[alasdair_]

Notably, his essay “no silver bullet” states that there has never been a new technology or way of thinking or working that has led to a 10X increase in the speed of software development.

That was true for almost seventy years until roughly last year.

AI is the silver bullet - my output is genuinely 10X what it was before claude code existed.

[hansvm]

I haven't yet seen anyone with a concrete example project (public ideally, but even describing private efforts in enough detail to enable potential criticism would be fine) making a claim as strong as 10x. Are you willing to break the mould and show us what we're all missing?

[CraigJPerry]

10x what? 10x revenue? 10x features shipped? Whats the measure, is it 10x speed of dev like parent comment? Because an unqualified 10x could mean 10x SLOC which is trivial with an agent but has negative value.

Assuming 10x on the speed of dev, Is the vscode repo a decent example? Recently they've been all in on AI augmented development so i'm thinking they'd be a reasonable subject?

How do you isolate out what counts as the "development" part of their delivery cycle (is that the dev inner loop, does that show up in frequency of commits then?) to measure it and see if it's running 10x?

https://github.com/microsoft/vscode/graphs/contributors?from...

[timacles]

Guarantee it’s the same story I get from all my friends/co workers who are now 10x… they are 10 times faster at starting random projects that get to 80% done that they can’t finish, so they immediately move on to the next project because their velocity is so high

[strgcmc]

From a software quality or software engineering POV --> this is clearly not building durable value, not scalable, etc. So I'd agree with you there.

But from the POV of say, a young startup company looking for PMF and navigating the ambiguities involved with trying to figure out what is the "right thing" to build that will appeal/delight/convince-people-to-pay --> being 10X faster at shipping 80% done projects, is actually incredibly, unfathomably valuable of a superpower. And it is also rationally the "right thing" to do, to make lots of cheap bets and fail/learn fast.

I find that many folks on my team (I am a manager/leader of small-to-mid size eng org), struggle with accepting the nuances of knowing the difference between different projects (where same team may need to do both kinds of work, all the time and in parallel):

- "Hey, the company needs, and you and I both agree, that this situation calls for building/renovating a skyscraper --> please design a fucking strong/safe/reliable skyscraper and don't take any shortcuts, this requires 'real' engineering"

- Vs, "Hey, the company isn't sure what it needs, and neither you nor I know any better either, so let's try a bunch of different shacks/sheds/treehouses/whatever, until we find something that has traction / makes us money (and it's okay if the shed collapses -- so long as the business knows this too, that it wasn't meant to be a load-bearing, skyscraper-esque thing anyways)"

I won't get into the rabbit hole of talking about dealing with bad business leaders, who want a skyscraper but expect to pay the price of a shack/shed. Let's assume that we are talking about the type of companies (maybe the minority) that are reasonable enough to know and acknowledge the difference. Then what is the game-theoretic/rational thing for them to do, and how does this 10X idea express itself? That's where my argument is coming from.

[mattbrewsbytes]

Its 10x code generation with .5x quality at best and all other parts of the SDLC are at 1.x or worse.

AI is not delivering 10x shareholder value, anywhere. Software developers have quite the level of hubris about how important they are to companies. Yes our work is very complex and takes a certain mindset to do it well. It takes a lot of other roles to have a successful business, many of those roles will use AI to help draft slide decks, emails, etc. and that's the limit for them.

Look at recent companies doing layoffs claiming its because of AI, like CloudFlare and Coinbase, do their reported financials paint the picture that they are crushing it with AI? No, its net losses into the $100's of millions.

[bear8642]

> AI is not delivering 10x shareholder value, anywhere.

A bit facetious, but I'd expect Nvidia and the like providing the "AI equipment" to have a 10× share value at least…

[TheCoelacanth]

As always, the real money in a gold rush goes to the people selling shovels.

[ventana]

It's more like ∞x (or N/Ax if you prefer) because the majority of the projects I did with LLM agents wouldn't have existed without them, because I would've never found enough time to work on them.

One of the latest things I made with Claude was a tool that allowed me to move a bunch of very low traffic Cloud Run services to a single VPS without losing any of the Cloud Run benefits such as easy Docker-based deployment and automatic certificate provisioning. I thought about making something like that for quite some time, and Claude finally made it possible, which makes me quite happy.

The fun thing here is that no other soul genuinely cares about it, or any other code I might publish. The code, especially AI generated, is so cheap that if anyone wants to repeat my steps to get rid of Cloud Run services, they will probably vibe-code their own tool instead of figuring out how to use mine, just like I did that instead of spending time on learning Dokku or similar solutions.

So, yes, 10x and more, but no one cares about the result, which makes the whole 10x measurement less useful.

[TehShrike]

There have been plenty of libraries/tools that got people from "I would like to do foo" to "oh, this tool makes foo possible in under 10 hours, I should start working on foo" in the past. LLMs have done this for many foos, which is great.

But I'm with hansvm - I haven't actually seen anyone plausibly maintain 10x. 10x is different from getting people past their activation cost.

[viccis]

>or N/Ax if you prefer

It's not a matter of preference

[wahnfrieden]

The incredulity at 10x claims is often unearned because how much do these skeptics actually notice and appreciate the depth of work of ten developers collaborating on something (if not their own org)? Dev output slips by quietly. There are reams of unnoticed projects even at the scale of a life’s work.

