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Eight Myths on Software Engineering and GenAI

291 points by tchalla 2mo ago

Supermancho 2mo ago
|--------|-------|------|------|-------|------| |Contract|Product|Design|Coding|Testing|Deploy| Writing Code Isn't the Bottleneck, until writing code is the bottleneck, until it's not again.
- sublinear 2mo ago
  You forgot to add "coordination" to that pipeline. That is easily far and away the biggest source of delays. That includes talking to vendors, meetings with every layer of stakeholder when just one person digs their heels, etc. That is truly the final frontier for "AI", and one that it will likely never cross. That would be when even the execs and upper management feel threatened by "AI". But, since they also delegate so much, you often see someone at the bottom of the totem pole in those meetings. This is why nobody is getting replaced by "AI". We really need to move this discussion away from the scifi stupidity already. There is no singularity or godlike AGI about to take over the world. I hate to use awful terms like "synergy" and "teamwork", but they do have a lot more substance and truth to them than any perceived threat from "AI".
- pstuart 2mo ago
  Getting a usable PRD is often the bottleneck.
  - hahahaa 2mo ago
    The real bottleneck is Omega Star getting their shit together. And I ain't joking.
    - Exoristos 2mo ago
      Or SPS Commerce. Evidence is becoming unconvincing that they're even in business anymore.
osigurdson 2mo ago
It seems that this could have been expanded or contracted to any Fibonacci number of myths.
simonw 2mo ago
> We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent. Anyone else finding they're spending more time writing code (or at least driving agents to write code) now? 14% used to feel about right for me - I'd spend the rest of the time researching approaches and libraries, planning things out in issues, or sometimes just thinking really hard about problems I ran into. Now... I still do those things, but I'm doing many of them faster - and I'm often doing them while my coding agents are churning away on code. There's also this weird effect where the harder a problem is the more I can get done in parallel with it, because an agent might need to spend 20 minutes on it without my involvement.
- enraged_camel 2mo ago
  Yeah. I spend most of my day driving agents to write code, verifying the results, orchestrating work streams, and so on. The rest of the time, a Fable agent is organizing work in Linear/Jira and making sure coworkers are getting their stuff done in a way that won’t conflict.
- geoduck14 2mo ago
  I used it to write SQL and make dashboards. Back in the day, I would spend a lot of time doing that, then I changed roles. I dipped my toe in it recently and used AI exclusively. I would send a prompt, see the output, decide if that is what I wanted or not. I kept my brain in "what-if mode" and I let the LLM handle the technical specs.
  - TheOtherHobbes 2mo ago
    'What-if' mode is a game changer. And underrated. The cost of prototyping has crashed. So you can A/B/C... various ideas, test them in the real world or by personal preference, to taste, and converge on designs that work for you. This used to very hard and expensive. Now it's so cheap it makes the idea -> test -> refine loop much tighter and faster.
    - geoduck14 2mo ago
TrustChain 2mo ago
The 14% coding time figure is one of those stats that sounds surprising until you actually track your own time. When I started building a coding agent with persistent state, I realized how some days are spent with minimal actual typing, most of it is design, reading code, debugging, problem solving, and context-switching. But I'd push back on one thing the article implies that AI is automatically a productivity win. It's not. Some days I've shipped two months of work in a few days with AI. Other days, like today, I've burned a whole day and gotten almost nothing done because the proper research was not done by me or multiple agents. The bottleneck for AI can be the human understanding of how to optimally use the tool. While the bottleneck for the human can be not maximizing multiple agents, or the input the user enters, then the retention of the output. If the user's input is lost, the output falters. If the user doesn't understand what the AI output is, there is going to be a problem eventually. The article touches on adoption barriers (Myth 7), but it doesn't really get into the ego piece. There's still a wave of experienced devs who either refuse to adopt AI, or use it quietly and don't share what they're doing. That slows the whole team's learning curve. At this point, I think it's pretty much understood that you should be using AI as a dev — not to replace your skills, but to accelerate them. That means still learning new languages, still writing code, still troubleshooting. The tools change, but the craft doesn't. I think the article is right that the real leverage is organizational, not individual. The teams that succeed with AI aren't the ones giving everyone a license — they're the ones rethinking how they review, test, and maintain code. What I'm still uncertain about is how to measure whether AI is actually making systems better, not just faster. Lines of code is clearly a bad metric, but I haven't seen a good alternative yet. What metrics are people actually using that feel meaningful?
- imrozim 2mo ago
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kylecazar 2mo ago
I don't understand Myth 1 (Developers Spend Most of Their Time Writing Code). They quote a study in which developers report to spend 11-14% of their day coding. The rest is stuff like solution design and meetings. The insinuation is that AI can at most automate 14% of your day. The problem with this argument is that once you have code, some (not all) of the precursors to code go away.
- unknownfuture 2mo ago
  Okay. Show me the evidence that AI has an impact on productivity when doing design work. Or reducing meeting load. My own experience is that AI doesn't tighten the design cycle, and in fact might extend it by encouraging gold plating.
  - simonw 2mo ago
    What kind of shape of evidence would you find convincing?
    - bluefirebrand 2mo ago
      People working fewer hours :)
      - kaashif 2mo ago
        Damn, looks like we have lower productivity than cavemen!
      - keeda 2mo ago
        Sir, this is Capitalism.
    - unknownfuture 2mo ago
      Self-reported or observational data capturing time spent for categories of task ala every other similar study in this space? This isn't exactly novel territory, here, Simon. Let's not pretend I'm asking for something strange, unprecedented, or unreasonable.
a_bonobo 2mo ago
>On my visits to the Bay Area, I would ask AI researchers or interns why they are doing their current research or projects, when in a year or three agentic LLMs could probably do them; This is such a weird point to make that doesn't become correct just because everyone makes it, all the time. Why clean the ocean if some magic future tech will clean them? Why save the world now if some benevolent AI is 'just around the corner' and will do it for us? And people have been making this point for years now, and it's not like my job got any easier. I just got more AI. https://www.poetryfoundation.org/poems/51294/waiting-for-the-barbarians https://www.poetryfoundation.org/poems/51294/waiting-for-the... And I say that as someone who uses Claude Code in complex environments almost hourly; I, as the human, still have to do the thinking as Claude still 'can't jump' [1] and I have seen no evidence that they (or similar AI, any time soon) will 'jump' like a human brain does. [1] https://www.tomzahavy.com/files/llms-cant-jump.pdf https://www.tomzahavy.com/files/llms-cant-jump.pdf
- Patient0 2mo ago
  Sorry where in the article does it make this point? I cannot find the text "On my visits to the Bay Area" anywhere in the original article.
  - decimalenough 2mo ago
