for every tiny shell script.
Do a few test projects where you just pretend you're a non-techinical project lead and know WHAT you want but not HOW you want it done. Plan the project, split it into tasks (github tasks or beads[0] both work pretty well). Then have the LLM(s) tackle the tasks one by one and test the end result like a non-techical PM would do in a demo. Comment, critique and ask them to change stuff that doesn't work.
If you can afford it, bring in an outside consultant (Codex or Gemini), both of which are _really_ good at evaluating large codebases for duplication, test coverage, repetition, bad patterns etc. Give their responses verbatim to Claude and ask what it thinks about them.
Working with LLMs is a skill you just need to use to get a feel for it, it's not a science and more like an art. For example I can "feel" when Claude is doing its thing and being either overeager or trying to complete a task while ignoring the burning pile of unit tests it leaves behind and interrupt. it before it gets too far.
[0] https://github.com/steveyegge/beads
Opus 4.5 in particular has been a profound shift. I’m not sure how software dev as a career survives this. I have nearly 0 reason to hire a developer for my company because I just write a spec and Claude does it in one shot.
It’s honestly scary, and I hope my company doesn’t fail because as a developer I’m fucked. But… statistically my business will fail.
I think in a few years there will only be a handful of software companies—the ones who already have control of distribution. Products can be cloned in a few weeks now; not long until it’s a few minutes. I used to see a new competitor once every six months. Now I see a new competitor every few hours.
With the steam engine, though, consumers made a trade-off: You pay less, and get (in most cases, I presume) a worse product. With LLMs and other machine learning technologies, maybe if you're paying for the software there's a trade-off (if the software is actually cheaper anyway), but otherwise it doesn't exist. It costs the same amount of money for you to read an LLM-generated article as to read a real one; your internet bill doesn't go down. Likewise for gratis software. It's just worse, with no benefit.
Hacker News is full of producers, in this sense, who often benefit from cutting corners, and LLMs allow them to cut corners, so obviously there are plenty of evangelists here. I saw someone else in this comment section mention that gamers who are not in the tech industry don't like "AI". That's to be expected; they're not the producers, so they're not the ones who benefit.
And this company, with all the formidable powers of AI behind them, can find no way to optimize that other than pre loading the app in memory. And that's for a app that's basically a GUI for `ls`
It’s often hard to ground how “good” blog writers are, but tidbits like this make it easy to disregard the author’s opinions. I’ve worked in many codebases where the test writers share the authors sentiment. They are awful and the tests are at best useless and often harmful.
Getting to this point in your career without understanding how to write effective tests is a major red flag.
Far better off for who? People constantly dismiss spreadsheets, but in many cases, they are more powerful, more easily used by the people who have the domain knowledge required to properly implement calculations or workflow, and are more or less universally accessible.
There is of course SAP for common problems.
It’s a rare spreadsheet that survives its original creator.
Most medium to large complex spreadsheets are better implemented in a high level programming language.
Spreadsheets seem useful for people that are scared of programming syntax but quickly become so much less maintainable and janky that I believe its almost always easier to just start with learning to program already.
Especially excel is 100% jank.
From where I sit, right now, this does not seem to be the case.
This is as if writing down the code is not the biggest problem, or the biggest time sink, of building software.
The marketplace for software for single-owner shops or 1-5 employee size places does seem to be quite strong, and then there's enterprise software, but small business seems to have a software marketplace that is atrociously bad. Here is the typical thing a prospective customer asks me to fix for them:
- They are using some piece of software that is essential to their business. - There really isn't much good competition for that software, and it would be a large cost to convert to another platform that also has all the same downsides below. - The software vendor used to be great, but seems to have been sold several times. - The vendor has recently switched to a subscription-only model and keeps on raising subscription prices in the 12% or so range every year, and the cost of this has started to become noticeable in their budget. - They were accustomed to software being a capital investment with a modest ongoing cost for support, but now it's becoming just an expense. - Quality has taken a nosedive and in particular new features are buggy. Promised integrations seem quite lacking and new features/integrations feel bolted on. - Support is difficult to get ahold of, and the formerly good telephone support then got replaced by being asked to open tickets/emails and now has been replaced by an AI chatbot frontend before they can even open a ticket. Most issues go unresolved.
There are literally millions of software packages in existence, and the bulk of them by numbers are niche products used by small businesses. (Think of a software package which solely exists to help you write custom enhancements for another software package which is used by a specific sector of the furniture-manufacturing business, to get an example.) The quality of this sector is not improving.
This is a field that is absolutely ripe for improvement. If the cost of building software really were dropping 90%, this would be a very easy field to move into and simply start offering for $6,000 a year the product that your competition is charging $12,000 a year for, for an inferior product. Before you bring up things like vendor lock-in or the pain of migration... why can't you write software to solve those problems, too? After all, the cost of writing a migration tool should be 90% cheaper now, too, right?