[Capricorn2481]

This doesn't pass a sniff test at any small organization. And wouldn't these devs see this 10x claim themselves?

[cyanydeez]

I'm assuming the devs are seeing 10x code generation and equating that to the improvement.

It's when they practically ignore the rabbit holes where it's suspect. I'm definitely seeing speed ups. I troubleshot a linux system yesterday with minimal effort using a local llm. It likely would have taken me a few hours to locate all the docs & testing procedures. the llm did it with only a few prompts. To ensure it did it correctly, I had to interrogate it a few times before letting it proceed.

Humans make really bad scientists, and it takes a lot of effort to properly catalog and provide statistics for these things.

There is an improvement, but I doubt any random dev can give a real estimate since before LLMs they couldnt really give you a real estimate anyway. I do know when I encounter a bug now, debugging is almost immediately possible.

[steve_adams_86]

My small organization is noticing output increasing. We're excited about it. I’m not sure about 10x… Like others have mentioned, it’s difficult because you have to measure different workloads.

I build things I never would have. My tooling is better and more robust than ever. I verify and test my work better than ever. I fix more bugs than I used to simply because no one needs to care if it fits into a cycle. I explore and solve more problems in more parts of the application, even if I don’t write code. I take better care of our infrastructure. Performance goes up, bugs go down, AWS resources scale back, costs go down. I’ve paid for my AI usage in scaled back resources several times over at this point.

It might not be 10x but it’s a significant multiple.

[jgrahamc]

I am building a better interface for managing KNX systems than the ETS6 software. Code is here: https://github.com/jgrahamc/koolenex

1. I would not have attempted this without AI assistance because it's a big project.

2. I have built a functional program that I am able to use for real work in a handful of weeks, working part time on this (like literally a few hours per day prompting Claude and Kimi).

3. Had I decided to do this without AI assistance it would have been months of work.

[ern]

I suspect that the goalposts for AI-assisted coding will be moved the same way they've been moved for the Turing Test.

The Turing Test used to matter until it didn't (does anyone even talk about it? was there a big news conference when it was solved?). Likewise every time it becomes easier to ship software, the bar will be pushed higher by sceptics. Ultimately the gatekeeping is going to become meaningless as software becomes "too cheap to meter".

[coldstartops]

Here is a public project.

https://github.com/KeibiSoft/KeibiDrop

It took me 2 years ago around 2k hours to build a cross platform FUSE vault, without using AI assisted tools.

The pain was debugging through logs and system traces. And understanding how things work.

Now managed to ship this one much faster, as an after hours project. Started it in may 2025, and around end of November 2025 started using claude on it.

Just by dumping logs into claude, and explaining the attack vector for the problems, saved me the FML moments of grindings walls of syscalls on 3 platforms.

I would say much easier to progress, and ship with the same rigour, minimize my time, focus and brain power involvement such that I can put the energy somewhere else.

[corndoge]

Yep, the real strength of AI is less in replacing engineering skills, it's more in slashing all the time we spend not using those skills and doing low level research and data correlation tasks instead. Which isn't to say that those tasks aren't valuable in their own way, but in terms of raw output...

[stephbook]

I long for the day when they will supervise CI/CD systems.

Trying to fix syntax errors in strong interpolation on a 5-minute-delay loop is hell.

[Deeds67]

Just create a skill for it -> I call mine `babysit`. It spins up a subagent that polls it every x minutes and auto-fixes it until it's green. I already continue with the next task while it does that in the background

[wallst07]

I do this with our AI PR review checks. We have AI review every PR and commits to PRs... which can cause long running loops of commit<>fix.

So my agent just listens for green checks and no PR comments and loops until those conditions are met.

[coldstartops]

It is possible. I tell to use cli app, and for the agent to ad timer and check the status once in a while. Especially if there is something with a long wait. Also if it can run some validators/ same tools locally, would be much faster.

Might tend to deviate and waste time, needs guiding once in a while, and to check what is it spewing out, point it in the correct direction.

[coldstartops]

I treat the low level tasks as building blocks. You need a grasp and understanding of what is possible with them, but you do not need to remember the exact byte order and syntax. I think the idea is you should structure your workflow in a deterministic way, and just use Claude/ LLM as the interface. It is much easier and enjoyable to use high level language, where you give pointers to building blocks/ directions/ say hard no when you understand things deviate.

If I had to output the code myself, would take around 8 hours of constant writing to get around 1k LoC of code. For FUSE level tricky stuff, I might need to spend 3 weeks for 10 LoC. Very easy to burnout and build pain.

[eitland]

My friend who has never taken a programming class (or even touched an IDE before AFAIK) has now put a small app into production.

Complete frontend + backend + database.

Yes, it is an internal app, but it works and everyone loves it.

Does that count as an example?

(Also I absolutely expect him to need help at some point, but so far it has taken his project from absolutely impossible to 3 weeks of work in between work, renovating his house and being a dad for the first time so I was very impressed.)

[viccis]

These kind of things (internal tools created out of band of normal engineering practices by non-engineers) were amazing back when I did pentesting because the security was always the last consideration. That got harder when SaaS became preferable to rolling your own stuff for everything. Guess things are gonna get fun again for red teams lol

[eitland]

I agree with you.

The danger is not however that only that people write their own tools for calculations and capacity planning etc.

The danger is people make useful stuff that is very fine as long it is just an internal tool, but then someone add credentials to other systems so it can access and maybe even update stuff and it gets exposed to third parties etc and all of a sudden we have a major data breach going on.