    It doesn't, GP was responding to the Gwern story at https://news.ycombinator.com/item?id=49174900 https://news.ycombinator.com/item?id=49174900 but posted in the wrong place.
- esafak 2mo ago
  Also, if you believe your well-paying job is eventually going to be automated you would be prudent to bank the money while you prepare for the future.
- fhub 2mo ago
  > I, as the human, still have to do the thinking as Claude still 'can't jump' I still have to do quite a bit of thinking but the amount of of thinking I do per task is trending down. I agree LLMs are not good at abduction but very few humans are either and very few jobs/tasks require it. I can't talk for researchers jobs though. But perhaps fewer researchers would be desired by these labs (not none).
mkozlows 2mo ago
I feel like all you need to know about how seriously to take this is that they cite that ancient early-2025 METR study, and describe it in the text as "recently one even found..."
- katzgrau 2mo ago
  Same thought - 80% through reading it occurred to me to check the citations. A few items from 2025 and most well before that. So much has changed since late 2025 one can’t really draw any conclusions from this. In fact, I’m guessing things will continue to move so fast that by the time one were to execute a survey of developers, many of the responses and findings are no longer relevant.
  - joshuastuden 2mo ago
    Exactly. I saw them using things from 2025... AI sorta sucked then and didn't really "take off" until that Opus drop in December or whatever it was.
  - greenhat76 2mo ago
    Your point really goes both ways, we really don't know anything about how LLM usage is affecting anything. No one knows, it's the wild wild west, which is whatever. But I think no one can really draw conclusions from what's happening in tech right now. Reminds me of COVID and how everyone was fighting over early trends during that time.
- CompoundEyes 2mo ago
  I felt the same and why didn’t the authors look over METR’s recent material? https://metr.org/blog/2026-05-11-ai-usage-survey/ https://metr.org/blog/2026-05-11-ai-usage-survey/
  - Izkata 2mo ago
    The whole point of the 2025 one is that they found the self-reporting to be significantly inflated, which is why self-reported surveys like this one are hard to trust.
abratabia 2mo ago
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physix 2mo ago
>a “good” workday, engineers spent 18 percent of their time “coding” (not including bug fixing, testing, etc.) I must be a crap developer, because I probably spend twice as much time bugfixing and testing than "coding". (Both of which actually involve coding stuff, so I really don't like that distinction they make) This is stuff AI can be really good at, so brushing that part under the table distorts the picture. Having said that, I do agree with most of the myths they present.
- Yopolo 2mo ago
  Then yeah you might not be a good developer. LLMs are also quite good in writing unit tests and understanding bugs a lot faster than I do, now. Just a few month back i looked at some yaml stuff for like 20 minutes, played around with it, looked at formatting etc. then i asked the LLM, it immediadly told me what was wrong. I was just blind to that particular wrong char. Logic bugs? Yeah it can find them too.
lovecg 2mo ago
> studies at Microsoft and elsewhere showing it’s closer to 14 percent This is a depressing stat. The real productivity gains come from leaving soul sucking big tech companies where nothing gets done with any sort of urgency.
- afdbcreid 2mo ago
  In my open source work I believe this is the same. I don't have numbers, but I'm sure the vast majority of my time isn't spent writing code. Of course, it depends on how you define "writing code".
- hahahaa 2mo ago
  It is not urgency. Large production systems mean you are doing mostly unsexy operational planning. If I had a dollar each time I hear the word "data migration" I reckon I could do well.
armitron 2mo ago
This reads like a critique of 2023 tooling published in 2026. Their Amdahl-style arithmetic (speed up a 14% slice, cap your gains at 14%) holds only if "AI" means autocomplete. Current frontier models do far more than that: research, code comprehension, review, test authoring, debugging, exploratory prototyping, ideation. That's most of the rest of the working day or "86%". The only point that still holds is that organizational policies and procedures that automate AI use and lower the barrier to entry are more efficient than leaving it up to each individual. Every other point they make is either stale or was never true to begin with.
langs 2mo ago
> Myth 2: Writing Code Is the Bottleneck Writing code is indeed the bottleneck for same resource constrained companies. Rapid code development creates more opportunities for trial and error, providing companies with more information for decision making, that previously might have been addressed by meetings. Of course, this might bring other problems, but it might not right to generally speaking that writing code is not a bottleneck.
- davidpapermill 2mo ago
  I’m very suspicious of this objection, because when Claude first landed the same people now saying “code is not the bottleneck” were saying “the generated code doesn’t work.” Smacks of moving goalposts. The only solid objection to “AI is going replace developers” is “AI is an accelerant.” It helps developers move faster. I haven’t seen anywhere it has fully replaced developers. Whether this leads to a large number of job losses depends on whether you think we can increase software output by the same factor as the acceleration and still be profitable. I think we can, latent software demand is extremely high. I also think we’re nearing the limit of capability with current models. Situation could change if more advanced models emerge, but some of the more foreseeable advances probably have compute requirements beyond today’s hardware.
LAC-Tech 2mo ago
All very sensible points which I think all senior programmers who have used AI would largely to agree with. For those more junior - keep in mind that a lot of the maximalist rhetoric are from people either selling models, or the cottage industry of people selling you courses or tools to help you use the models. Try and keep in mind software is not a mature industry, it's an immature one, and it's prone to hype and fads.
zkmon 2mo ago
11-18% of time spent in coding is still very high number I think. For a large org with lots of process and risk aversion, this number could be as low as 5%. Even for 14%, the 10x improvement could mean 86+(14/10) => 87.4/100 => 12.6% overall time saved.
- hahahaa 2mo ago
  And time in coding is like time on highways for taxi drivers. A fairly useless metric.
lz400 2mo ago
Like many others in the comments, I feel there are a lot of assumptions in this piece. Before, coding is only 14% therefore, small slice. I think that's a very superficial assumption. That was because coding was expensive and we needed to be sure we didn't code the wrong thing. If code is as cheap as it is now, we will optimize differently, we will structure around it. Instead of so many meetings we will code 5 different versions of the same thing and choose, etc.
- champagnepapi 2mo ago
  So you're suggesting that coding will take more of the PRD phase?
  - lz400 2mo ago
    Basically yes, there will be more coding in that phase, more prototyping, the PRD phases will be shorter too, there will be more pressure to deliver quickly and the PRDs will be under more pressure to move more quickly. This is what I'm already seeing to be honest.
- AdieuToLogic 2mo ago
  > That was because coding was expensive and we needed to be sure we didn't code the wrong thing. Coding has never been expensive as it is nothing more than a reification of a solution to a problem as it is understood at that time. It is the underlying understanding of the problem which has always been expensive and remains so.
  - lz400 2mo ago
    Coding was expensive in the sense that once you decided what to do, it took a few engineers months / years to do moderately complex projects. That's not true anymore. Therefore the risk of "coding the wrong thing" is less.
