Has the cost of building software dropped 90%?

> Like, is there truly an agentic way to go 10x or is there some catch?

Yes. I think it’s practice. I know this sounds ridiculous, but I feel like I have reached a kind of mind meld state with my AI tooling, specifically Claude Code. I am not really consciously aware of having learned anything related to these processes, but I have been all in on this since ChatGPT, and I honestly think my brain has been rewired in a way that I don’t truly perceive except in terms of the rate of software production.

There was a period of several months a while ago where I felt exhausted all the time. I was getting a lot done, but there was something about the experience that was incredibly draining. Now I am past that and I have gone to this new plateau of ridiculous productivity, and a kind of addictive joy in the work. A marvellous pleasure at the orchestration of complex tasks and seeing the results play out. It’s pure magic.

Yes, I know this sounds ridiculous and over-the-top. But I haven’t had this much fun writing software since my 20s.

That's really interesting.

May I ask what kinds of projects, stack and any kind of markdown magic you use?

And any specific workflow? And are there times when you have to step in manually?

> Yes, I know this sounds ridiculous and over-the-top.

in that case you should come with more data. tell us how you measured your productivity improvement. all you've said here is that it makes you feel good

Currently three main projects. Two are Rails back-ends and React front-ends, so they are all Ruby, Typescript, Tailwind, etc. The third is more recent, it's an audio plugin built using the JUCE framework, it is all C++. This is the one that has been blowing my mind the most because I am an expert web developer, but the last time I wrote a line of C++ was 20 years ago, and I have zero DSP or math skills. What blows my mind is that it works great, it's thread safe and performant.

In terms of workflow, I have a bunch of custom commands for tasks that I do frequently (e.g. "perform code review"), but I'm very much in the loop all the time. The whole "agent can code for hours at a time" thing is not something I personally believe. It depends on the task how involved I get, however. Sometimes I'm happy to just let it do work and then review afterwards. Other times, I will watch it code and interrupt it if I am unhappy with the direction. So yes, I am constantly stepping in manually. This is what I meant about "mind meld". The agent is not doing the work, I am not doing the work, WE are doing the work.

Research -> Plan -> Implement

Start by having the agent ask you questions until it has enough information to create a plan.

Use the agent to create the plan.

Follow the plan.

When I started, I had to look at the code pretty frequently. Rather than fix it myself, I spent time thinking about what I could change in my prompts or workflow.

Work that would have taken me 1-2 weeks to complete, I can now get done in 2-3 hours. That's not an exaggeration. I have another friend who is as all-in on this as me and he works in a company (I work for myself, as a solo contractor for clients), and he told me that he moved on to Q1 2026 projects because he'd completed all the work slated for 2025, weeks ahead of schedule. Meanwhile his colleagues are still wading through scrum meetings.

I realize that this all sounds kind of religious: you don't know what you're missing until you actually accept Jesus's love, or something along those lines. But you do have to kinda just go all-in to have this experience. I don't know what else to say about it.

I maintain a few rails apps and Claude Code has written 95% of the code for the last 4 months. I deploy regularly.

I make my own PRs then have Copilot review them. Sometimes it finds criticisms, and I copy and paste that chunk of critique into Claude Code, and it fixes it.

Treat the LLMs like junior devs that can lookup answers supernaturally fast. You still need to be mindful of their work. Doubtful even. Test, test, test.

My sympathies go out to the friend's coworkers. They are probably wading through a bunch of stuff right now, but given the context you have given us, its probably not "scrum meetings"..

I don't even care about the llm, I just want the confidence you have to assess that any given thing will take N weeks. You say 1-2 weeks.. thats like a big range! Something that "would" take 1 week takes ~2 hours, something that "would" take 2 weeks also takes ~2 hours. How does that even make sense? I wonder how long something that would of taken three weeks would take?

Do you still charge your clients the same?

> They are probably wading through a bunch of stuff right now, but given the context you have given us, its probably not "scrum meetings"..

This made me laugh. Fair enough. ;)

In terms of the time estimations: if your point is that I don't have hard data to back up my assertions, you're absolutely correct. I was always terrible at estimating how long something would take. I'm still terrible at it. But I agree with the OP. I think the labour required is down 90%.

It does feel to me that we're getting into religious believer territory. There are those who have firsthand experience and are all-in (the believers), there are those who have firsthand experience and don't get it (the faithless), and there are those who haven't tried it (the atheists). It's hard to communicate across those divides, and each group's view of the others is essentially, "I don't understand you".