[brazukadev]

My friend who has never taken a programming class did the same 10 years ago.

[eitland]

Obviously it was not the same s since models that could write programs were not available 10 years ago.

And if you just mean your friend taught himself programming on his own, well that is actually very cool, I did too back in the 90ies and so did many others here.

My point is that it is now possible to vibe code a full application from frontend to backend today and still not be able to understand a line of TypeScript or anything else.

[brazukadev]

20 years ago we had cpanel where people without programming knowledge can instantly deploy their own apps. Many people got millionaire doing that, I'd say proportionally probably way more than the people vibecoding solutions. This is not as revolutionary as we thought.

[Deeds67]

I'm building an open source Google Photos alternative. Have a look at my project and tell me if you think you could do all this at the same speed without an LLM: https://opennoodle.de

Direct github link: https://github.com/open-noodle/gallery

[wallst07]

It doesn't completely blow away your argument, but you forked Immich and gave it to a LLM. Which is arguably slightly easier than starting from scratch.

Nothing wrong with forks though.

[Deeds67]

Sounds like you're nitpicking on whether or not LLMs make you faster by saying that working on existing code is easier than starting from scratch? I think you've missed the point.

[bronson]

No, they're saying that it was misleading. OP said "I'm building an open source Google Photos alternative" and surprisingly didn't say "based on Immich". This dramatically changes the evaluation of "open-noodle".

We're now in an era where LoC is easy and design is hard[1]. Starting with an existing project means using an existing design, where someone else has already made many/most of the difficult decisions.

10Xing code without caring about design/UX/DX is trivial. Literally anybody with a token budget can do it. But they probably won't ship a good project. Not with current frontier models.

[1]: design has always been hard. But now it's even more difficult because of code veloocity and because LLMs are happier to work with bad code than humans. It's never been easier to go deep into rabbit holes without noticing a single issue.

[timacles]

Pretty much every example in this thread is "I forked some existing project and made changes I like".

The main thing they dont realize is: 1. These are mostly superficial changes. 2. The only thing they 10xed is their ability to "start" on something. 3. They have not produced actual value. Their project/fork is just a version they think they prefer. But It is less maintainable, and less robust/useful for others due to its specificity.

My observations is that consistently these arguments are made by: inexperienced devs who simply dont understand what it takes to produce value in the real world.

LLMs CAN 10x you (in very specific areas like prototyping), IF you understand how to deliver this value, but that is the hard part. It has always been the hard part.

[Deeds67]

What are you debating here? I replied to a comment asking for examples of public work displaying that LLMs can 10x a human's output.

https://opennoodle.de/roadmap/

Look at what I built, these are not all simple designs.

[matheusmoreira]

I have a programming language project: lone lisp. It's on GitHub. I asked Claude to analyze the commit history before and after AI and the result was: with AI I'm committing around 8x faster than before. Lone experienced a literal explosion of features, improvements and fixes after I subscribed to Claude.

And this is the project I care most about. I review every single line of code the AI outputs. I push back on everything it does. I reword every commit message. I make every effort to understand how everything works before committing it to master. I cook branches for days and I don't merge until I think it's perfect.

Still gave me an ~8x improvement.

The latest development: shaped objects, like Self and V8. I asked Claude about it and it just implemented it in like 10 minutes. Boom, instant ~20% speed improvement. I read the code and it turned out to be almost obnoxiously simple. It basically converts hash tables into arrays internally, and deoptimizes back to a hash table if anyone deletes keys from it. I'm still reeling from the sheer absurdity of it.

[smartmic]

It is worth to have a detailed look into the original essay and its arguments. My interpretation is https://smartmic.bearblog.dev/no-ai-silver-bullet/

[oaxacaoaxaca]

I can describe private efforts about a couple recent projects that made me finally believe that Claude Code can actually be a 10x multiplier on certain work.

We decided to integrate our SaaS into Microsoft Business Central and NetSuite as plugins into those systems. BC has its own programming language, called AL, that has a lot of idiosyncrasies from any other language I've worked with. And NetSuite plugins are written in SuiteScript, which is a custom JS runtime with a ton of APIs to learn.

In the "before", it would've taken 5 developers a year or more to build those integrations. I did both by myself in well under a year. Thank you Claude.

[wallst07]

I can state one thing that I'm sure a lot of people connect with, and I don't know if this is 10x, probably not.

I've always been a backend engineer, never front end. And almost every team I've been on has lacked any front end skills at all, so all our tools end up being a mash of scripts, maybe sometimes an API.

Now we are all front end engineers creating UIs for things we could never do before, and this starts API first development, so the CLI + UI are just calling APIs. Nothing new here, but this used to be what teams do, now a single person does it.

[rjh29]

It would not have taken you long to learn frontend if you wanted to. Now you can use AI to generate it but you don't understand any of the generated code.

[vga1]

It's often much more than 10x, because AI makes things so much faster and easier that we are now doing many things we wouldn't have bothered to do at all before. And there's no reason to believe we're near the finish line yet as to how good LLMs can get.

[eloisant]

It's a 10x in areas where I'm not very good/experimented at. Or perhaps even more. For example I'm mostly a backend developer, I used to be a full stack dev a long time ago so I know how to make front-end but my knowledge there is outdated, I've forgotten half of it, it takes me time to get back to it. I'm also not good at creating a web UI so in the past I was using frameworks like Bootstrap or Foundation, leading to sites that looked good but very generic.