    - gmueckl 2mo ago
      Is it? The temptation to start without a thorough design is now much stronger because the implementation osnperceived to be cheap and easy to replace. But if you start building the wrong thing fast, you still get the right thing later than when you had checked properly at the start.
dasil003 2mo ago
A lot of this rings true, but I think it's still too narrow. Sure, coding does not equal productivity, that is well debunked already. But I would argue that productivity is a product of engineering delivery + product decision making. Now where is the line between product and engineering? It varies by company, team and individual, but I don't think productivity can be measured for those functions independently, and in fact I see gains from AI on both the coding AND the product management side. Basically as a senior tech lead in a large company engineering org, I don't have the bandwidth to individually validate every assertion from engineers on other teams OR from every product manager that comes with a half-baked ask. In the past I would be limited by the influence I could get through human relationships to strong SMEs with good judgment, and those folks always thin out as a company grows and calcifies. The number of creative and innovative thinkers dwindles, and the number of people protecting their turf and doing the minimum not to get fired increases. As a result many good ideas can get blocked by random gatekeeprs with poor imagination, poor expertise or both. However with AI I can follow up on gut instincts and fact check a lot more things, and ask incisive questions that can cut through a lot of organizational bullshit. That's where I think most of the AI gains are today. Of course once AI plateaus and normalizes I think it will be baked into the org structures of tomorrow. But for now it offers real competitive advantage to those with the expertise to ask the right questions.
outoftheweed 2mo ago
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01100011 2mo ago
I'm getting tired of these articles telling me what AI will or won't do to my career when every day I see something different first hand. I'm about to stop arguing with people. If you think it's all BS then fine. Good luck.
baobeta2907 2mo ago
This is actually true at my company. They expect employees to be 10× more productive now that we have AI.
- jdlshore 2mo ago
  I’ve had people tell me, with a completely straight face, that they expected 10-100x productivity improvements. This is at the executive and VC level. The mania is extreme.
  - miraculixx 2mo ago
    So then they should get 10-100x more revenue, now that AI does all the marketing and selling.
  - Yopolo 2mo ago
    I for sure do plenty of things with AI a lot faster. Instead of searching some linux issue, i will prompt claude to generate a small analyser script for checking wha tlinux i have, i will tell it what hardware i have and it fixed my issue in like 5 minutes? That would have been a lot longer before.
  - aryehof 2mo ago
    > … with a completely straight face, that they expected 10-100x productivity improvements. A great alternative future to look forward to - 1 employee expected to do the work of 10-100. Those others fired to save money.
- camdenreslink 2mo ago
  You can be 10x more productive if you don’t verify anything the LLM generates and just YOLO it into your codebase. I wouldn’t recommend it.
laichzeit0 2mo ago
I don’t trust point estimates like 14%. It’s like calculating an average salary and saying it’s $120k. Completely meaningless. What does the actual distribution look like that this was pulled from? No standard deviation. Is it even symmetric? What’s the 10th and 90th percentiles? Just giving a statistic on its own tells me nothing.
deleted 2mo ago
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mellosouls 2mo ago
even an AI assist that makes coding twice as fast would, in theory, improve developers’ overall productivity by less than 15 percent. The other 85 percent of their time remains untouched I stopped reading after this. AI has massively impacted most aspects of my non-coding work including the mentioned planning, understanding legacy code bases, setting up environments, etc etc. Either this article is written by people with skill issues or - given the platform - its a biased and protectionist take that will fall quickly under the march of reality.
- JackSlateur 2mo ago
  Have you considered the theory that, perhaps, you are the one with skill issue ?
cyliu 2mo ago
Some experience from my work: - In biz development, a dev usually spends 30-40% time on coding, and more time on requirement discussion, integration testing (especially when the tests involves mobilephone or car) - coding time can be reduced to 30%, which means reduce 20%-30% time of the full pipeline - meanwhile, every phase and role is using LLM now, for example, product manager can produce longer requirement doc easily (we can use LLM to read it anyway:) Meeting sometimes is more than before, because more document output leads to more reading and discussion. - I hope to find new ways to express biz requirements, in a more efficient and automatic manner. - Shorten the requirement-dev-test-deploy loop is very important. OUTPUT is not OUTCOME. It is equal when we can see the final result, instead of intermediate metric. - Agentic infra is extremely useful, or every one will find a way to access the database, report and ops system, in some weird fragile method.
fenestella 2mo ago
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bwhiting2356 2mo ago
> A June 2025 study of Microsoft developers A year ago feels like forever
- davidpapermill 2mo ago
  Not so much due to length of time, but because of the Opus shockwave than fell within that period.
1saadcodes 2mo ago
I think the paper would have been stronger if it acknowledged how quickly the underlying evidence is becoming outdated. AI-assisted development in 2026 isn't just better models. The way many devs including myself work has changed and matured quite a bit as compared to last year
- tkzed49 2mo ago
  how so?
  - sevenzero 2mo ago
    Many devs now work in YOLO mode letting LLMs automate their tasks.
  - cyptus 2mo ago
    I think the tooling around the models themself has improved _a lot_ - they are really good at giving the models the correct context, even in big code bases
  - Yopolo 2mo ago
    We switched from looking at an UI (claude webui) and waiting for code generation to using claude exclusivlie on the cli and claude doing a lot more stuff in the background with smaller prompts. For me it changes in a way that i would like to have a 24/7 workspace vm setup outside of my work laptop for keeping it running if it wants and looking at it remotely if i want. The workspace thing would also allow it to have more permissions like downloading, configuring and using headless chrome instead of highjacking my chrome session.
levmiseri 2mo ago
> f developers spend only about 15 percent of their time typing in the editor I think this is missing an important detail. Lots of time was spent on non-coding stuff, because coding used to be more committal and hence expensive. With how quickly one can code up a quick prototype or even production-ready code these days, the code becomes the communication tool as well.
deleted 2mo ago
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mumin00 2mo ago
one still has to think. Also about this ai automating stuff and humans playing around. I believe there is a time for this and time for that
willtemperley 2mo ago
With all the myths and hyperbolae circulating regarding AI, I'd love to know what it's like at large software companies adjusting to this brave new world. It's easy for a small team to adjust workflows and roles, but I just imagine the office politics must be a waking nightmare in big organisations right now.
- user43928 2mo ago
