Oh I'm well aware of this. I admitted defeat in a way.. I can't compete. I'm just at loss, and unless LLM stall and break for some reason (ai bubble, enshittification..) I don't see a future for me in "software" in a few years.
But it is sad if good programmers should loose sight of the opportunities the future will bring (future as in the next few decades). If anything, software expertise is likely to be one of the most sought-after skills - only a slightly different kind of skill than churning out LOCs on a keyboard faster than the next person: People who can harness the LLMs, design prompts at the right abstraction level, verify the code produced, understand when someone has injected malware, etc. These skills will be extremely valuable in the short to medium term AFAICS.
But ultimately we will obviously become obsolete if nothing (really) catastrophic happens, but when that happens then likely all human labor will be obsolete too, and society will need to be organized differently than exchanging labor for money for means of sustenance.
Any implementation moat around rapid prototyping, and any fundraising moat around hiring a team of 10 to knock out your first few versions, seems gone now. Trying to sell MVP-tier software is real hard when a bunch of your potential customers will just think "thanks for the idea, I'll just make my own."
The crunch for engineers, on the other hand, seems like that even if engineers are needed to "orchestrate the agents" and manage everything, there could be a feature-velocity barrier for the software that you can still sell (either internally or externally). Changing stuff more rapidly can quickly hit a point of limited ROI if users can't adjust, or are slowed by constant tooling/workflow churn. So at some point (for the first time in many engineers' career, probably) you'll probably see product say "ok even though we built everything we want to test, we can't roll it all out at once!". But maybe what is learned from starting to roll those things out will necessitate more changes continually that will need some level of staffing still. Or maybe cheaper code just means ever-more-specialized workflows instead of pushing users to one-size-fits-all tooling.
In both of those cases the biggest challenge seems to be "how do you keep it from toppling down over time" which has been the biggest unsolved problem in consumer software development for decades. There's a prominent crowd right now saying "the agents will just manage it by continuing to hack on everything new until all the old stuff is stable too" but I'm not sure that's entirely realistic. Maybe the valuable engineering skills will be putting in the right guardrails to make sure that behavioral verification of the code is a tractable problem. Or maybe the agents will do that too. But right now, like you say, I haven't found particularly good results in conceptualizing better solutions from the current tools.
yeah, and i'm surprised nobody talks about this much. prompting is not that hard, and some non software people are smart enough to absorb the necessary details (especially since the llm can tutor them on the way) and then let the loop produce the MVP.
> Or maybe cheaper code just means ever-more-specialized workflows instead of pushing users to one-size-fits-all tooling.
Interesting thought
OR,
something like Mercor, currently getting paid really well by Meta, OpenAI, Anthropic and Gemini to pay very smart humans really well to proof language model outputs.
I think we realistically have a few years of runway left though. Adoption is always slow outside of the far right of the bell curve.
Maybe I'm just as naive as those who said that photographs lack the soul of paintings. But I'm not 100% convinced we're done for yet, if what you're actually selling is thinking, reasoning and understanding.
Some will have to crash and burn their company before they realize that no human at all in the loop is a non sense. Let them touch fire and make up their mind I guess.
People are also non deterministic. When I delegate work to team of five or six mid level developers or God forbid outsourced developers, I’m going to have to check and review their work too.
It’s been over a decade that my vision/responsibility could be carried out by just my own two hands and be done on time within 40 hours a week - until LLMs
Perhaps outsourcing is a good analogy. But in that case I'd call it outsourcing without accountability. LLMs feel more like an infinite chain of outsourcing.
I’ve said repeatedly over the past couple of days that if a web component was done by someone else, it might as well have been created by Claude, I haven’t done web development in a decade. If something isn’t right or I need modifications I’m going to either have to Slack the web developer or type a message to Claude.
And there are no computer professionals who haven’t heard about hallucinations.
Reviewing whether the code meets requirements through manual and automated tests - and that’s all I cared about when I had a team of 8 under me - is the same regardless. I wasn’t checking whether John used a for loop or while loop in between my customer meetings and meetings with the CTO. I definitely wasn’t checking the SOQL (not a typo) of the Salesforce consultants we hired. I was testing inputs and outputs and UX.
Two things changed - Codex CLI now lets you use it with your $20 a month subscription and I have never run into quota issues with it and my employer signed up for the enterprise vs of Claude and we each have an $800 a month allowances
My argument though is “why should I care about the code?” for the most part. If I were outsourcing a project or delegating it to a team lead, I would be asking high level architectural, security and scalability questions.
AI generated the code, AI maintains the code. I am concerned about abstractions and architecture.
