I think AI can be really powerful tool. I am more productive with it than not, but a lot of my time interacting with AI is reviewing its code, finding problems with it (I always find some issues with it), and telling it what to do differently multiple times, and eventually giving up, and fixing up the code by hand. But it definitely has reduced average time it takes me to implement features. But I also worry that not everyone would be responsible and check/fix AI generated code.

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.

It's not just about "building" ... who is going to maintain all this new sub-par code pushed to production every day?

Who is going to patch all bugs, edge cases and security vulnerabilities?

I contracted briefly on a post-LLM-boom Excel modernization project (which ended up being consulting mainly, because I had to spend all my time explaining key considerations for a long-running software project that would fit their domain).

The company had already tried to push 2 poor data analysts who kind of new Python into the role of vibe coding a Python desktop application that they would then distribute to users. In the best case scenario, these people would have vibe coded an application where the state was held in the UI, with no concept of architectural seperation and no prospects of understanding what the code was doing a couple months from inception (except through the lens of AI sycophancy), all packaged as a desktop application which would generate excel spreadsheets that they would then send to each other via Email (for some reason, this is what they wanted - probably because it is what they know).

You can't blame the business for this, because there are no technical people in these orgs. They were very smart people in this case, doing high-end consultancy work themselves, but they are not technical. If I tried to do vibe chemistry, I'm sure it would be equally disastrous.

The only thing vibe coding unlocks for these orgs by themselves is to run headfirst into an application which does horrendous things with customer data. It doesn't free up time for me as the experienced dev to bring the cost down, because again, there is so much work needed to bring these orgs to the point where they can actually run and own an internal piece of software that I'm not doing much coding anyway.

> 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.

These kind of future prediction posts keep coming, and I'm tired of them. Reality is always more boring, less extreme, and slower at changing, because there are too many factors involved, and the authors never account for everything.

Maybe we should collect all of these predictions, then go back in 5-10 years and see if anyone was actually right.

> I've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests) for a fairly complex internal tool. This would take me, or many developers I know and respect, days to write by hand.

I'm not sure about this. The tests I've gotten out in a few hours are the kind I'd approve if another dev sent then but haven't really ended up finding meaningful issues.

I think the cost of prototyping has definitely gone down.

Developing production grade software which you want to people to rely on and pay for it is not gone down so much. The "weak" link is still human.

Debugging complex production issues needs intimate knowledge of the code. Not gonna happen in next 3-4 years atleast.

In context of B2B SaaS products that require a high degree of customization per client, I think there could be an argument for this figure.

The biggest bottleneck I have seen is converting the requirements into code fast enough to prove to the customer that they didn't give us the right/sufficient requirements. Up until recently, you had to avoid spending time on code if you thought the requirements were bad. Throwing away 2+ weeks of work on ambiguity is a terrible time.

Today, you could hypothetically get lucky on a single prompt and be ~99% of the way there in one shot. Even if that other 1% sucks to clean up, imagine if it was enough to get the final polished requirements out of the customer. You could crap out an 80% prototype in the time it takes you to complete one daily standup call. Is the fact that it's only 80% there bad? I don't think so in this context. Handing a customer something that almost works is much more productive than fucking around with design documents and ensuring requirements are perfectly polished to developer preferences. A slightly wrong thing gets you the exact answer a lot faster than nothing at all.

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.

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.

> This takes a fairly large mindset shift, but the hard work is the conceptual thinking, not the typing.

But the hard work always was the conceptual thinking? At least at and beyond the Senior level, for me it was always the thinking that's the hard work, not converting the thoughts into code.

Where are the billions of dollars spent on GPUs and new data centers accounted for in this estimation?

Domain knowledge is the moat, we need to rethink career planning https://news.ycombinator.com/item?id=46197349

Did I miss something or is there actually no evidence provided that costs have dropped?

> 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.

By making up numbers and not supplying any evidence, you can come to any conclusion you like! Then you get to draw a graph with no units on it. Finally, you can say things that are objectively false like "These assertions are rapidly becoming completely false".

> One objection I hear a lot is that LLMs are only good at greenfield projects. I'd push back hard on this. I've spent plenty of time trying to understand 3-year-old+ codebases where everyone who wrote it has left.

Where I am, 3 year old is greenfield, and old and large is 20 years old and has 8million lines of nasty c++. I’ll have to wait a bit more I think …

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!)