  As an individual contributor I do not have insights into office politics. While we have >10k developers, it is not a software company. Top leadership and/or investors believe in the benefits of AI. Thus, skeptics stay silent. Who wants to loudly contradict their bosses' boss? In practice, I do not see a big shift yet in workflows that would require a lot of politics. We just have the agent implement the code, and then it still goes through the usual code review and QA processes. Only now with more effective models and harnesses do many developers realize how good these tools are at investigating bugs, etc. Before the price-decreased GPT 5.6 Luna we barely had access to enough cheap AI to last for a month of work.
- Yopolo 2mo ago
  In my company GitHub CoPilot was rolled out on a global scale last year. LLMs from Anthropic and co we get through a central tool which buys api tokens from Azure and AWS. Its surprisingly fast, probably thefastest i have seen technology getting rolled out. Im more worried about the small/middle sized companies which are software companies but don't get that they are. You know the companies 100% depending on IT but not having the right or good or enough people who often in interviews struggle with basics like code review.
bjourne 2mo ago
> Despite this decade-old research, many organizations still rely on lines of code as a measure of developer productivity. No, they don't! It's easy to dispel myths when the myths are built on straw men. Dumb article.
giorgiogamba 2mo ago
I mostly agree with the part where it is stated that AI is a tool which received massive investments without knowing how to maximize its utility. I think that we will pay for it in the near future.
agronomov 2mo ago
ChatGPT, summarize
GunjanKarun 2mo ago
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welcomezhangjun 2mo ago
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MstTK 2mo ago
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mfru 2mo ago
I've found that using LLMs for significant amounts of code generation completely drain the result from any dopamine I would get doing it myself. Have others noticed this as well? This is going so far as to me losing interest in side projects because I have "lost touch" with the code base.
- fhd2 2mo ago
  With GenAI, we can now produce something without caring about it - or while caring about it very little. And the parts we don't care about aren't necessarily worse, they are just... arbitrary. Could be good, could be bad, no one knows, because no one really cares. I find that if I care about something a lot, it's a pretty similar time investment than pre LLMs. And it makes me feel invested and proud in the result, motivated to show it and improve it. If I care about something very little, in the past I just wouldn't have done it at all. Now I might, but I feel that same disconnect you mentioned. I think being strategic in what we do and do not care about is likely the key skill we'll have to build to actually make the best of the tech.
- delis-thumbs-7e 2mo ago
  Yep. ADHD very strong in this one, so LLM code generation takes pretty much all joy out of coding. It’s like watching a computers play chess. Yeah, no thanks.
  - theshrike79 2mo ago
    My ADHD gets dopamine from getting something working, not from the tedious process of getting there. So YMMV.
lentil_soup 2mo ago
>a “good” workday, engineers spent 18 percent of their time “coding” (not including bug fixing, testing, etc.) that's such a weird metric, why exclude bug fixing and testing? depending on the phase of the project I might spend 100% of my coding time bug fixing
krembo 2mo ago
It's kind of weird how we blame agents for hallucinations as if humans don't fall for that as well, while agents can run the build-fail-fix-repeat in much faster cycles than coders.
imilev 2mo ago
I hope that some of the executives out there will read the list. I know they won't spend the time to read the full blog, but at least the headers should be enough
runtime_lens 2mo ago
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watchping 2mo ago
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ascotan 2mo ago
>>>Recent research shows that developers—especially women and older engineers—face a “competence penalty” when using AI and why did this study (performed in China I might add) find that women and “mature age” (which is not defined in the study) have less usage of AI tools? >>>? We suggest a new barrier: using technology to assist task completion signals a lack of competence to perform the task independently. So basically the study suggests that older engineers and women are reluctant (and especially women) to use AI tooling because they feel they are being judged more on non-technical competencies. This study may have a strong cultural influence but I would say that one thing they noted I’ve also seen. 41% of engineers in the study had used AI 12 months after the initial rollout. This aligns with my observations. Some people are struggling figuring out how to adopt in their day to day while others are full in.
_pdp_ 2mo ago
If you can spin up a new software project with little to no effort, the most important part of the job becomes making the right decisions and this is where we will be spending 99.9% of your time.
fullstackwife 2mo ago
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dr0idattack 2mo ago
I look askance at an article that uses a GenAI survey from 2024. Other references could be good. But the dev agent milestone was Nov/Dev 2025, and CoPilot and agents were pretty sketch before then (but helpful at times.)
HarHarVeryFunny 2mo ago
> A study of more than 450 engineers at Microsoft in 2025 showed developers spend only 14 percent of their time writing code This feels about right as an average across project cycles and different types of companies, and is the same type of number I've suggested here before. The obvious conclusion is that even if AI reduced coding time to zero, then it would only reduce software development time by that 14%. Of course AI may be used for other aspects of the job as well as coding, but on the flip side any serious use of AI requires a human in the loop to give work to the AI, steer the AI, assess the output, etc. It's interesting that this 14% figure is close to Uber's choice to limit AI spend to 10% of developers salary. I wonder where that Uber number came from? Another rather startling datapoint on the perceived value of AI comes from Microsoft who are also adopting budgeted AI usage, and are looking for "outcomes that move the needle". Their budget guidelines apparently refer to (current? targeted?) per-developer AI usage of "hundreds of dollars a month to a few thousand dollars in tokens". https://www.techradar.com/pro/tokenmaxxing-is-not-what-we-are-optimizing-for-microsoft-tells-engineer-to-calm-down-on-ai-usage https://www.techradar.com/pro/tokenmaxxing-is-not-what-we-ar...
altern8 2mo ago
I can't remember of any product in my lifetime that was more over hyped than AI. It's a huge piece of shit and if I wasn't forced to use it at work I would never use it. It writes dumb, throw-away code and adds thousands of dollars/developer in costs. All this crazy code that we're adding to our projects will come back to bite us in the future, there's no way it won't.
al_be_back 2mo ago
> Myth 3: Lines of Code Written by AI... how come lines of code (or expressions) by an engineer aren't a good way to measure progress (Gates point etc) but GenAI tokens must count and be paid for?
- dxdm 2mo ago
  That's a good point. They're not selling progress, they are claiming to enable progress by selling you (tokens in -> tokens out), making it your responsibility to connect the two. Filling that gap is part of your expertise that you can get paid for.
spiritrock 2mo ago
> AI Will Turn Individual Developers into 10x Developers Maybe not 10x, but there's definitely a significant boost in velocity of development and delivery. We used to be a team of 20+, now only 9, and we are delivering more than before. Besides that, we did some major refactors that were sitting in the backlog for months.
peteroettl 2mo ago
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felixlu2026 2mo ago
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291 points by tchalla 2mo ago

