If I had to highlight the one thing all those conversations had in common it would be precisely this:
I thought that having this knowledge would set me apart
* The curve of AI improvement will continue at the current pace
* AI companies will have the capital continue to expand infrastructure
* there will be some kind of functioning economy if all knowledge workers are replaced
There are strong headwinds to all three of these.
Hey it may come to pass but it’s very speculative at this point. I see a lot of tech people simply overlaying the progress curve of previous tech booms which is reductive.
In my position, our team is clearly displaying "increased demand due to increased efficiency". I admit our position may be situational -- but my anecdote seems more substantive and speculative than "I disagree" from my vantage at least.
> Work that introduces new methods, highly creative ideas, or solutions that have not been used or experienced before. More generally, an approach that introduces an innovative strategy to solve a complex problem.
Something that I've been thinking about for the past year or so is coming to grips with the fact that the vast majority (anecdote) of software engineering work is not novel (and maybe that's okay). Few opportunities lend themselves to doing truly novel work. Other than infrastructure work and highly specialized software, pause and ask yourself when you last encountered software were you said "how the hell did they do that?" or "damn, that's nice" (for me, the most recent was Ghostty). I think much of the angst that people have when they fear for their job is coming to the realization that LLMs can do most of the "standard" work that a lot of highly compensated individuals currently do. We've built livelihoods around this and the threat of that coming to an end is genuinely frightening.
The practice of writing code, or programming, in recent years has really fallen into two buckets:
The vast majority of folks are given a task, they write code to complete that task, and the task completion then counts towards some objective (eg; a new feature, product or fixing a bug). Perjoratively, they've been known as "ticket takers".
A much smaller group have instead worked in the other direction-- identifying where improvements can be made to a product, piece of infrastructure, or pain point and transformed that into tasks that can then be solved via code.
How much of a role you play in that strategy and formulation has been the real differentiator. Not so much what you know. While these are correlated, they're very different.
At a high level, it's been the difference between "developer" and "engineer" but the reality is the titles have become somewhat meaningless in recent years where many "engineers" are just doing the same CRUD tasks over and over.
The reason this matters is that at some point, you can only abstract so far... the requirements for what to build have to come from somewhere. At the most extreme case, there's only the CEO and a company that's nothing but AI agents. In the least extreme case (today) each line worker could manage 1 or more LLMs/agents.
It's not entirely clear to me or frankly a large portion of those in the industry that we're suddenly on pace for one outcome vs another. But I do think that software isn't particularly unique here other than it was an initial starting point for LLMs to deliver value. All white collar work is at risk including CEOs.
And if that happens it would be outlandish to think a utopia emerges... the opposite is far more likely.
No, it does not. There is no ceiling for complexity.
I feel that OP has reach that point because he went out of the basic tooling like Claude Code (at least in its default state) and embrace multi-model, automatic reviewing, fuse, loops and so-on, when it's done right, well, failure rate to solve issues is <1%, this is exactly why you arrive to that kind of depressing thoughts afterward and it's spot-on.
Many people will disagree because they are still at the vibe coding stage, not "as much as I can prompt will be automatically done stage". Claude Code imo is deliberately not implementing the best ways for users to work, they have recently implemented Workflows but that's almost a year late, many companies are doing this since always and that's just part of basic tooling nowadays.
People talk about models and benchmarks score while genuinely I'm baffled because they seem to ignore that that same benchmark can reach 99% by levering tooling intelligently, we don't really need better models (at least for coding), we just need adoption of proper methods. The day developers will discover that they are already able to solve 300 issues in a single day with ZERO supervision in complex Rust codebases, I'm sure they'll change their mind.
Our bottleneck in our team is currently just having the mental bandwidth to type as much as possible, it's kinda sad, it is becoming all absurd.
If you are still watching the output of the model for coding tasks, I bet you haven't challenged your own methodologies, yet.
Extremely formal syntax, limited ambiguity, simple verifiable testing procedures, and colossal well-documented training sets.
I don't yet buy that the successes of coding agents will apply nearly as well to other professions. "Correct more often than not when asked a random accounting question" really isn't any indication to me that they'll get there.
We became for AI what our clients were for us. Some hate it, some love it.
To feel safe in life our clients needed to have an actual business. Now when we are the clients of our AI we are scared, because now we need to have an actual viable business. Economic machine that works. Because the old model of just selling our time and effort to a client no longer works, when we are the clients.
TLDR: there will be less programmers and they will be better on average.
This entire section is backwards to me.
The current state of a lot of different domains I've been in is that they tend to center around 2-3 major, generic products that all get retrofitted to fit those smaller/medium-sized businesses. Now that the economics have shifted, it makes sense for those businesses to bring on software devs to build software tailored to their problem specifically.
And you can't compare copyrighting. It's a totally different field, with different goals and different time tables.