What's worked best with Gemini such I made a DSL that transpiles to C with CUDA support to train small models in about 3 hours... (all programs must run against an image data set, must only generate embeddings)

Do not; vibe code from top down (ex. Make me a UI with React, with these buttons and these behaviors to each button)

Do not; chat casually with it. (ex. I think it would look better if the button was green)

Do; constrain phrasing to the next data transform goal (ex. You must add a function to change all words that start with lowercase to start with uppercase)

Do; vibe code bottom up (ex. You must generate a file with a function to open a plaintext file and appropriate tests; now you must add a function to count all words that begin with "f")

Do; stick to must/should/may (ex. You must extend the code with this next function)

Do; constrain it to mathematical abstractions (ex. sys prompt: You must not use loops, you must only use recursion and functional paradigms. You must not make up abstractions and stick to mathematical objects and known algorithms)

Do; constrain it to one file per type and function. This makes it quick to review, regenerate only what needs to change.

Using those patterns, Gemini 2.5 and 3 have cranked out banging code with little wandering off in the weeds and hallucinating.

Programming has been mired in made up semantics of the individual coder for the luls, to create mystique and obfuscate the truth to ensure job security; end of the day it's matrix math and state sync between memory and display.

this is just not a very interesting way to talk about technology. I'm glad it feels like a religious experience to you, I don't care about that. I care about reality

Not to pick apart your analogy, but asserting that atheists haven't tried religion is misinformed.

Nobody had a robust, empirical metric of programmer productivity. Nobody. Ticket count, function points, LoC, and others tell you nothing about the fitness of the product. It’s all feels.

But then does this not give you pause, that it "feels religious"? Is there not some morsel of critical/rational interrogation on this? Aren't you worried about becoming perhaps too fundamentalist in your belief?

To extend the analogy: why charge clients for your labor anymore, which Claude can supposedly do in a fraction of the time? Why not just ask if they have heard the good word, so to speak?

ok, but there's a spectrum between fully reproducible empirical evidence and divine revelation. I'm not convinced it's impossible to measure productivity in a meaningful way, even if it isn't perfect. it at least seems better to try than... whatever this is

If your work maps exceedingly well to the technology it is true, it goes much faster. Doubly so when you have enough experience and understanding of things to find its errors or suboptimal approaches and adjust it that much faster.

The second you get to a place where the mapping isn’t there though, it goes off rails quickly.

Not everyone programs in such a way that they may ever experience this but I have, as a Staff engineer at a large firm, run into this again and again.

It’s great for greenfield projects that follow CRUD patterns though.

it seems to me if these things were real and repeatable there would be published traces that show the exact interactions that led to a specific output and the cost in time and money to get there.

do such things exist?

Can we see any of this software created by this amazing LLMs?

Brain-rot can be associated with heavy LLM usage.

Why do you need to use Tailwind if the code is generated? Can't there be something more efficient?

So, you say that AI has made you "ridiculously faster", but then admit you've always been terrible at estimating how long something would take?

Religions are about faith, faith is belief in the absence of evidence. Engineering output is tangible and measurable, objectively verifiable and readily quantifiable (both locally and in terms of profits). Full evidence, testable assertions, no faith required.

Here we have claims of objective results, but also admissions we’re not even tracking estimations and are terrible at making them when we do. People are notoriously bad at estimating actual time spent versus output, particularly when dealing with unwanted work. We’re missing the fundamental criteria of assessment, and there are known biases unaccounted for.

Output in LOC has never been the issue, copy and paste handles that just fine. TCO and holistic velocity after a few years is a separate matter. Masterful orchestration of agents could include estimation and tracking tasks with minimal overhead. That’s not what we’re seeing though…

Someone who has even a 20% better method for deck construction is gonna show me some timetables, some billed projects, and a very fancy new car. If accepting Mothra as my lord and saviour is a prerequisite to pierce an otherwise impenetrable veil of ontological obfuscation in order to see the unseeable? That deck might not be as cheap as it sounds, one way or the other.

I’m getting a nice learning and productivity bump from LLMs, there are incredible capabilities available. But premature optimization is still premature, and claims of silver bullets are yet to be demonstrated.

Extensive tailwind training data in the models. Sure there's something more efficient but it's just safer to let the model leverage what it was trained on.

> Yes, I know this sounds ridiculous and over-the-top. But I haven’t had this much fun writing software since my 20s.

But...you're not writing it. The culmination of many sites, many people, Stack Overflow, etc. all wrote it through the filtering mechanism being called AI.

You didn't write a damn thing.

> It does feel to me that we're getting into religious believer territory. There are those who have firsthand experience and are all-in (the believers), there are those who have firsthand experience and don't get it (the faithless), and there are those who haven't tried it (the atheists). It's hard to communicate across those divides, and each group's view of the others is essentially, "I don't understand you".

What a total crock. Your prose reminds of of the ridiculously funny Mike Meyers in "The Love Guru".

Here's an example from this morning. At 10:00 am, a colleague created a ticket with an idea for the music plugin I'm working on: wouldn't it be cool if we could use nod detection (head tracking) to trigger recording? That way, musicians who use our app wouldn't need a foot switch (as a musician, you often have your hands occupied).

