We need 70% less coders as the AI handles most of the coding
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This is the sort of work that AI is coming for. It's low impact, low effort, low paid, and importantly it doesn't get automated (often). This means there is a lot of low hanging fruit for automation, whether that's by regular tooling or LLMs.
On the other hand, if you're a highly paid software engineer, it's likely you're already working with highly automated and abstracted systems, so there's much less opportunity for LLMs. If your deployment process is a Word doc specifying the 120 steps you have to run in bash to deploy that takes 1 eng day, that's going to be automated, but if you're git-pushing and having Kubernetes roll it out in your CI/CD flow, automation has already raised the level of abstraction that you need to work at and there are fewer opportunities.
Yes there's Copilot/etc which will reduce boilerplate, but the only way a company achieves "70% less coders" is by wholesale automation of large parts of their process that must be horribly basic already.
The entire concept that if you make coding 70% more efficient that you'll make coders 70% more efficient is simply wrong.
Given a full time worker vs a contractor, I'm guessing the contractor has far less knowledge of the system as a whole, and ripe for being replaced. Then with freed up funds, maybe they hire more internal developers. It could be more of a reshuffling than anything else.
I think you're wrong about this. There are people today getting paid lots of money for basic jobs, and people with real difficult jobs that don't get paid much. Pay rate is as much a function of location and your particular company or industry as it is the actual nature of what you are doing.
>Yes there's Copilot/etc which will reduce boilerplate, but the only way a company achieves "70% less coders" is by wholesale automation of large parts of their process that must be horribly basic already.
The basics often only seem basic because we've done them a great deal. When the machines are charged with doing a lot of stuff, will the basics still appear basic? Will you be able to spot the critical yet tricky errors buried inside reams of code for a process that you never have to develop yourself? Furthermore, will you be able to skip all the basics in your career development and work on advanced things? I have my doubts. A lot of "horribly basic" "drudgery" will have to be done manually, because it is too important to leave to the whims of a LLM and people have no other way to develop the necessary skills to sustain the industry.
When I'm talking about pay I'm thinking location-agnostic, i.e. low to high pay within a comparable region. For every engineer in London earning £100k there's many earning £26k doing more basic work.
And when I say "basic" I don't just mean working with low level systems, I mean working with systems that are un-automated. Working with processes where someone has made the judgement call that it's cheaper to throw large numbers of cheap engineers at the problem rather than fewer highly paid engineers to automate it all away.
That's not to say that highly paid engineers don't need to get into the basics, they definitely do, but that digging into the depths of an automated deployment system is not the same as running repetitive manual tasks.
I'm talking about the programmers that a friend of mine works with who take several quarters to produce a dashboard, or the entry level PHP jobs that make barely above minimum wage and sell custom websites and hosting to real-estate companies in small towns, or the outsourced programmers that other friends interact with, who spent ~10 eng over 2 years building a "PaaS" style system in shell scripts that no one in their company actually uses because surprise surprise no one ever thought to ask whether it was necessary or had the right feature set or even worked (but management paid for it).
These people are spending a significant amount of their time coding, but they're not spending time automating, or improving the process for next time, and so the work they're doing is fairly trivial and is most likely to be impacted by AI.
What I find odd is that AI tools are used to create new code but the bulk of the work is in rewriting and changing existing software,and fixing issues by touching single lines of code spread throughout the project.
Perhaps AI tools will improve, but today you need an awful lot of prompting to get a single decent usable starting point. In some applications you end up spending far more time prompting the AI tool than what you would end up doing by simply writing the thing.
> boring low paid drudgery
> the sort of work that AI is coming for
AI is hopeless, because of the sheer lack of anything to accurately train itself for this task. It is trying to sell itself to the OEMs and platforms with shiny demos as an even cheaper alternative to the bottom feeding group of outsourced labor.
The joke is going to be real when the $$$ are spent on AI and the outcome is outsourced to the bottom feeding group to maintain.
Strange that the people in the trenches are saying that AI is helping them, but people on HN are screaming that AI is useless…
I mean, it sounds a lot like a standard management failure mode, which must be about half a century old at this stage: pretend you can get by on X% of staff due to [faddish pretext], then a year later when the cracks start showing quietly hire more people again. The nature of the fad changes, but the basic story is generally about the same.
Actually, I’m not sure it’s even that; at this point the claim seems to be that they _can_ get by on 30% of the staff, not that they _are doing so_. There’s a decent chance this is just a case of “oh, shit, earnings call coming up, we have to mention AI because the markets like that”, tbh.
AI has made big splashes and some industries are in the process of getting annihilated (ie. Designers working for marketing agencies and similar roles). I'd expect things to get more spicy over the coming decade for programming, too... But right now, at this very moment: LLMs can't code good enough to save time unless the programmer is a total novice.
Might be different in SV or at a FAANG, but speaking from my nearly 4 decades of experience in tech, many to most programmers that have come up in the last 20 years are either lifetime novices, or at least just barely capable of productivity. I see 80% of the work being done by the top 20%. I think AI is definitely going to devastate the vocation because it’s going to replace that 80% barely productive group. I can see a future where most of the code is written to a 90% completion level by AI, then finished by the best of the best of us ugly bags of mostly water.
I fired the me responsible last week.
