Ask HN: In 2024, is SWE a sustainable career?

We're still a very long ways away from LLMs/AI replacing SWEs. I don't even think we'll see them replace SWE in my lifetime, at least not with the way LLMs work currently.

LLMs are great at producing single functions, maybe even a whole class. But they really are terrible architects and can't produce something that requires multiple systems to interact. Their simple method of "predict the next token" is bad at planning and is mainly incapable of producing complex systems.

Until AI gets to a point where you can just say "Create an MMORPG with these features [....]", there will be a need for SWEs. Until then, it's just "Create a function that adds all the stat bonuses from the player's gear" and hope that it can understand your other code that defines the player's gear.

The flip side of this is that AI tools can enable much faster learning, so the time to go from junior to senior can potentially become much shorter for people who are motivated.

Here is my perspective as JavaScript developer with over 15 experience and possibly more than a hundred interviews. This includes any job that mentions things like jQuery, React, Angular, Vue, TypeScript, Node.js, Deno, and on and on.

1. Nobody knows how to evaluate for competence, so technical interviews always start with basic literacy and are generally (not always) extremely subjective. This holds true even for senior developer positions. It's the equivalent of a journalist interviewing for a job and being asked to demonstrate writing words or a lawyer demonstrating they can read.

2. There are some extremely talented brilliant people in this line of work, but you will likely never know if you encounter them. Few people in this line of work have any incentives to do more than put text on screen using a framework. That means most of the brilliant stuff happens only in never disclosed personal projects far outside of work or at the largest software companies with budgets dedicated for exploratory open source projects not directly associated with the employer's primary business interest.

3. Low confidence and emotional insecurity are out of control in this line of work. There is little incentive to become an excellent craftsman in this line of work, because its rarely rewarded but frequently discouraged. The primary business interest with regards to this silo of software is hiring. Way back in the day when I first started writing this sort of code it was all about talent discovery, which was very expensive with poor results. So, instead its long become about finding for the lowest common denominator because they are cheap to replace. Many of the developers doing this work are fully aware of this and are utterly reliant upon a single tool or set of conventions to qualify their employment, which is extremely fragile. Worse, most of these people are entirely replaceable by ChatGPT and there are YCombinator start ups already building those products.

4. I have encountered so very many people in this line of work that cannot measure things and cannot write. I am not talking about writing books, but writing quick emails or simple dirty documentation so that you are not repeating the same failures over and over. Based on that, in past years, I would suggest to people offline in the real world that everybody should become a software engineer. If you can pass a 30 minute interview and write your name then you too could have a 6 figure income with low stress sitting at a desk all day. You didn't even need any kind of education.

In summary none of that is sustainable. Years ago I remember people on here scoffing, laughing, and becoming angry at the idea of professional licenses for software developers to identify the capable adults apart from the children in the room. The entitlement was pretty brazen. Then suddenly most of these people then found themselves out of work. Now when I bring up stuff like licenses or certifications the reaction is completely different.

I've been programming since approximately age 8, so around 40 years. For the past few years have been focused on generative AI, agents, etc. I have built multiple agent frameworks in Node.js, Rust and now Python.

I use AI with my agent system to help me write code for projects and my agent system. The leading edge models are incredible, but still somewhat brittle. They can make some weird mistakes. And I definitely have to go back over things.

But actually given all of the necessary context they can already complete a surprising number of programming tasks with good supervision.

It is night and day beyond the capabilities that it had a couple of years ago when I built my first agentic coding tests.

The thing that people strangely still seem to not get is that these systems will continue to improve rapidly. We continue to break through barrier after barrier with new paradigms. Now we are on the inference time ramp which is going to lead to large gains in intelligence.

There are more significant gains to be had also with things like multimodality and just plain efficiency increases from ASICs.

Beyond that, new machine learning approaches such a JEPA, new hardware paradigms built on memristors, etc.

Robotics and integration of new general purpose machine learning into robots continues to improve.

In less than five years, human software engineers will not be able to compete with AI in most contexts. Not only that, they generally will hold projects back if they are involved.

Before we get to the fully general purpose AI software engineers, platform specific tools with integrated agents can already with current models be very competitive in producing customized software for specific domains.

But it's not just software engineering. It's literally every single job. Including plumbers and all of the physical labor which currently is safe but improved robotics are just a few years away.

It seems obvious to me that normal careers are just not a good plan.

Instead, think of AI and robotics as incredibly cheap labor that will be available to just about everyone. So you become an entrepreneur, or the manager of a sophisticated network of teams of robots/AI running on a blockchain. Think about how to leverage these systems to provide goods and services.

"Even if you do manage to make it as an IC all the way into your forties, you're going to run into the pervasive age discrimination, which is only getting worse."

Is this really the case? With the demographics of today, where can employers find all these young SWEs to replace the older SWEs?