Yes, that would be cool. An hour later, I shipped a release build with that feature fully functional, including permissions plus a calibration UI that shows if your face is detected and lets you adjust sensitivity, and visually displays when a nod is detected. Most of that work got done while I was in the shower. That is the second feature in this app that got built today.

This morning I also created and deployed a bug fix release for analytics on one platform, and a brand-new report (fairly easy to put together because it followed the pattern of other reports) for a different platform.

I also worked out, argued with random people on HN and walked to work. Not bad for five hours! Do I know how long it would have taken to, for example, integrate face detection and tracking into a C++ audio plugin without assistance from AI? Especially given that I have never done that before? No, I do not. I am bad at estimating. Would it have been longer than 30 minutes? I mean...probably?

I think you have to make a distinction between indvidual experience and claims about general truths.

If I know someone as an honest and serious professional, and they tell me that some tool has made them 5x or 10x more productive, then I'm willing to believe that the tool really did make a big difference for them and their specific work. I would be far more sceptical if they told me that a tool has made them 10% more productive.

I might have some questions about how much technical debt was accumulated in the process and how much learning did not happen that might be needed down the road. How much of that productivity gain was borrowed from the future?

But I wouldn't dismiss the immediate claims out of hand. I think this experience is relevant as a starting point for the science that's needed to make more general claims.

Also, let's not forget that almost none of the choices we make as software engineers are based on solid empirical science. I have looked at quite a few studies about productivity and defect rates in software engineering projects. The methodology is almost always dodgy and the conclusions seem anything but robust to me.

Just having a 'count-in' type feature for recording would be much much more useful. Head nodding is something I do all the time anyway as a musician :).

I don't know what your user makeup is like, but shipping a CV feature same day sounds so potentially disastrous.. There are so many things I would think you would at least want to test, or even just consider with the kind of user emapthy we all should practice.

Surely there is an order of magnitude more training data on plain CSS than tailwind, right?

Just as an aside I also think I am way more productive now but a really convincing datapoint would be someone who does project work and now has 5x the hourly rate they had last year. If there are not plenty of people like this, it cannot be 10x

Awesome comment, thank you. No idea why it was flagged as dead. Vouched for it to not be.

That's not a very convincing argument. Even if you can do 10x the work, that doesn't necessarily mean you can easily find customers ready to pay 5x the hourly rate.

In my experience the LLMs work better with frameworks that have more rigid guidance. Something like Tailwind has a body of examples that work together, language to reason about the behavior needed, higher levels of abstraction (potentially), etc. This seems to be helpful.

The LLMs can certainly use raw CSS and it works well, the challenge is when you need consistent framing across many pages with mounting special cases, and the LLMs may make extrapolate small inconsistencies further. If you stick within a rigid framework, the inconsistencies should be less across a larger project (in theory, at least).

> An hour later, I shipped a release build

I would love to see that pull request, and how readable and maintainable the code is. And do you understand the code yourself, since you've never done this before?

Assuming 40 hours a week of work time, you’re claiming a ~25x speed up, which is laughably absurd to me.

It will take you 2.5 months to accomplish what would have taken you five years, that is the kind of productivity increase you’re describing.

It doesn’t pass the smell test. I’m not sure that going from assembly to python would even have such a ludicrous productivity enhancement.

Lol that's like saying that because you found the solution on stack overflow you didn't write the program

News flash buddy: YOU never wrote any code yourself either. Literally every single line of code you've ever committed to a repo was first written by someone else and you just copied it and modified it a little.

Not everyone bills hourly. I mostly do fixed price contracts

THis is remarkably similar to the process we had to follow a couple of decades ago, when offshoring to IT mills: spell out every little detail in small steps, iterate often, and you'll usually get most of what you want.

This. I find constraints to be very important. It's fairly obvious an llm can tackle a class or function. It's still up to the human to string it all together. I'm not quite sure how long that will last though. Seems more of an engineering problem to me. At the end of the day you absolutely can get good outputs from these things if you provide the proper input. Everything else is orchestration.

I appreciate this example. This does seem like a pretty difficult feature to build de novo. Did you already have some machine vision work integrated into your app? How are you handling machine vision? Is it just a call to an LLM API? Or are you doing it with a local model?

I understood their comment as going from

$100 / hour * 100 hours

to

$100 / hour * 500 hours

not to

$500 / hour * 100 hours

But it specifically mentions having 5x the previous hourly rate.

Yeah the last one. The others would require 5x deal flow which LLMs might not help deliver at all. But the last one should exist for people if 10x is true. Not every client can have already fully price in LLM improvements, people have contracts negotiated pre LLM. I have not heard of this though so I have to remain sceptical