Now with AI, I can easily create a nice looking front-heavy web app.

See this for example: https://github.com/erwan/sovereign-cards-database

I would never have bothered doing that without AI.

In areas I'm more familiar with, like back-end software, it's maybe more of the 2x or 3x.

[mohamedkoubaa]

There are some things around the corner. The best engineers aren't going 10x on Claude to build the next goofy SaaS app.

[pydry]

There is verifiably a flood of new projects. The selfhosted subreddit had to put in checks coz too many people were complaining about vibecoded slop.

iOS submissions are way up.

What I havent seen is existing open source people develop 10x faster.

Or, anything vibe coded get popular which wasnt just a gimmick.

Just a tsunami of slop.

[lp4v4n]

I'm curious to check how faster AAA games will hit the market in the next years compared to the pre-LLM era. Or how much of the aging COBOL code base out there will disappear in the next decade.

When concrete things like that start to happen, then I will start to believe in the 10x claim.

[chickensong]

I'm not sure those are great examples. Why not just consider normal apps?

I don't think we'll see AAA game velocity change until asset generation progresses quite a bit, not to mention stuff like rigging. Even then, there's still a layer between code and engine where you have to wire everything together which an LLM will struggle with.

Replacing some old COBOL is probably more of a management decision based on appetite for change and politics rather than development speed.

Aren't there some measurable things like github repo creation, PRs, app store additions, etc. that can be correlated to LLM adoption? Didn't Show HN have to get throttled after LLMs arrived?

[Towaway69]

I think your answer is the reason why. LLM performance is fine when applied to everything they can do.

Take LLM out that safe space and suddenly they are no silver bullet, in fact they are unless.

So of course those making the 10x claim mean in the safe space where LLM can handle all activities required. You can’t have it both ways 10x and difficult and confusing tasks for LLMs.

[chickensong]

Right, I get that. I'm just saying it seems wrong to throw up minority examples. Nobody is pumping out AAA games at speed with LLMs, nor is anyone claiming to do so. There will likely always be some areas where LLMs are bad or useless.

How many people are writing crud apps using mainstream languages vs COBOL though? You don't need 100% silver bullet 1-shot everything, just to recognize the signals that for many use cases, there's a significant shift happening. The safe space is expanding and velocity is increasing.

[Towaway69]

Definitely the safe space is expanding but how fragile and expensive is this expansion?

AI requires a larger amount of fragile resources to work as opposed to an editor, keyboard and a human.

It some sense it’s a bit like the bitcoin revolution that slowed down once transaction times ballooned out. And blockchains didn’t replace databases as expected. Probably for very good reasons: resources required v. results delivered.

I personally agree that AI is great technology for some great new tools. But we still haven’t found its limits: cost v. results. That happened with bitcoins and blockchains is still outstanding for AIs.

[chickensong]

The resources are definitely an issue. I'm still sucking from the corporate teat, but my hope is that by the time the frontier race slows down and they tighten the screws too much, the local models will be good enough. It sounds like recent local models are already getting pretty good for normal duties, but honestly, if it all goes away tomorrow, that's fine too. I'll go back to the old ways. I'd miss the informational capabilities more than the coding capabilities, but I'm no stranger to man pages.

As an aside, I still think there's a place for blockchains. They're not a good replacement for a typical database, but I think some of the concepts are useful. The idea of distributed ledgers and smart contracts have a lot of applications IMHO, particularly in government. The traceability of transactions seems like a great fit to enable transparency of government spending. Of course, governments are allergic to that idea for the usual reasons, but it's still a nice idea. Distributed computing is hard, and it's a shame that blockchains were usurped by crypto bro scams. I'm still rooting for the folks who are trying to push distributed technology forward though.

[plausibility]

I feel like that’s tied to the hardware the companies are using. All the banks I’ve worked at run z/OS mainframes, can they even deploy modern run of the mill Go/Python/Rust code or is getting off COBOL reliant on hardware changes?

[HarHarVeryFunny]

> AI is the silver bullet - my output is genuinely 10X what it was before claude code existed.

This reminds me of ThePrimeagen noting that Dario was right about 90% of all software being written by AI. 90%+ of all useful software is still being written by humans, but now we've also got non-programmers like Gary Tan pushing the button to generate garbage piles of AI generated code at 10x the volume of what humans are generating.

Or look at Claude Code itself, the poster child for what AI generated code looks like, especially when you're operating in YOLO "never mind the quality, count the LOC" mode. Over a half million lines of bug ridden crap when 10-50K could have done the job.

https://techtrenches.dev/p/the-snake-that-ate-itself-what-cl...

[duskdozer]

>https://techtrenches.dev/p/the-snake-that-ate-itself-what-cl...

Ugh, I've started having a visceral reaction to that typeface+card-layout+color-scheme combo; is the author using it ironically?

[HarHarVeryFunny]

I browse on my desktop and all these mobile-optimized blog sites look like crap regardless of color schemes etc, so I try to ignore that.

[mohamedkoubaa]

It's always worth remembering that code is a liability while software is the asset. Wiring 10x more code is accumulating 10x the liability, with the often unjustified belief that the software is 10x as valuable. It might be, but that's what the market is for.

[eloisant]

Software written in Big tech companies is probably written at 90% with AI.

