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- Hacker News
- What are you writing that Claude is actually writing all of it? Every time I get past the green field stage, I just end up throwing out what it writes half the time since its trash. Claude seems really great at fix this unit test, generate this boiler plate, take this uml and build this framework out. But when I am doing refactorings, or implementing things that are beyond monotonous, I end up writing it all by hand. My best luck is still do the design, query AI for possible choices, sketch out the framework of what I am writing, have AI critique my plan, and then have AI design individual methods, then fix what it writes.by ecshafer
- "Computer" use to be a job title. So no, I am not optimistic about the future of most programmers, maybe even all programmers.
One possibility is that software starts to look more like traditional manufacturing.
The machine is the company’s core asset. The engineer only needs to know how to operate the machine well. Once that happens, the barrier gets much lower, need much less people, and the job naturally become much less valuable. Some parts will still need to be done by hand, of course. But only a very small part. It is like old factories. They used to need lots of fitters, at all levels of skill. Now you only need a few of the elite ones.
AI is the CNC machine of the software industry.
The more pessimistic future is that, maybe five years from now, the best programmers will look at AI the same way the best Go or chess players look at AI today: Like KeJie said, "I don't even know what I am trying so hard against." We now have a new SOTA every two months. It just took 18 months for LLMs from reasoning models to disproving the unit distance conjecture. ChatGPT itself has not even existed for as long as a college student spends in university.
In any case, we have already passed the point where this can be rolled back.
Maybe ten years from now I will be leaving a comment saying that "programmer" used to be a job too :-/
Programming is the low-hanging fruit for AI. Open source and knowledge sharing have given it huge amount of public, high-quality training data at a level other industries can hardly imagine. And almost everything in programming can be tested and verified inside the computer quickly in a closed loop. No robot arm is needed.
The main weakness of current LLMs is still that they are static: They do not really change themselves through use. Harness tools are just elaborate ornamentation on top of prompts. LLMs are frozen at the moment training stops. Once we get models that can change their own weights through self-feedback, then maybe AGI really is on the horizon.
Thinking optimistically: I may be lucky enough to see it in my lifetime. Maybe by then, people will be able to live more like human beings, instead of organizing their whole lives around work :-)
by linzhangrun - Low-skill work that used to be outsourced will go to cheaper LLMs, unless wages are depressed enough / running costs are high enough to keep using humans as cogs in the machine. This will also consume a ton of small-scale things, like personal-sized automation and small-business customization of better-crafted things (stuff that normally wouldn't be paid for in the first place, or only extremely rarely). Some will obviously exist, because paying someone else to farm out a ton of mediocre output with LLMs is still worthwhile sometimes, but it's going to be gutted as a general statement.
Especially with prototyping-style work, LLMs are clearly good enough for a ton of business-oriented proof-of-concepts, and that line of work is essentially dead. Unfortunately a lot of mid-tier art falls into this category as well, particularly because execs very clearly can't tell good art from bad (on a "customers like this" scale, with functionality being the judge, which is fairly objective. not a subjective "this is good art").
High-skill work is still necessary, but it's hard to tell if it's actually going to be more important (because skill is obviously still needed for actually-good results, and I honestly see no evidence that this will change with current tech) or less (primarily due to less demand, and it being significantly harder for non-skilled to judge skill when everyone can prototype something seemingly-impressive in a weekend). Some will very obviously continue to exist though.
Whether this means "high-skill people are going to be fine, stay the course" or "<10% of high-skill people will be fine, you had better be scrambling right now or looking for a new line of work" is... much less clear.
by Groxx - These are people who don't understand the job of SWE.
Look, the job of a medicine doctor, or a plane pilot, have largely been automated. The doctor could rely on google searches, or even AI, to answer your questions. The pilot can trust the auto pilot. Yet, the doctor who does advanced stuff (surgery) has no shortcut to mastering his skill : he still has to go through 10 years of studies + years of experience under the supervision of a senior with 20y of XP. Similar path for the plane pilot.
And the same reasoning applies to the SWE. AI allows to : delegate the repetitive tasks, generate the boilerplate code, fix time consuming bugs, to focus on more meaningful stuff.
AI is a tool. It's an additional layer of abstraction. The winners will be the guys who are passionate, who still put efforts to master SW, who still put efforts to remain up to date with the regular updates (new releases, new libraries, new approaches...), and who understand how to use AI the right way.
All those guys who 100% rely on AI do is help big tech cover their massive costs for the deployment of AI infrastructures. Big tech does need those guys.
Imagine the auto pilot fails for some reason, during a flight. There are 400 passengers behind. This is a minor issue for the trained and experienced pilot.
What do you do, as a SWE, when tomorrow, anthropic/google/whoever, tells you : "we can't keep running at a loss, our prices for AI have to reflect our costs. Your monthly subscription for Claude is now $500/month". Or there is a power shortage and for a couple of days you cannot rely on AI, you can only rely on your brain to deliver this feature you committed to deliver tomorrow ?
by doweneedai47 - I have had some truly spectacular results that still kind of stagger me in the last few months using Claude in my hobby projects -- but even though Claude insists on trying to slip its name into the git history as credit it's not Claude -- it's me. Someone who has studied CS and software engineering for decades will craft different prompts from someone without that background. A suggested axiom: there is nothing I can build with Claude that I could not build myself with my current level of CS knowledge, assuming I had infinite focus and time. In my hands it can go as far I could anyway, and no further. (But it is faster!) My experience bears that out so far.by retrac
- I think a lot of developers probably FEEL like they are in super mode, but in reality they're just letting Claude drive the boat and they get to wear the captain's hat.
Maybe I'm wrong. Maybe AI Natives will be faster in the end and can build / do more, or building software really is a dead field - but I noticed that I was losing my brain and had to get back into the seat.
There are definitely great use cases for agents - but I think a lot of us aren't flexing our brains anymore and, even worse, some devs believe they are. I urge every developer to put Claude down for a day/week... see how well you can do in the "old" ways. It'll still be here when you get back, but my guess is it'll be a rude awakening.
- I'm a Senior Freelance Programmer, I can see many of my past and present clients moving towards the exact path you described. I keep warning them during meetings that Claude model isn't sustainable for long, eventually the VCs will come for their revenues and Claude will be forced to close their access to all but the most enterprisey ones with deep pockets. The mere electricity cost for that kind of high level reasoning and abstraction can't be subsidized forever. However, there are other forces which pull them towards Claude and AI workflows. Most of the clients are in a "wait and watch" mode right now, using LLM assistance for code generation but not fully depending on them.
Before LLMs came, there used to be the technical debt to deal with in a project, now there is also the added cognitive debt which is way more subtle and impactful long-term. If your source of truth isn't source code but a prompt (or even a series of prompts with branches) and the executor of prompts is a non-deterministic agent, I think you've already lost the battle there.
by pyeri - My personal experience: writing code has always been the easy part. AI does most of that now.
Understanding the problem and the existing system well enough to design the right solution, even with AI assistance, is a higher cognitive load. I’m doing a lot more of that lately.
I’m more productive, but also more tired. This may be due in part to the breadth of what my team owns, which makes my day a bit more context-switchy than other teams.
As others in this thread have noted, the situation is still evolving. However, I worry less each day about being replaced by AI. There has always been more work than available bandwidth in my experience.
What seems clear to me is that expectations around velocity and throughput will increase (are increasing). AI use will be required to meet those expectations. Learning to use this new tool effectively will be essential for career progression (and preservation).
by fibonachos