|--------|-------|------|------|-------|------| |Contract|Product|Design|Coding|Testing|Deploy| Writing Code Isn't the Bottleneck, until writing code is the bottleneck, until it's not again.

sublinear 2mo ago
You forgot to add "coordination" to that pipeline. That is easily far and away the biggest source of delays. That includes talking to vendors, meetings with every layer of stakeholder when just one person digs their heels, etc. That is truly the final frontier for "AI", and one that it will likely never cross. That would be when even the execs and upper management feel threatened by "AI". But, since they also delegate so much, you often see someone at the bottom of the totem pole in those meetings. This is why nobody is getting replaced by "AI". We really need to move this discussion away from the scifi stupidity already. There is no singularity or godlike AGI about to take over the world. I hate to use awful terms like "synergy" and "teamwork", but they do have a lot more substance and truth to them than any perceived threat from "AI".
pstuart 2mo ago
Getting a usable PRD is often the bottleneck.
- hahahaa 2mo ago
  The real bottleneck is Omega Star getting their shit together. And I ain't joking.
  - Exoristos 2mo ago
    Or SPS Commerce. Evidence is becoming unconvincing that they're even in business anymore.

osigurdson 2mo ago

It seems that this could have been expanded or contracted to any Fibonacci number of myths.

simonw 2mo ago

> We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent. Anyone else finding they're spending more time writing code (or at least driving agents to write code) now? 14% used to feel about right for me - I'd spend the rest of the time researching approaches and libraries, planning things out in issues, or sometimes just thinking really hard about problems I ran into. Now... I still do those things, but I'm doing many of them faster - and I'm often doing them while my coding agents are churning away on code. There's also this weird effect where the harder a problem is the more I can get done in parallel with it, because an agent might need to spend 20 minutes on it without my involvement.

enraged_camel 2mo ago
Yeah. I spend most of my day driving agents to write code, verifying the results, orchestrating work streams, and so on. The rest of the time, a Fable agent is organizing work in Linear/Jira and making sure coworkers are getting their stuff done in a way that won’t conflict.
geoduck14 2mo ago
I used it to write SQL and make dashboards. Back in the day, I would spend a lot of time doing that, then I changed roles. I dipped my toe in it recently and used AI exclusively. I would send a prompt, see the output, decide if that is what I wanted or not. I kept my brain in "what-if mode" and I let the LLM handle the technical specs.
- TheOtherHobbes 2mo ago
  'What-if' mode is a game changer. And underrated. The cost of prototyping has crashed. So you can A/B/C... various ideas, test them in the real world or by personal preference, to taste, and converge on designs that work for you. This used to very hard and expensive. Now it's so cheap it makes the idea -> test -> refine loop much tighter and faster.
  - geoduck14 2mo ago

TrustChain 2mo ago

The 14% coding time figure is one of those stats that sounds surprising until you actually track your own time. When I started building a coding agent with persistent state, I realized how some days are spent with minimal actual typing, most of it is design, reading code, debugging, problem solving, and context-switching. But I'd push back on one thing the article implies that AI is automatically a productivity win. It's not. Some days I've shipped two months of work in a few days with AI. Other days, like today, I've burned a whole day and gotten almost nothing done because the proper research was not done by me or multiple agents. The bottleneck for AI can be the human understanding of how to optimally use the tool. While the bottleneck for the human can be not maximizing multiple agents, or the input the user enters, then the retention of the output. If the user's input is lost, the output falters. If the user doesn't understand what the AI output is, there is going to be a problem eventually. The article touches on adoption barriers (Myth 7), but it doesn't really get into the ego piece. There's still a wave of experienced devs who either refuse to adopt AI, or use it quietly and don't share what they're doing. That slows the whole team's learning curve. At this point, I think it's pretty much understood that you should be using AI as a dev — not to replace your skills, but to accelerate them. That means still learning new languages, still writing code, still troubleshooting. The tools change, but the craft doesn't. I think the article is right that the real leverage is organizational, not individual. The teams that succeed with AI aren't the ones giving everyone a license — they're the ones rethinking how they review, test, and maintain code. What I'm still uncertain about is how to measure whether AI is actually making systems better, not just faster. Lines of code is clearly a bad metric, but I haven't seen a good alternative yet. What metrics are people actually using that feel meaningful?

imrozim 2mo ago
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kylecazar 2mo ago

I don't understand Myth 1 (Developers Spend Most of Their Time Writing Code). They quote a study in which developers report to spend 11-14% of their day coding. The rest is stuff like solution design and meetings. The insinuation is that AI can at most automate 14% of your day. The problem with this argument is that once you have code, some (not all) of the precursors to code go away.

unknownfuture 2mo ago
Okay. Show me the evidence that AI has an impact on productivity when doing design work. Or reducing meeting load. My own experience is that AI doesn't tighten the design cycle, and in fact might extend it by encouraging gold plating.
- simonw 2mo ago
  What kind of shape of evidence would you find convincing?
  - bluefirebrand 2mo ago
    People working fewer hours :)
    - kaashif 2mo ago
      Damn, looks like we have lower productivity than cavemen!
    - keeda 2mo ago
      Sir, this is Capitalism.
  - unknownfuture 2mo ago
    Self-reported or observational data capturing time spent for categories of task ala every other similar study in this space? This isn't exactly novel territory, here, Simon. Let's not pretend I'm asking for something strange, unprecedented, or unreasonable.

a_bonobo 2mo ago

>On my visits to the Bay Area, I would ask AI researchers or interns why they are doing their current research or projects, when in a year or three agentic LLMs could probably do them; This is such a weird point to make that doesn't become correct just because everyone makes it, all the time. Why clean the ocean if some magic future tech will clean them? Why save the world now if some benevolent AI is 'just around the corner' and will do it for us? And people have been making this point for years now, and it's not like my job got any easier. I just got more AI. https://www.poetryfoundation.org/poems/51294/waiting-for-the-barbarians https://www.poetryfoundation.org/poems/51294/waiting-for-the... And I say that as someone who uses Claude Code in complex environments almost hourly; I, as the human, still have to do the thinking as Claude still 'can't jump' [1] and I have seen no evidence that they (or similar AI, any time soon) will 'jump' like a human brain does. [1] https://www.tomzahavy.com/files/llms-cant-jump.pdf https://www.tomzahavy.com/files/llms-cant-jump.pdf