Now you could claim that software from Google/Meta/Microsoft is useless, but billions of humans rely on it every day.

[HarHarVeryFunny]

I highly doubt that, unless you are talking about something much more specific like test cases.

There is certainly no sign of these companies becoming more productive.

Most of the software that "billions" of humans are relying from any of these companies are things like Microsoft Windows, Microsoft Office, Google Search, FaceBook, that were not written, or rewritten, in last 1-2 years, so were certainly not written by AI.

[marcosdumay]

> There is certainly no sign of these companies becoming more productive.

Oh, if you look at real signs, like uptime and number of bugs, they are becoming very clear.

But it's not clear how much of it is caused by the layoffs and how much is because of LLMs.

[HarHarVeryFunny]

Well, not exactly productivity, but yes there are some symptoms of a reduction in quality from some companies. I was about to say not the three mentioned, but GitHub (owned by Microsoft) is certainly one, and Amazon seems to be having an uptick in outages that are anecdotally linked to use of AI. Anthropic, who we know are using AI a lot internally also have reliability problems.

[cdavid]

The main point of mythical man month was that communication cost across people was the main cost as project grow in complexity.

So increasing individual output by itself is not enough to affect the argument. It could, if you also reduce the size of people needed for a project, where people are everyone included in the project, not just SWE. But there are strong forces in large orgs to pull toward larger project sizes: budgeting overhead and other similar large orgs optimize for legibility kind of arguments.

IMO the only way this will change is when new companies will challenge existing big guys. I think AI will help achieve this (e.g. agentic e-commerce challenging the existing players), but it will take time.

[mbeex]

That is far from proven, 'far' being the keyword here in another understanding.

At _this_ moment, AI is in the state of producing things - if you like with factor 10 or more. But what will come afterwards, when all this mush of code shall create _reliable_ results. This means not man month then, rather man years or decades to fix this billion and maybe trillions lines of opaque probabilistic LOC. You have to take the mean of these two stages, if nothing qualitative happens to the models.

[skydhash]

> that has led to a 10X increase in the speed of software development.

> AI is the silver bullet - my output is genuinely 10X what it was before claude code existed.

Those are not the same.

You can add 5 different features to a project and still provide less value that the 5 lines diff that resolves a performance bottleneck.

[jrumbut]

I agree with this sentiment but I think LLMs are really close to the Brooks idea of a silver bullet.

I don't know if, overall, it's a 10x improvement or 6x or 14x but it's a serious contender. Part of it is the LLMs are very uneven in their performance across domains. If all I build is simple landing pages, it might be a 100x improvement. If I work on more complex, proprietary work where there aren't great examples in the training data then it might be a 10% improvement (it helps me write better comments or something)

[BlackFly]

All available evidence points to it being an incremental improvement at best. Higher claims are attributable to the psychological effect of the AI sycophancy problem which erases the Dunning-Kruger effect and makes even experts extremely overconfident.

You still have to read the output of your LLM. Learning by reading alone and not doing is not nearly as effective.

[winrid]

"claude, connect to a k8s pod in prod and grab a 30s cpu profile, analyze and create a performance test locally for the top outlier, verify your fix and create a PR"

[ssivark]

So there's input (prompts/requests/tokens), then there's outputs (lines of code) and there's outcomes. How much have the outcomes improved? Not just yours, but I'm more curious on the outcomes with regards to the actual need your projects are solving.

[whateveracct]

This was true as programming languages evolved too. It was so much easier to write scripting languages than C. You could crap out scripts like crazy - no cc refusing to give you a binary to get in your way.

Clearly..it still wasn't a silver bullet. Because output as a metric is a bad one. I thought it was only one managers valued..but apparently Anthropic has convinced devs to value it finally? i guess it def hits that dopamine receptor hard.

[majormajor]

First counterexample that comes to mind: Rails vs 90s networked/shared line-of-business crud app development was a 10x factor. It also enabled a lot of internal tools that wouldn't have been worth doing without it.

But after people's expectations adjusted it was just back on the treadmill.

I don't think we've found a new steady-state yet, but I have some gut feeling guesses about where it's going to be.

[Pamar]

90% of my my experience has always been dealing with large-ish corporate systems. I am in Europe, so YMMV even when talking about corporate instead of smaller scale projects.

In my experience stuff like RAILS had negligible impact in my field because companies would always require solid backup from some big name vendor (MS, Oracle, IBM, Sun - back in the day, or even SAP).

So most if not all the smaller silver bullets did not even make a blimp on the radar... and stuff like Java or .NET, while definitely better than C or COBOL... did not really deliver in terms of productivity boost (in part because, as noted in the message I am answering to, expectations kept growing at the same pace)

[majormajor]

>90% of my my experience has always been dealing with large-ish corporate systems. I am in Europe, so YMMV even when talking about corporate instead of smaller scale projects.

>In my experience stuff like RAILS had negligible impact in my field because companies would always require solid backup from some big name vendor (MS, Oracle, IBM, Sun - back in the day, or even SAP).

>So most if not all the smaller silver bullets did not even make a blimp on the radar... and stuff like Java or .NET, while definitely better than C or COBOL... did not really deliver in terms of productivity boost (in part because, as noted in the message I am answering to, expectations kept growing at the same pace)

I've always been in small-to-midsized US corporate where Oracle etc were generally "no way are we gonna spend that much" but if someone can hack a decent thing together and run it on a spare server... that got traction 10-20 years ago.