"Today we’re introducing Fizzy. Kanban as it should be, not as it has been. [...] we’ll host your account for just $20/month for unlimited cards and unlimited users. [...] And here’s a surprise... Fizzy is open source! If you’d prefer not to pay us, or you want to customize Fizzy for your own use, you can run it yourself for free forever." https://x.com/jasonfried/status/1995886683028685291
You are saying there aren't more low cost alternatives coming out
You also say writing code isn't the big problem (which I agree with)
But both can be true and in fact the reason is because the second is true! You aren't seeing the alternate because marketing is hard. People generally don't care about new products and aren't willing to save a little bit of money risking their time on something new
make something decent in the same space as an existing mega-corporation's tool? prepare to get sued and they also steal your good ideas and implement them themselves because you don't have the money to fight them in court
The crap I build _replaces_ someone else's SaaS (or free open source) product.
They solve my exact problem and nothing else and they follow the ways I like to use my software, with no fancy Dockerised WebUIs etc.
I have exactly zero intention of putting any of that shit out there as any kind of service with user accounts and billing and all of the associated stress. A few of them might be something I could sell as a SaaS offering, but I'm not interested in it at all.
Most of them are on my Github though for anyone to get and use as they see fit, but then it's up to them if the vibe coded program does something it shouldn't :)
Aha. Are developers finally realizing that just writing code doesn't make a business? We actually have a ton of SaaS companies being born right now but they're not making headway, because functionality and good code don't necessarily mean good businesses. Building a business is hard.
Edit: I also feel stumped why so many people give in to this hype that LLMs are good at coding when they can't even do seemingly simple tasks of plain English language summarization accurately as evidenced in https://www.youtube.com/watch?v=MrwJgDHJJoE. If the AI summarizes the code in its own context incorrectly then it will not be able to write it correctly either.
Was there an explosion of useful features in any software product you use? A jump in quality? Anything tangible an end user can see?..
I used to look at release notes excited about what new features I might get. Now I read them with some level of anxiety. I hope none of the inevitably removed features are ones I used.
The AI evangelist talks to me about 10×. Meanwhile, all the software I use is becoming less functional, less configurable, less powerful, less secure, less stable, and in general crappier by the day.
I believe Betteridge's law of headlines [1] applies here:
No.
1. https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headline...
I've only been working with AI for a couple of months, but IMHO it's over. The Internet Age which ran 30 years from roughly 1995-2025 has ended and we've entered the AI Age (maybe the last age).
I know people with little programming experience who have already passed me in productivity, and I've been doing this since the 80s. And that trend is only going to accelerate and intensify.
The main point that people are having a hard time seeing, probably due to denial, is that once problem solving is solved at any level with AI, then it's solved at all levels. We're lost in the details of LLMs, NNs, etc, but not seeing the big picture. That if AI can work through a todo list, then it can write a todo list. It can check if a todo list is done. It can work recursively at any level of the problem solving hierarchy and in parallel. It can come up with new ideas creatively with stable diffusion. It can learn and it can teach. And most importantly, it can evolve.
Based on the context I have before me, I predict that at the end of 2026 (coinciding with the election) America and probably the world will enter a massive recession, likely bigger than the Housing Bubble popping. Definitely bigger than the Dot Bomb. Where too many bad decisions compounded for too many decades converge to throw away most of the quality of life gains that humanity has made since WWII, forcing us to start over. I'll just call it the Great Dumbpression.
If something like UBI is the eventual goal for humankind, or soft versions of that such as democratic socialism, it's on the other side of a bottleneck. One where 1000 billionaires and a few trillionaires effectively own the world, while everyone else scratches out a subsistence income under neofeudalism. One where as much food gets thrown away as what the world consumes, and a billion people go hungry. One where some people have more than they could use in countless lifetimes, including the option to cheat death, while everyone else faces their own mortality.
"AI was the answer to Earth's problems" could be the opening line of a novel. But I've heard this story too many times. In those stories, the next 10 years don't go as planned. Once we enter the Singularity and the rate of technological progress goes exponential, it becomes impossible to predict the future. Meaning that a lot of fringe and unthinkable timelines become highly likely. It's basically the Great Filter in the Drake equation and Fermi paradox.
This is a little hard for me to come to terms with after a lifetime of little or no progress in the areas of tech that I care about. I remember in the late 90s when people were talking about AI and couldn't find a use for it, so it had no funding. The best they could come up with was predicting the stock market, auditing, genetics, stuff like that. Who knew that AI would take off because of self-help, adult material and parody? But I guess we should have known. Every other form of information technology followed those trends.
Because of that lack of real tech as labor-saving devices to help us get real work done, there's been an explosion of phantom tech that increases our burden through distraction and makes our work/life balance even less healthy as underemployment. This is why AI will inevitably be recruited to demand an increase in productivity from us for the same income, not decrease our share of the workload.
What keeps me going is that I've always been wrong about the future. Maybe one of those timelines sees a great democratization of tech, where even the poorest people have access to free problem solving tech that allows them to build assistants that increase their leverage enough to escape poverty without money. In effect making (late-stage) capitalism irrelevent.
If the rate of increasing equity is faster than the rate of increasing excess, then we have a small window of time to catch up before we enter a Long Now of suffering, where wealth inequality approaches an asy...
But you need: a staff level engineer to guide it, great standardization and testing best practices. And yes in that situation you can go 10-50x faster. Many teams/products are not in that environment though.