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- Hacker News
- You still have to know what you’re doing. That came from years of doing it by hand. Where is that necessary experience going to come from for the current and future generations of juniors?by watso
- Shipping. Breaking stuff. Fixing it. And discovering, repeatedly, that the tool sounded much more confident than it had any right to.
Like always. This is why the average carpenter you hire in 2026 still won’t do a perfect job, despite carpentry having existed for thousands of years.
by peheje - In 10 years llms will handle it all from start to finish.by ipaddr
- I'm pretty sure that just a year or two ago, software engineers were saying that coding was only a small part of the job; the rest is meetings, dealing with requirements, design, testing, maintenance. So, how can we expect a 10x boost in a productivity from improving a small part of the job - especially now if we have to clean up any mistakes the LLM makes?by spaqin
- Now you actually have very long meetings with AI, if you consider all these long design / explorer / post-poc conversations "meetings".by 361994752
- Yeah that's a good point, in order to see a 10x gain it would require at minimum coding be 90% of your day [7 hours, 20min) (or somehow for AI to replace meetings)by zug_zug
- for me, almost all of the work is specs
I am no longer:
- reading docs for hours and hours
- typing (barely at all)
- writing code
- manually doing tight debug loops
- using an IDE
to do this I had to give up reading or even controlling the code and focusing on behavior/design-level control (not superficial, still dictating overall technical architecture)
i have agents doing everything from writing the code, verifying the code, hardening, increasing test coverage, analyzing behavior, algorithmic perf improvements, managing/deploying to cloud resources, etc... (pretty much everything)
and I am accomplishing projects that would take months or years in a fraction of the time.
that's way more than 10x.
somehow, this is harder and more cognitively demanding than writing code
by bthornbury - How much does it cost in GPU rental?
- > to do this I had to give up reading or even controlling the code and focusing on behavior/design-level control (not superficial, still dictating overall technical architecture)
how do you verify the behavior? are you still writing or at least reading tests or just doing manual testing?
by twister2920 - I'm not sure about the x, but the first thing that arises from that is, I feel like in my case it's way higher than 2.
The 2nd thing is, how do I measure that.
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In my case, the details of my work (Kinda DevOps, kinda Senior Dev) makes it that having an LLM to do the heavy lifting allows me to do things not only faster, but better, and across domains I do not hold expertise on.
An example of the effect of LLMs in my daily work is that I'm in the middle of a PHP upgrade for a rather large legacy application, and the "heavy lifting" is really out of the scale, letting me concentrate on what really matters, while at the same time if I do keep "the harness" tight I'm certain the results are the correct ones. Also correcting course is just as cheap.
Not having to worry on the tooling on exchange has the incredible desirable result of my velocity being incomparable to what it was before.
Then we have the side effect of how easy to do transfer knowledge: Rather than telling the QA guy how to do the work specific for this task, I defined a set of files (.md documents, skills, an off-the-shelf customised MCP server) that assist QA into doing the work in a way that helps me do my job better and faster.
There's also a clear possibility that what I'm doing will expand to the rest of the team I am in, completely altering the way in which we approach development.
If we take 'x' as 'mileage', yours might vary. Mine has, and I'm baffled at the positive net results I AM getting.
Also, this what I do (coding?) is extremely fun again.
Being able to work close to the speed of thought is the best high.
by ericol - > allows me to do things not only faster, but better, and across domains I do not hold expertise on.
How would you know it's better when you have no expertise?
by soperj - I recently removed about 50% of code in a feature submitted by a colleague, because it's a pile of over-engineered mess that either never gets used or caused trouble for us. We probably would not have added the code in the first place if we actually discussed the design. With the code removed, the feature is now much simpler and more maintenable.
And that's the second time this happened over the past few months.
by fg137 - One time before LLMs we outsourced this project. It was something to sign file headers, written in ruby by an overseas company. It was something like 4500 lines long, and I wound up reducing it to something like 550 lines.
My story, like yours, has nothing to do with the topic at hand.
It happened many times to me, as well. Humans write terrible code.
You didn't even mention if the code you're talking about was generated or not.
by sejje - There's someone I know that jumped head-first into AI... they have embraced everything agentic. While setting up mail on their new iphone they encountered a problem. They had claude go through and do a bunch of tests against the server... allegedly. It didn't do any actual testing, though it did generate a long-winded report of what it pretended to try, fully blaming the server the whole time.
Actual problem: he typed in the wrong password
by bigbuppo - Not sure what your point is, could you clarify? Are you saying that your friend is stupid? Or do you mean Claude is stupid? Both?
- I'm probably in the 5x-10x range, but we are a very small team, and we've been accumulating a backlog of ideas over the years. I drive the architecture, and have almost complete autonomy over the work I do. I think someone in my shoes will see a greater result than someone trying to do the same thing in large team, with all the usual process and ceremony, only wanting to go faster.by bdcravens
- Where as I'm stuck in a big team with a legacy codebase and lots of business rules, performing small incremental changes. So I spend my days banging the Esc key and shouting "Shut the f**k up!".
Luckily I work remote. I'd turn it off again, but my usage is monitored and I don't want to look like a Luddite.
So may be .75x to .8x range.
by RegW - The way I see it you should calibrate the way you work with LLMs based on how confident you are on that specific area, and if it's your responsibility to own/understand it. Here's how it feels for me:
* Learning stage: 0.5x - 1x. I change my system prompt to teacher mode, taking the productivity hit for actually learning the system/tool pays off dividends later. I change my system prompt to "teacher mode" and slowly loosen it as I get more confident.