I'm curious if those large corporations are more homegrown-code-by-AI-friendly than they would've been towards homegrown-Rails-app? A lot of the same potential problems exist.

[Towaway69]

In particular if that steady-state requires 4 to 40GB blob of binary code to be installed or an internet connection to an AI SaaS provider and a credit card.

I remember when coding was free as in beer and freedom!

[bitwize]

It's okay. In the near future people will not own a computer of significant capability at all, so it's not like they'd even be able to develop without a cloud connection in the first place.

And, for the most part, they will be okay with this. Gen Alpha or Beta will tell each other how morally wrong it is to expect for everyone to own a computer or even a smartphone, citing the environmental impacts, slaves mining coltan, and the toxic emotional effects upon people who grew up in the Social Media Dark Ages. Much like present-day Hackernews feels about personal automobile ownership.

[bitwize]

Ah, Fails. "Before we made x improvement, the app had to restart 400x a day, now it's only 10x!"

For all the complaining we do about "enshittification", we (Hackernews, the broader industry, whatever), are perfectly willing to pay the price of stability and performance to get a little development speed. That's one prong of how enshittification happens. "I can make compromises in the quality of my product because time to market is the one thing, the only thing that matters in this move-fast-break-things economy—and pass my savings on to the customer (in the form of hidden costs)!"

[batshit_beaver]

10x the amount of code or features =/= 10x the speed of software development.

[lovich]

And 20x the bugs.

I too can vastly increase my speed of development when I stop caring about the quality.

[furyofantares]

There are sizes of projects where it's true, and that size is growing.

[MattDamonSpace]

Doesn’t necessarily but does sometimes unless you have a concrete alternative

[esafak]

How are you defining speed of software development?

[bogdanoff_2]

How is that not the same thing?

[tudelo]

Most of my work has been in core infra at large companies. Having the code written faster does not change rollout velocity all that much... It does help with signals and idiot proofing on bugs but when things break and cost real (very real) dollars AI is not an explanation. In that instance, its not even close. Development might be 10-20 percent of the actual work to get a change out.

[cortesoft]

AI can also speed up the release processes

[vehementi]

To an extent it can help reduce wasteful steps. But there's nothing AI can do that can make it less irresponsible to reduce soak times, stagger the release across many environments, etc.

[ben_w]

Code is always easy to multiply fruitlessly, always has been.

Features are harder to show the limits of, but have you ever had a client or boss who didn't know what they wanted, they just kept asking for stuff? 100 sequential tickets to change the contrast of some button can be closed in record time, but the final impact is still just the final one of the sequence.

Or have you experienced bike-shedding* from coworkers in meetings? It doesn't matter what metaphorical colour the metaphorical bike shed gets painted.

Or, as a user, had a mandatory update that either didn't seem to do anything at all, or worse moved things in the UX around so you couldn't find features you actually did use? Something I get with many apps and operating systems; I'd say MacOS's UX peaked back when versions were named after cats. Non-UX stuff got better since then, but the UX (even the creation of SwiftUI as an attempt to replace UIKit and AppKit) feels like it was CV-driven development, not something that benefits me as a user.

You can add a lot of features and close a lot of tickets while adding zero-to-negative business value. When code was expensive, that cost could be used directly as a reason to say "let's delay this"; now you have to explain more directly to the boss or the client why they're asking for an actively bad thing instead of it being a replacement of an expensive gamble with a cheap gamble. This is not something most of us are trained to do well, I think. Worse, even those of us who are skilled at that kind of client interactions, the fact of code suddenly being cheap means that many of us have mis-trained instincts on what's actually important, in exactly the way that those customers and bosses should be suspicious of.

* https://en.wikipedia.org/wiki/Law_of_triviality

[duskdozer]

>Or, as a user, had a mandatory update that either didn't seem to do anything at all, or worse moved things in the UX around so you couldn't find features you actually did use? Something I get with many apps and operating systems; I'd say MacOS's UX peaked back when versions were named after cats. Non-UX stuff got better since then, but the UX (even the creation of SwiftUI as an attempt to replace UIKit and AppKit) feels like it was CV-driven development, not something that benefits me as a user.

I can't name a single new feature Android has gained since version 13, or at least one that I am aware I use. I have a large handful of performance issues, feature removals, and UI annoyances that have been introduced, though.

[CreepGin]

"nine women can't have a baby in a month". Speed of software development is not pure output.

[whateveracct]

for certain monkeys, they think it is tho

there are entire C corps of monkeys out there

[__s]

At Microsoft I wrote a feature to support customer setting a preferred AZ for their database. Took a couple weeks as a side project. Nearly 2 years later it reached customers

Extreme example, but exemplifies point

[jen20]

Writing code is a part (sometimes a big part, sometimes not) of delivering software to production. The overall system throughput is the interesting thing to look at.

[boron1006]

Conversely, the value of software has dropped to 1/10 of what it was before Claude code existed.

I’m being glib, but there’s a whole class of software (eg simple crud apps) that just don’t have any marginal value anymore. So it doesn’t matter if it’s 10X faster or 100X faster. 100 x $0 is still 0.

[zemvpferreira]

You mean the price of software, as well as the cost. The value (to the user) is the same if not more.

[boron1006]

Unless the user just vibe-codes their own version.