Patient0 2mo ago
Sorry where in the article does it make this point? I cannot find the text "On my visits to the Bay Area" anywhere in the original article.
- decimalenough 2mo ago
  It doesn't, GP was responding to the Gwern story at https://news.ycombinator.com/item?id=49174900 https://news.ycombinator.com/item?id=49174900 but posted in the wrong place.
esafak 2mo ago
Also, if you believe your well-paying job is eventually going to be automated you would be prudent to bank the money while you prepare for the future.
fhub 2mo ago
> I, as the human, still have to do the thinking as Claude still 'can't jump' I still have to do quite a bit of thinking but the amount of of thinking I do per task is trending down. I agree LLMs are not good at abduction but very few humans are either and very few jobs/tasks require it. I can't talk for researchers jobs though. But perhaps fewer researchers would be desired by these labs (not none).

mkozlows 2mo ago

I feel like all you need to know about how seriously to take this is that they cite that ancient early-2025 METR study, and describe it in the text as "recently one even found..."

katzgrau 2mo ago
Same thought - 80% through reading it occurred to me to check the citations. A few items from 2025 and most well before that. So much has changed since late 2025 one can’t really draw any conclusions from this. In fact, I’m guessing things will continue to move so fast that by the time one were to execute a survey of developers, many of the responses and findings are no longer relevant.
- joshuastuden 2mo ago
  Exactly. I saw them using things from 2025... AI sorta sucked then and didn't really "take off" until that Opus drop in December or whatever it was.
- greenhat76 2mo ago
  Your point really goes both ways, we really don't know anything about how LLM usage is affecting anything. No one knows, it's the wild wild west, which is whatever. But I think no one can really draw conclusions from what's happening in tech right now. Reminds me of COVID and how everyone was fighting over early trends during that time.
CompoundEyes 2mo ago
I felt the same and why didn’t the authors look over METR’s recent material? https://metr.org/blog/2026-05-11-ai-usage-survey/ https://metr.org/blog/2026-05-11-ai-usage-survey/
- Izkata 2mo ago
  The whole point of the 2025 one is that they found the self-reporting to be significantly inflated, which is why self-reported surveys like this one are hard to trust.

abratabia 2mo ago

[flagged]

physix 2mo ago

>a “good” workday, engineers spent 18 percent of their time “coding” (not including bug fixing, testing, etc.) I must be a crap developer, because I probably spend twice as much time bugfixing and testing than "coding". (Both of which actually involve coding stuff, so I really don't like that distinction they make) This is stuff AI can be really good at, so brushing that part under the table distorts the picture. Having said that, I do agree with most of the myths they present.

Yopolo 2mo ago
Then yeah you might not be a good developer. LLMs are also quite good in writing unit tests and understanding bugs a lot faster than I do, now. Just a few month back i looked at some yaml stuff for like 20 minutes, played around with it, looked at formatting etc. then i asked the LLM, it immediadly told me what was wrong. I was just blind to that particular wrong char. Logic bugs? Yeah it can find them too.

lovecg 2mo ago

> studies at Microsoft and elsewhere showing it’s closer to 14 percent This is a depressing stat. The real productivity gains come from leaving soul sucking big tech companies where nothing gets done with any sort of urgency.

afdbcreid 2mo ago
In my open source work I believe this is the same. I don't have numbers, but I'm sure the vast majority of my time isn't spent writing code. Of course, it depends on how you define "writing code".
hahahaa 2mo ago
It is not urgency. Large production systems mean you are doing mostly unsexy operational planning. If I had a dollar each time I hear the word "data migration" I reckon I could do well.

armitron 2mo ago

This reads like a critique of 2023 tooling published in 2026. Their Amdahl-style arithmetic (speed up a 14% slice, cap your gains at 14%) holds only if "AI" means autocomplete. Current frontier models do far more than that: research, code comprehension, review, test authoring, debugging, exploratory prototyping, ideation. That's most of the rest of the working day or "86%". The only point that still holds is that organizational policies and procedures that automate AI use and lower the barrier to entry are more efficient than leaving it up to each individual. Every other point they make is either stale or was never true to begin with.

langs 2mo ago

> Myth 2: Writing Code Is the Bottleneck Writing code is indeed the bottleneck for same resource constrained companies. Rapid code development creates more opportunities for trial and error, providing companies with more information for decision making, that previously might have been addressed by meetings. Of course, this might bring other problems, but it might not right to generally speaking that writing code is not a bottleneck.

davidpapermill 2mo ago
I’m very suspicious of this objection, because when Claude first landed the same people now saying “code is not the bottleneck” were saying “the generated code doesn’t work.” Smacks of moving goalposts. The only solid objection to “AI is going replace developers” is “AI is an accelerant.” It helps developers move faster. I haven’t seen anywhere it has fully replaced developers. Whether this leads to a large number of job losses depends on whether you think we can increase software output by the same factor as the acceleration and still be profitable. I think we can, latent software demand is extremely high. I also think we’re nearing the limit of capability with current models. Situation could change if more advanced models emerge, but some of the more foreseeable advances probably have compute requirements beyond today’s hardware.

LAC-Tech 2mo ago

All very sensible points which I think all senior programmers who have used AI would largely to agree with. For those more junior - keep in mind that a lot of the maximalist rhetoric are from people either selling models, or the cottage industry of people selling you courses or tools to help you use the models. Try and keep in mind software is not a mature industry, it's an immature one, and it's prone to hype and fads.

zkmon 2mo ago

11-18% of time spent in coding is still very high number I think. For a large org with lots of process and risk aversion, this number could be as low as 5%. Even for 14%, the 10x improvement could mean 86+(14/10) => 87.4/100 => 12.6% overall time saved.

hahahaa 2mo ago
And time in coding is like time on highways for taxi drivers. A fairly useless metric.

lz400 2mo ago

Like many others in the comments, I feel there are a lot of assumptions in this piece. Before, coding is only 14% therefore, small slice. I think that's a very superficial assumption. That was because coding was expensive and we needed to be sure we didn't code the wrong thing. If code is as cheap as it is now, we will optimize differently, we will structure around it. Instead of so many meetings we will code 5 different versions of the same thing and choose, etc.