You shouldn’t have to maintain or refactor “millions of lines of code”, if your code is well modularized with clean interfaces, making a change for $x7 may mean making a change for $x1…$x6. But you still should be working locally in one module at the time. You should do the same for the benefit of coders. Heck my little 5 week project has three independently deployable repos in a root folder. My root Agents file just has a summary of how all three relate via a clean interface.
In the project I am working on now, besides “does it meet the requirements”, I care about security, scalability, concurrency, user experience for the end user, user experience for the operations folks when they need to make config changes, and user experience for any developers who have to make changes long after I’m off this project. I haven’t looked at a single line of code - besides the CloudFormation templates. But I can answer any architectural question about any of it. The architecture and abstractions were designed by me and dictated to the agents
On this particular project, on the coding level, there is absolutely nothing that application code like this can do that could be insecure except hypothetically embed AWS credentials into the code. But it can’t do that either since it doesn’t have access to it [1].
In this case security posture comes from the architecture - S3 block public access, well scoped IAM roles, not running “in a VPC”. Things I am checking in the infrastructure as code and I was very specific about.
The user experience has to come from design and checking manually.
I mentioned earlier that my first stab it scaled poorly. This was caused by my design and I suspected it would beforehand. But building the first version was so fast because of AI tools, I felt no pain in going with my more architecturally complicated plan B and throwing the first version away. I wouldn’t have known that by looking at the code. The code was fine it was the underlying AWS service. I could only know that by throwing 100K documents at it instead of 1000.
I designed a concurrent locking mechanism that had a subtle flaw. Throwing the code into ChatGPT into thinking mode, it immediately found it. I might have been better off just to tell the coding agents “design a locking mechanism for $x” instead of detailing it.
Even maintainability was helped because I knew I or anyone else who touched it was probably going to be using an LLM. From the get go I threw the initial contract, the discovery sessions transcripts, the design diagrams, the review of the design diagrams, my project plan and breakdown into ChatGPT and told it to render a detailed markdown file of everything - that was the beginning of my AGENTS.md file.
I asked both Codex and Claude to log everything I was doing and my decisions into separate markdown files.
Any new developer could come into my repo, fire up Claude and it wouldn’t just know what was coded, it would have full context of the project from the initial contract through to the delivery
[1] code running on AWS never explicitly has to worry about AWS credentials , the SDKs can find the information by themselves by using the credentials of the IAM role attached to the EC2 instance, Lambda, Docker container, etc.
Even locally you should be getting temporary credentials that are assigned to environment variables that the SDK retrieved automatically.
People will say "oh, it's the same as when the printing press came, people were afraid we'd get lazy from not copying text by hand", or any of a myriad of other innovations that made our lives easier. I think this time it's different though, because we're talking about offloading the very essence of humanity – thinking. Sure, getting too lazy to walk after cars became widespread was detrimental to our health, but if we get too lazy to think, what are we?
As someone who’s always wanted to “get home and code something on my own”, I do have a glimmer of hope that I wonder if others share. I’ve worked extensively with Claude and there’s no question I am now a high velocity “builder” and my broad experience has some value here. I am sad that I won’t be able to deeply look at all the code I am producing, but I am making sure the LLM and I structure things so that I could eventually dig in to modules if needed (unlikely to happen I suppose).
Anyway, my hope/question: if I embrace my new role as fast system builder and I am creative in producing systems that solve real problems “first”, is there a path to making that a career (I.e. 4 friends and I cranking out real production software that’s filling a real niche)? There must be some way for this to succeed —- I am not yet buying the “everything will be instantly copyable and so any solution is instantly commodity” argument. If that’s true, then there is no hope. I am still in shape, though, so going pro in pickleball is always an option, ha ha.
Fair point, but my hope is that the creativity involved in deciding what to build, with the choice informed by engineering experience (the project/value will not be obvious to everyone) will allow differentiation.
How? Anyone upon seeing your digital product can just prompt the same thing in no time. If you can prompt it, I can prompt it and so can a million other people.
Nobody whether an individual or business holds any uniqueness or advantage to themselves. All careers and skill sets are leveled and worthless. Implementation skills are worthless. Creativity is worthless.
The only valuable thing is data.
"Oops I automated myself out a job".
I can't help but resist this line of thinking as a result. If the end is nigh for us, it's nigh for everyone else too. Imagine the droves of less technical workers in the workforce who will be unseated before software engineers. I don't think it is tenable for every worker in the first world to become replaced by a computer. If an attempt at this were to occur, those smart unemployed people would be a real pain in the ass for the oligarchs.
Frankly, I am not sure there is a place in the world at all for me in ten years.
I think the future might just be a big enough garden to keep me fed while I wait for lack of healthcare access to put me out of my misery.
I am glad I am not younger.
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