It depends. For AI to work for large projects (did a post on this forever ago in AI terms. https://getstream.io/blog/cursor-ai-large-projects/)

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.

Copying GPL code, with global search&replace of the brand names, has always lowered the cost of software 'development' dramatically.

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

Then why is all my software slower, buggier, and with a worse UX?

Can we also take into account the mental cost associates with building software? Because how I see it, managing output from agents is way more exhausting than doing it ourself.

And obviously the cost of not upskilling in intricate technical details as much as before (aka staying at the high level perspective) will have to be paid at some point

If the cost of building software dropped so much - where is that software?..

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've had Claude Code write an entire unit/integration test suite in a few hours (300+ tests)

I'd love to see someone do this, or a similar task, live on stream. I always feel like an idiot when I read things like this because despite using Claude Code a lot I've never been able to get anything of that magnitude out of it that wasn't slop/completely unusable, to the point where I started to question if I hadn't been faster writing everything by hand.

Claiming that software is now 90% cheaper feels absurd to me and I'd love to understand better where this completely different worldview comes from. Am I using the tools incorrectly? Different domains/languages/ecosystems?

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.

No. Not unless your business wasn't competitive to begin with

Maybe I'm holding it wrong, but I don't actually see the huge productivity gains from LLM-assisted software development. Work is leaning on us to use AI—not requiring it yet, but we're at DEFCON 3, borderline 2 (DEFCON 1 being a Shopify situation). My team's experience is that it needs LOTS of handholding and manual fixing to produce even something basic that's remotely fit for production use.

I closed a comment from ~2.5y ago (https://news.ycombinator.com/item?id=36594800) with this sentence: "I'm not sure that incorporating LLMs into programming is (yet) not just an infinite generator of messes for humans to clean up." My experience with it is convincing me that that's just what it is. When the bills come due, the VC money dries up, and the AI providers start jacking up their prices... there's probably going to be a boom market for humans to clean up AI messes.

I don't really build software any more and have moved into other parts of the business. But I'm still a huge user of software and I'd just echo all the other comments asking if it's so easy to get all these great tools built and shipped, where are they? I can see that YouTube is flooded with auto-generated content. I can see that blogspam has skyrocketed beyond belief. I can see that the number of phishing texts and voicemails I get every day has gone through the roof. I don't see any flood of new CNCF incubating projects. I don't see that holy grail entire OS comparable to Linux but written in Rust. I don't see the other holy grail new web browser that can compete with Firefox, Chrome, and Safari. It's possible people are shipping more of the stripped down Jira clones designed for a team of ten that gets 60 customers and stops receiving updates after 2 years but that's not the kind of software that would be visible to me.

If you're replacing spreadsheets with a single-purpose web UI with proper access control and concurrent editing that doesn't need Sharepoint or Google Workspaces, fine, but if you're telling me that's going to revolutionize the entire industry and economy and justify trillions of dollars in new data centers, I don't think so. I think you need to actually compete with Sharepoint and Google Workspaces. Supposedly, Google and Microsoft claim to be using LLMs internally more than ever, but they're publicly traded companies. If it's having some huge impact, surely we'll see their margins skyrocket when they have no more labor costs, right?

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.

> Has the cost of building software just dropped 90%?

I believe Betteridge's law of headlines [1] applies here:

No.

1. https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headline...

Perhaps the cost will drop over time, but it will be because writing code is becoming more accessible. It's not just because of AI, but the natural progress of education and literacy on the topic that would have happened anyway.

What I see are salaries stagnating and opportunity for new niche roles or roles being redefined to have more technical responsibility. Is this not the future we all expected before AI hype anyway? People need to relax and refocus on what matters.

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.

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.

If you’re quicker then competition heats up management wants more done, efficiencies are soon forgotten and new expectations and baselines set.

Ask someone who builds software for a fee. Are you able to do 90% more? Fire 9/10 engineers? Produce 90% faster?

No, no, and no.

*90% so far..

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 asymptote making life performative, pageantry for the masses who must please an emperor with no clothes.

In a recent interview with Mel Robbins in episode 715 of Real Time, Bill Maher said "my book would be called: It's Not Gonna Be That" about the future not being what we think it is. I can't find a video, but he describes it starting around the 19:00 mark:

https://podcasts.musixmatch.com/podcast/real-time-with-bill-...

Our best hope for the future is that we're wrong about it.