* Working-knowledge: 2x - 3x. Once I am ramped up enough I feel like I can get a decent productivity boost. Most of the time is spent at the planning stage. This is my mode for areas I don't really own or care about, just need to get work done.
* Mastered: 10x+ I have been doing web front end for 12+ years, I can quickly review plan/implementations and for my initial prompt I already know most of what I want built.
1x == my speed before AI
by lazopm - Hey, could you share the prompt you're using for "teacher mode"?
- Some domains don't have the established regularity of architecture that it takes to achieve 10X efficiency. Two I can think of off the top of my head are embedded systems, with a variety of sensors, outputs, processing power, and memory, and novel protocols like ATProto, for which training data is thin on the ground.by Zigurd
- > * Mastered: 10x+
This really needs to be calibrated to the type of work and complexity.
I can actually believe that LLMs would speed up basic web dev work in small, simple codebases 10X for simple requests.
These conversations usually turn into people talking past each other because they’re working on different things. For other less routine and more complex work, expecting a 10X productivity boost is not realistic at all. It doesn’t matter how good you get at writing prompts and reviewing plans. LLMs just don’t solve everything for you in a good way. Some times the true nature of the problem is revealed while implementing it and by deferring everything to an LLM you spend days throwing tokens at the wrong thing. There is a lot of work where the LLM speed up comes from helping you quickly search docs and codebases and double check your code, but handing the entire thing off to an LLM isn’t reasonable. These tasks aren’t going to reach this mythical 10X productivity boost that is genuinely achievable for much simpler work.
by Aurornis - This reminds me of themes I recently saw in [Harness Engineering is not Enough: Why Software Factories Fail](https://www.youtube.com/watch?v=Ib5GBkD555M) (Warning: the last 3 slides seem like an advertisement). One thing I liked is how Dex has a little graphic he glossed over showing software development is
- 25% planning & aligning with other teams
- 25% coding
- 25% testing/verifying
- 25% code review/rework
One argument was that agentic coding speeds up that coding part a bunch. So maybe there's 2x speedup in coding. But that's only a small speedup in the totality of everything software engineers do.
by gashad - Agentic tools changed the workflow in our org, we were very tense before with a simple yet careful team process.. Since last winter we're now pushing a lot more but the teamwork (which was brittle before) is now mostly gone, everybody can roll on its own, but the review process didn't scale and now monthly deliveries are full of "seems to work". nobody checks properly, nobody reviews, nobody tighten any bolts.. and nobody cares much anyway, the system allows it.by agumonkey
legit question: has anyone got ai to do all the above? i've heard people trying ai-dlc [0] but it sounds like a slog...> - 25% planning & aligning with other teams > - 25% coding > - 25% testing/verifying > - 25% code review/rework[0] https://aws.amazon.com/jp/blogs/devops/ai-driven-development...
by andrekandre- I use CC to do the testing and verifying in multiple deployment environments. It’s faster at things like coming up a plausible test payload or ten, querying a bunch of metrics from datadog, querying and verifying state from a db before and after testing, scanning all the deployed logs for relevant errors. For me that has been more of an uplift than the coding. I still feel like communication it’s worst at. So writing tickets, getting a decision out of a group, documenting only the important things, etc. it’s still not that good atby coffeebeqn
- The other hard to measure part is that I see/hear a lot of LLM usage going towards dev work that was never prioritized before.
Suddenly devs who were cranking out features with no interest in infrastructure are attacking giant refactors to make the code more understandable to the LLM.
Other devs are using LLMs to build themselves quality of life SDLC tools completely separate from the core code base.
Plenty of other examples of this.
by steveBK123 - > So maybe there's 2x speedup in coding. But that's only a small speedup in the totality of everything software engineers do.
Amdahl's Law should be familiar to anyone with a 4y computer science/engineering degree. Why aren't they applying it to their own throughput?
by whateveracct - AI is great because my job is a lot easier, but it produces some extremely crappy code that would've NEVER passed a code review 1 year ago.
You could argue that it speeds up development by 5X or more, but then it slows down testing/verifying, code review, and in many cases it makes it impossible to review/rework by hand.
I just do what I'm told at work but even though I'm sure I'm in the minority I'm extremely skeptical that LLMs can produce any good-quality code.
Looks to me like we've just lowered the bar--by a lot--and stopped looking at the code that goes out. Every time I look into how Claude implemented something it's completely insane, with no way to refactor it or maintain it in the future.
by altern8 - I have a weird issue with using AI for coding. I can code something entirely by myself at my baseline speed; call it 1x. Or I can use Claude to do it, and it does it in 1/10 - 1/4 of the time. The problem, however, is that to review Claude’s code properly takes 2-3x the amount of time it would have taken me to write it all by hand.
So my two choices are basically “YOLO, LGTM” and hope I can revert if it breaks something, or to just write all the code by hand from the start. With the increased pressure for output, I’ve noticed both myself and coworkers tending more toward “commit and hope it works” over time. It’s sort of perverse incentives in a way...
by Xcelerate - not to forget the cognitive strain of the constant back and forth between LLM and you.
One challenge is when knowing how the code should look like, the LLM solution always looks weird, and one tries to maunally steer against it, so accepting a bit of "good enough" is unavoidable to gain some productivity
by mrbnprck