champagnepapi 2mo ago
So you're suggesting that coding will take more of the PRD phase?
- lz400 2mo ago
  Basically yes, there will be more coding in that phase, more prototyping, the PRD phases will be shorter too, there will be more pressure to deliver quickly and the PRDs will be under more pressure to move more quickly. This is what I'm already seeing to be honest.
AdieuToLogic 2mo ago
> That was because coding was expensive and we needed to be sure we didn't code the wrong thing. Coding has never been expensive as it is nothing more than a reification of a solution to a problem as it is understood at that time. It is the underlying understanding of the problem which has always been expensive and remains so.
- lz400 2mo ago
  Coding was expensive in the sense that once you decided what to do, it took a few engineers months / years to do moderately complex projects. That's not true anymore. Therefore the risk of "coding the wrong thing" is less.
  - gmueckl 2mo ago
    Is it? The temptation to start without a thorough design is now much stronger because the implementation osnperceived to be cheap and easy to replace. But if you start building the wrong thing fast, you still get the right thing later than when you had checked properly at the start.

dasil003 2mo ago

A lot of this rings true, but I think it's still too narrow. Sure, coding does not equal productivity, that is well debunked already. But I would argue that productivity is a product of engineering delivery + product decision making. Now where is the line between product and engineering? It varies by company, team and individual, but I don't think productivity can be measured for those functions independently, and in fact I see gains from AI on both the coding AND the product management side. Basically as a senior tech lead in a large company engineering org, I don't have the bandwidth to individually validate every assertion from engineers on other teams OR from every product manager that comes with a half-baked ask. In the past I would be limited by the influence I could get through human relationships to strong SMEs with good judgment, and those folks always thin out as a company grows and calcifies. The number of creative and innovative thinkers dwindles, and the number of people protecting their turf and doing the minimum not to get fired increases. As a result many good ideas can get blocked by random gatekeeprs with poor imagination, poor expertise or both. However with AI I can follow up on gut instincts and fact check a lot more things, and ask incisive questions that can cut through a lot of organizational bullshit. That's where I think most of the AI gains are today. Of course once AI plateaus and normalizes I think it will be baked into the org structures of tomorrow. But for now it offers real competitive advantage to those with the expertise to ask the right questions.

outoftheweed 2mo ago

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01100011 2mo ago

I'm getting tired of these articles telling me what AI will or won't do to my career when every day I see something different first hand. I'm about to stop arguing with people. If you think it's all BS then fine. Good luck.

baobeta2907 2mo ago

This is actually true at my company. They expect employees to be 10× more productive now that we have AI.

jdlshore 2mo ago
I’ve had people tell me, with a completely straight face, that they expected 10-100x productivity improvements. This is at the executive and VC level. The mania is extreme.
- miraculixx 2mo ago
  So then they should get 10-100x more revenue, now that AI does all the marketing and selling.
- Yopolo 2mo ago
  I for sure do plenty of things with AI a lot faster. Instead of searching some linux issue, i will prompt claude to generate a small analyser script for checking wha tlinux i have, i will tell it what hardware i have and it fixed my issue in like 5 minutes? That would have been a lot longer before.
- aryehof 2mo ago
  > … with a completely straight face, that they expected 10-100x productivity improvements. A great alternative future to look forward to - 1 employee expected to do the work of 10-100. Those others fired to save money.
camdenreslink 2mo ago
You can be 10x more productive if you don’t verify anything the LLM generates and just YOLO it into your codebase. I wouldn’t recommend it.

laichzeit0 2mo ago

I don’t trust point estimates like 14%. It’s like calculating an average salary and saying it’s $120k. Completely meaningless. What does the actual distribution look like that this was pulled from? No standard deviation. Is it even symmetric? What’s the 10th and 90th percentiles? Just giving a statistic on its own tells me nothing.

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mellosouls 2mo ago

even an AI assist that makes coding twice as fast would, in theory, improve developers’ overall productivity by less than 15 percent. The other 85 percent of their time remains untouched I stopped reading after this. AI has massively impacted most aspects of my non-coding work including the mentioned planning, understanding legacy code bases, setting up environments, etc etc. Either this article is written by people with skill issues or - given the platform - its a biased and protectionist take that will fall quickly under the march of reality.

JackSlateur 2mo ago
Have you considered the theory that, perhaps, you are the one with skill issue ?

cyliu 2mo ago

Some experience from my work: - In biz development, a dev usually spends 30-40% time on coding, and more time on requirement discussion, integration testing (especially when the tests involves mobilephone or car) - coding time can be reduced to 30%, which means reduce 20%-30% time of the full pipeline - meanwhile, every phase and role is using LLM now, for example, product manager can produce longer requirement doc easily (we can use LLM to read it anyway:) Meeting sometimes is more than before, because more document output leads to more reading and discussion. - I hope to find new ways to express biz requirements, in a more efficient and automatic manner. - Shorten the requirement-dev-test-deploy loop is very important. OUTPUT is not OUTCOME. It is equal when we can see the final result, instead of intermediate metric. - Agentic infra is extremely useful, or every one will find a way to access the database, report and ops system, in some weird fragile method.

fenestella 2mo ago

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bwhiting2356 2mo ago

> A June 2025 study of Microsoft developers A year ago feels like forever

davidpapermill 2mo ago
Not so much due to length of time, but because of the Opus shockwave than fell within that period.

1saadcodes 2mo ago

I think the paper would have been stronger if it acknowledged how quickly the underlying evidence is becoming outdated. AI-assisted development in 2026 isn't just better models. The way many devs including myself work has changed and matured quite a bit as compared to last year

tkzed49 2mo ago
how so?
- sevenzero 2mo ago
  Many devs now work in YOLO mode letting LLMs automate their tasks.
- cyptus 2mo ago
  I think the tooling around the models themself has improved _a lot_ - they are really good at giving the models the correct context, even in big code bases
- Yopolo 2mo ago
  We switched from looking at an UI (claude webui) and waiting for code generation to using claude exclusivlie on the cli and claude doing a lot more stuff in the background with smaller prompts. For me it changes in a way that i would like to have a 24/7 workspace vm setup outside of my work laptop for keeping it running if it wants and looking at it remotely if i want. The workspace thing would also allow it to have more permissions like downloading, configuring and using headless chrome instead of highjacking my chrome session.

levmiseri 2mo ago

> f developers spend only about 15 percent of their time typing in the editor I think this is missing an important detail. Lots of time was spent on non-coding stuff, because coding used to be more committal and hence expensive. With how quickly one can code up a quick prototype or even production-ready code these days, the code becomes the communication tool as well.

deleted 2mo ago

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mumin00 2mo ago

one still has to think. Also about this ai automating stuff and humans playing around. I believe there is a time for this and time for that

willtemperley 2mo ago

With all the myths and hyperbolae circulating regarding AI, I'd love to know what it's like at large software companies adjusting to this brave new world. It's easy for a small team to adjust workflows and roles, but I just imagine the office politics must be a waking nightmare in big organisations right now.