Which is what I’m seeing at my job. All of these “afternoon vibe code” projects never actually get users because everyone just vibe-codes their own.

[darkwater]

But GP statement is still true. You just cut out a middleman.

[boron1006]

But “your software” isn’t bringing value anymore if people don’t use it.

The things that the software does might have value, but the marginal utility of your software is effectively 0.

[codingdave]

The disconnect here is a lack of proof that your increase in personal output actually increases the speed of software development. Considering: https://en.wikipedia.org/wiki/Ninety%E2%80%93ninety_rule as a joking, but true fact of how software projects go, does AI skip that 2nd 90%? Or do we add a whole new bottleneck of review and corrections, and still need to code that last 90%?

When I measure software dev, delivery of code isn't even a metric I care about. It is a key part of the process, to be sure, but I care about results - Did we ship? Did it work? Do we have happier customers and a smaller bug list?

In my experience, while I can answer "yes" to those questions on people who use AI assistance surgically, applying it where its strengths lie... I can answer an emphatic "No" for the teams I've worked with who are "AI-first", making the AI usage itself part of their goals.

[OtherShrezzing]

You’re describing output while the essay is discussing productivity.

If you’re 10x more productive, someone is willing to pay you 10x as much as they were last year, because you’re producing 10x as much value as before.

Has your salary increased 10x?

[doesnt_know]

I don't believe the 10x claims, but since when has salary been any indication of productivity?

[OtherShrezzing]

Productivity is a value measured in dollars. So if you’re 10x more productive, someone somewhere is making 10x the $ value from your output.

You should expect this to be reflected in the labour market somewhere. Maybe not your own salary, but in somebody’s salary.

[tehjoker]

One of the most important graphs in economics shows a divergence between increases in labor productivity and worker take home share since at least the 1970s

maybe you are thinking ceos or shareholders

[dgellow]

In economics productivity is generally the outputs divided by the inputs used for production. Are you talking specifically about capital productivity?

[dgellow]

> If you’re 10x more productive, someone is willing to pay you 10x as much as they were last year, because you’re producing 10x as much value as before. Has your salary increased 10x?

That's too simplistic because the rest of the economy isn't static. Everyone is getting access to AI tooling, if the whole field gets a productivity increase then the baseline changes, you don't just become 10x more valuable. The previous work is now way less valuable than it was before. It's also not clear to me that the productivity gains from AI convert 1:1 into profit gains

[aryehof]

Salary stays the same. A bunch of others are fired. You’re expected to produce their level of output as well as your own. After all, you’re 10x more productive now?

[OtherShrezzing]

I guess the follow up question to this is “have nine of your colleagues been fired?”

[SoftTalker]

They are paying Anthropic instead of you, because you aren't producing that value, Claude is.

[gabriel-uribe]

Salary has had weak correlation to productivity gains since last century.

[RaftPeople]

> Notably, his essay “no silver bullet” states that there has never been a new technology or way of thinking or working that has led to a 10X increase in the speed of software development.

I think the statement is generally true, but I also think there are specific tools that do vastly increase dev time for something that follows that specific pattern.

Program templates and also code generation have been used forever to simplify and speed up specific types of programs, like all of the CRUD programs in an ERP system for maintaining the hundreds to thousands of different master data like Customers, etc.

Those approaches can speed a specific activity that follows a specific pattern by some multiplier (e.g. 4x or 10x).

But the trade-off is time to build the template or code gen vs number of instances it will be used.

I think where "no silver bullet" has the strongest case is for something completely new where the patterns and templates have not been established.

When I think about LLM's and compare to past templates and code gen, I wonder what exactly is the nature of the LLM trade-off in the broad sense. For a template, it's pretty clearly up front design+dev compared to number of instances of usage of the template.

LLM's are more general and more broadly applicable, but still not the same as a human. Is the trade-off purely cost that was sunk into the model and tool that now needs to be recouped by the AI company? (e.g. charging the actual $1,000 to $1,500 that it really costs instead of $200

Or are the big trade-offs and costs going to show up in the future: the dwindling of human expertise due to reliance on the tool and the loss of understanding of complex systems.

[TimTheTinker]

AI is certainly able to increase coding speed, especially for experienced engineers who can design the analytical parts themselves (data structures, interfaces, invariants, and process), but in large projects and/or organizations, queuing theory (especially as understood by lean development practitioners like Don Reinertsen) is going to be nasty.

Lean development theory teaches us that in a multi-workstream, multi-stage development process, developers should be kept at roughly 65-75% utilization. Otherwise, contra-intuitively, work queue lengths increase exponentially the closer utilization gets to 100%. The reason is that slack in the system absorbs and smooths perturbations and variability, which are inevitable.

Furthermore, underutilization is also highly comparable to stock market options: their value increases as variability increases. Slack enables quick pivots with less advance notice. It builds continuous responsiveness into the system. And as the Agile Manifesto tells us, excellent software development is more characterized by the ability to respond to change than the mere ability to follow a plan. Customers appreciate responsiveness from software vendors; it builds trust, which is increasing in value all the more with the rise of AI.

But AI-driven development threatens to increase, not decrease individual engineer utilization. More is expected, more is possible, and frankly, once you learn how to guardrail the AI and give it no trust to design well analytically, the speed a senior engineer can achieve while writing great code with AI assistance often feels intoxicating.