Just spend time adding very simple script as cronjob by CI/CD... And everything was copy paste. But it still took time to set up and name things. To get the small inconsequential details right.
What they won't be good at is when there are deeper semantics, when there are performance requirements, when there's a complex data model, or when you need to come up with the data model and consider how that will work over time.
All of these issues are nearly impossible to spot and correct unless you're an expert yourself, but then you wouldn't need AI in the first place.
That said, I fully expect such an industry to take off and we'll all be worse off for it. Lowering the barrier to entry is empowering for those who couldn't develop software before, which is good, but if it enters mainstream usage then we're all going to suffer even worse products and services.
I’ve tried doing just basic json printing apps and the AIs (GPT-4o, Claude Opus, Gemini) often fail me after digging into what needs to be done.
They do great at scaffolding things and getting you maybe 40-50% there, then they hit a brick wall of awful code and not doing what I want.
How can you replace devs for even these simplest cases? It just doesn’t work at the end.
> Due to GenAI and in-house built developer productivity tools, we have increased the output of our software developers by around 70% year-over-year. In parallel, we have been carrying out a large-scale digital talent transformation, accelerated by our in-house AI + human-powered code-reviews-as-a-service capability. As a part of this we have been reducing 3rd party software engineers in our organization by around 60% percent in the last 6 months.
They have increased in-house developers' productivity, which means they are less reliant on 3rd party developers.
If you do the same with translators now in May 2024 you will provide a horrible service.
June may be a different kettle of fish!
For a 40h all week job that is less than 1h
Not enough time to even understand the requirements of a 40h job.
10h would be minimum.
Unless you are just checking that the style guide is correct and obvious missed null checks.
For this reason I feel code reviews are a bit silly and pair programming is way better (pairing with a mix of sync and async work) but that is an aside.
In addition a code review being short is usually because the coder and reviewer are both very competent. Once AI enters the chat the reviewer needs to look very closely at every line.
It’s going to be the same with AI. It pumps out a lot of code. Human does spot checks and probably uses other AI to help with the code review. A real human does the really hard, critical code directly. A more robust QA team makes sure it all works.
In some way reviewing code is more complicated and hard than actually writing it.
I really like the „reverse centaur“ metaphor by Doctorow regarding the automation AI will bring us - humans having to double check the stuff AI wrote for correctness in AI pace.
Unless they were paying a whole bunch of programmers to do not much useful at all or just incredibly simple repetitive things, this is obviously not true to anyone who has tried to use LLMs to solve problems.
I’m guessing some mid management sold the idea of firing 2/3 of the development staff and somebody is declaring victory a bit early.
It's excellent at getting code snippets, suggesting possible ways on how to handle something, etc. I recently had to help out my son with Arduino programming, which I'm totally new at, and thanks to ChatGPT this was super fast and easy.
But to handle an actual codebase, even a single developer codebase, it just doesn't have enough context for that.
I'm sure some day computers will be smarter than us, but some people are still seriously overestimating this.
Sure, it's much more possible for bob from accounting to throw together some trivial python script than it was a few years ago, but it seems the main benefit more skilled programmers get from it seems to be helping with syntax and pumping out boilerplate. Which is quite a bit of programming work but well less than 70% of it.
When a problem is tricky, it seems people turn off the autopilot.
When AI starts to produce compilable non-trivial code, I'll consider changing my mind, but that has yet to happen.
Visual Studio can auto suggest me stuff while I'm refactoring, that easily saves me an hour a week of work during a busy week. The rest of my work can't be automated by any current AI, because most of my work is thinking, debugging and testing.
LLMs can only go "Oh, i'm so sorry, let me just try brute forcing the problem! Heres another variation of the solution, please spend 5-15 minutes testing it to exhaustion!" - "Ah, my bad, heres another fix that doesnt work: ..."... etc.
Months can go by before I get to solve a good DS & A problem in production. Most of my job consits of fighting with the mundane drudgery of fighting with cloud providers or getting crappy frameworks to do what I want.
I think the value of people who have a deep understanding is about to skyrocket.
This is because the corporate culture and reward structure incentivise using the cheapest labour to spend as much money as possible delaying delivery for so long that accountability doesn't come home to roost and the system can instead be scheduled to be replaced by a bigger worse new project before it ever gets finished.
Yeap I'm cynical but there are precious few 'wow they are doing it right' 'efficient and effective' stories from big corp IT.
They are probably right about their help desks too. And so on.
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Some studies suggest that the lines of codes produced per time unit is more or less constant across different languages. What matters is what those lines do. If you are programming in assembly, it's going to take ages of very verbose programming to get anything done. Do the same in Haskell and you might reduce it to a couple of lines of code.
Based on what happened in the past, we might expect programming work to outgrow the efficiency gains. That's what has happened every time there was a step change reduction in cost for producing software. The community of developers keeps expanding and isn't shrinking.
Reading code is sometimes much harder than writing it yourself. If you still have to validate the code, I don't understand how it's a net gain.
With an elastic demand there will be more code not less coders.
Basically almost all intellectually challenging problems have a major component of programming, to the point that most engineering professions are thought of a special case of 'programmer'. Data Scientists', ML engineers', Electrical engineers' valuable outputs are usually some kind of computer code.