user43928 2mo ago
As an individual contributor I do not have insights into office politics. While we have >10k developers, it is not a software company. Top leadership and/or investors believe in the benefits of AI. Thus, skeptics stay silent. Who wants to loudly contradict their bosses' boss? In practice, I do not see a big shift yet in workflows that would require a lot of politics. We just have the agent implement the code, and then it still goes through the usual code review and QA processes. Only now with more effective models and harnesses do many developers realize how good these tools are at investigating bugs, etc. Before the price-decreased GPT 5.6 Luna we barely had access to enough cheap AI to last for a month of work.
Yopolo 2mo ago
In my company GitHub CoPilot was rolled out on a global scale last year. LLMs from Anthropic and co we get through a central tool which buys api tokens from Azure and AWS. Its surprisingly fast, probably thefastest i have seen technology getting rolled out. Im more worried about the small/middle sized companies which are software companies but don't get that they are. You know the companies 100% depending on IT but not having the right or good or enough people who often in interviews struggle with basics like code review.

bjourne 2mo ago

> Despite this decade-old research, many organizations still rely on lines of code as a measure of developer productivity. No, they don't! It's easy to dispel myths when the myths are built on straw men. Dumb article.

giorgiogamba 2mo ago

I mostly agree with the part where it is stated that AI is a tool which received massive investments without knowing how to maximize its utility. I think that we will pay for it in the near future.

agronomov 2mo ago

ChatGPT, summarize

GunjanKarun 2mo ago

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welcomezhangjun 2mo ago

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MstTK 2mo ago

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mfru 2mo ago

I've found that using LLMs for significant amounts of code generation completely drain the result from any dopamine I would get doing it myself. Have others noticed this as well? This is going so far as to me losing interest in side projects because I have "lost touch" with the code base.

fhd2 2mo ago
With GenAI, we can now produce something without caring about it - or while caring about it very little. And the parts we don't care about aren't necessarily worse, they are just... arbitrary. Could be good, could be bad, no one knows, because no one really cares. I find that if I care about something a lot, it's a pretty similar time investment than pre LLMs. And it makes me feel invested and proud in the result, motivated to show it and improve it. If I care about something very little, in the past I just wouldn't have done it at all. Now I might, but I feel that same disconnect you mentioned. I think being strategic in what we do and do not care about is likely the key skill we'll have to build to actually make the best of the tech.
delis-thumbs-7e 2mo ago
Yep. ADHD very strong in this one, so LLM code generation takes pretty much all joy out of coding. It’s like watching a computers play chess. Yeah, no thanks.
- theshrike79 2mo ago
  My ADHD gets dopamine from getting something working, not from the tedious process of getting there. So YMMV.

lentil_soup 2mo ago

>a “good” workday, engineers spent 18 percent of their time “coding” (not including bug fixing, testing, etc.) that's such a weird metric, why exclude bug fixing and testing? depending on the phase of the project I might spend 100% of my coding time bug fixing

krembo 2mo ago

It's kind of weird how we blame agents for hallucinations as if humans don't fall for that as well, while agents can run the build-fail-fix-repeat in much faster cycles than coders.

imilev 2mo ago

I hope that some of the executives out there will read the list. I know they won't spend the time to read the full blog, but at least the headers should be enough

runtime_lens 2mo ago

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watchping 2mo ago

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ascotan 2mo ago

>>>Recent research shows that developers—especially women and older engineers—face a “competence penalty” when using AI and why did this study (performed in China I might add) find that women and “mature age” (which is not defined in the study) have less usage of AI tools? >>>? We suggest a new barrier: using technology to assist task completion signals a lack of competence to perform the task independently. So basically the study suggests that older engineers and women are reluctant (and especially women) to use AI tooling because they feel they are being judged more on non-technical competencies. This study may have a strong cultural influence but I would say that one thing they noted I’ve also seen. 41% of engineers in the study had used AI 12 months after the initial rollout. This aligns with my observations. Some people are struggling figuring out how to adopt in their day to day while others are full in.

_pdp_ 2mo ago

If you can spin up a new software project with little to no effort, the most important part of the job becomes making the right decisions and this is where we will be spending 99.9% of your time.

fullstackwife 2mo ago

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dr0idattack 2mo ago

I look askance at an article that uses a GenAI survey from 2024. Other references could be good. But the dev agent milestone was Nov/Dev 2025, and CoPilot and agents were pretty sketch before then (but helpful at times.)

HarHarVeryFunny 2mo ago

> A study of more than 450 engineers at Microsoft in 2025 showed developers spend only 14 percent of their time writing code This feels about right as an average across project cycles and different types of companies, and is the same type of number I've suggested here before. The obvious conclusion is that even if AI reduced coding time to zero, then it would only reduce software development time by that 14%. Of course AI may be used for other aspects of the job as well as coding, but on the flip side any serious use of AI requires a human in the loop to give work to the AI, steer the AI, assess the output, etc. It's interesting that this 14% figure is close to Uber's choice to limit AI spend to 10% of developers salary. I wonder where that Uber number came from? Another rather startling datapoint on the perceived value of AI comes from Microsoft who are also adopting budgeted AI usage, and are looking for "outcomes that move the needle". Their budget guidelines apparently refer to (current? targeted?) per-developer AI usage of "hundreds of dollars a month to a few thousand dollars in tokens". https://www.techradar.com/pro/tokenmaxxing-is-not-what-we-are-optimizing-for-microsoft-tells-engineer-to-calm-down-on-ai-usage https://www.techradar.com/pro/tokenmaxxing-is-not-what-we-ar...

altern8 2mo ago

I can't remember of any product in my lifetime that was more over hyped than AI. It's a huge piece of shit and if I wasn't forced to use it at work I would never use it. It writes dumb, throw-away code and adds thousands of dollars/developer in costs. All this crazy code that we're adding to our projects will come back to bite us in the future, there's no way it won't.

al_be_back 2mo ago

> Myth 3: Lines of Code Written by AI... how come lines of code (or expressions) by an engineer aren't a good way to measure progress (Gates point etc) but GenAI tokens must count and be paid for?

dxdm 2mo ago
That's a good point. They're not selling progress, they are claiming to enable progress by selling you (tokens in -> tokens out), making it your responsibility to connect the two. Filling that gap is part of your expertise that you can get paid for.

spiritrock 2mo ago

> AI Will Turn Individual Developers into 10x Developers Maybe not 10x, but there's definitely a significant boost in velocity of development and delivery. We used to be a team of 20+, now only 9, and we are delivering more than before. Besides that, we did some major refactors that were sitting in the backlog for months.

peteroettl 2mo ago

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felixlu2026 2mo ago

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