I think we're going to go through a whole new spat of hard, counterintuitive lessons similar to those many 1960s and 70s developers like Fred Brooks and his IBM team learned the hard way.

[teddyh]

For your sake I hope that your pay is determined by your “output”, and not your long-term usefulness.

[conartist6]

Oh spare me! Anyone can "output" 10x more code. Fred knew you could slap 10x more people on a team and "output" 10x more code.

What this article explains is why despite your feelings of untouchable success, on average the experience of using software just keeps getting worse and worse and worse, making this the worst era for software quality that I've ever lived through

Didn't we already do this with every company looking to hire "rockstar programmers"? I don't recall that that ended well.

[nonameiguess]

This seems like somewhat of a mischaracterization. He contrasted improvements in software with improvements in hardware, saying we'd never have something like a Moore's law for software where performance doubled or cost halved equally rapidly. Churning out software faster doesn't mean it's any better.

We also seem to fall into these ruts of not understanding what is meant by labor productivity. When an economist is presenting the common outputs / inputs measure, they don't mean raw quantity of output. They're talking about the value added by outputs divided by the value of inputs. Churning out software faster that doesn't earn anybody additional revenue is not making us more productive. It's disheartening that even c-suites with business education don't seem to understand this. That's not to say there is no productivity gain. Plenty of AI-adjacent hyperscalers are seeing ridiculous growth right now, but no non-startup is seeing revenue 10x what it was the year before, not even NVIDIA.

A lot of this is just basic diminishing marginal utility. There is only so much value to be added. Software is usually either a semi-automated controller or human decision making augmenter to some kind of physical manufacturing process, or entertainment, when we talk about ultimately delivering value. Everything else is an intermediate input. We can only be so entertained. For physical goods, we have food, space, clothing seemingly at a sufficient level to satisfy just about everyone, with the reasons for value not being maximized having to do with distribution. Unless your software manages to solve borders, bigotry, cultural incompatibility, poverty, mental illess, physical illness, violence, I'm not sure what the other big rocks are. Software can absolutely be a key part of infrastructure to facilitate distribution. That's exactly what the Internet is, along with all the backend business and logistics systems out there in existence. But without hitting the true big rocks, where is the 10x value supposed to come from? We're talking incremental gains simply because we're not in the dark ages any more and incremental gains are all that's there. Short of Star Trek style replicators and transporters, I'm not sure what could realistically multiply global value by 10.

Without the value, then sure, you may be churning out 10 times as many discrete projects used by at least one person, or 10 times as many lines of code, but that was never the point. Your personalized notes and grocery ordering apps you share with your wife might excite you for a few weeks, but I can assure you they aren't going to revolutionize your life.

[gensym]

I've been thinking about this and have wanted to discuss it with people. I think the 10x thing has been broken, but I don't think it's because the premise of "No Silver Bullet" was false - I think it's because LLMs have the ability to navigate some of the _essential_ complexity of problems.

I don't think anyone has really wrestled with the implications of that yet - we've started talking about "deskilling" and "congnitive debt" but mostly in the context of "programmers are going to forget how to structure code - how to use the syntax of their languages, etc et etc)." I'm not worried about that as it's the same sort of thing we've seen for decades - compilers, higher-order languages, better abstracts, etc etc etc.

The fact that LLMs are able to wrestle with essential complexity means that using them is going to push us further and further from the actual problems we're trying to solve. Right now, it's the wrestling with problems that helps us understand what those problems are. As our organizations adopt LLMs that are able to take on _those_ problems - that is, customer problems, not problems of data, scaling, and so forth - will we hit a brick wall where we lose that understanding? Where we keep shipping stuff but it gets further and further from what our customers need? How do we avoid that?

[globular-toast]

Even assuming you are correct, does your "output" being 10x actually mean "a 10x increase in the speed of software development"?

[deadbabe]

Just because code has been put out does not mean the software is “developed”.

[slopinthebag]

10x would only be possible if your output was low before Claude Code

[hatsix]

I've found that I can have 10x output, so long as I don't expect anyone to review your code...

[slopinthebag]

I can get 100x output, if we're counting lines of code!

[emp17344]

I bet get I could hit 1000x output of random characters produced by smashing my hand against the keyboard.

[dzonga]

your output !!

but is the industry output over 10X ?

[johnyzee]

It's mostly slop. And sometimes slop is good enough. But Fred Brooks was talking about actual software systems, not a shop front for an amateur wine importer.

[raincole]

The premise of "no silver bullet" is wrong (LLM just made it clear, but it has always been wrong).

The premise is that the software development had been mostly "essential complexity" rather than "accidental complexity." But I think anyone who worked as SE in the past decade would have found the opposite is true.

It's not only that software development is full of accidental complexity. Programmers (and the decision makers above them) have always been actively creating accidental complexity. Making a GUI program hasn't gotten easier since Visual Basic. In fact for each JavaScript framework and technique that wraps around DOM render engine, it has got harder over years. Until LLMs made it easier again (by creating a permanent dependency on LLMs. If you intend to edit the code manually afterwards, it became even harder!)

[Jach]

I think the fuller version of the "'no silver bullet' is wrong" claim is at: https://blog.ploeh.dk/2019/07/01/yes-silver-bullet/

A weaker claim is that maybe there's no single silver bullet but there have been many bronze bullets that add up to more than a single silver bullet. I readily endorse at least that and think it's rather easy to justify.