Ultimately hardware, software, QA, etc is all about delivering a system that produces certain outputs for certain inputs, with certain penalties if it doesn’t. If you can, great, if you can’t, good luck. Whether you achieve the “can” with human development or LLM is of little concern as long as you can pay out the penalties of “can’t”.
As for more dedicated to Ops side, it's garbage in, garbage out. I've already had too many outages caused by AI Slop being fed into production, calling all Developers = SRE won't change the fact that AI can't program now without massive experienced people controlling it.
The article's premise (AI makes code cheap, so operations becomes the differentiator) has some truth to it. But I'd frame it differently: the bottleneck was never really "writing code." It was understanding what to build and keeping it running. AI helps with one of those. Maybe.
AI will not get much better than what we have today, and what we have today is not enough to totally transform software engineering. It is a little easier to be a software engineer now, but that’s it. You can still fuck everything up.
Wow, where did this come from?
From what just comes to my mind based on recent research, I'd expect at least the following this or next year:
* Continuous learning via an architectural change like Titans or TTT-E2E.
* Advancement in World Models (many labs focusing on them now)
* Longer-running agentic systems, with Gas Town being a recent proof of concept.
* Advances in computer and browser usage - tons of money being poured into this, and RL with self-play is straightforward
* AI integration into robotics, especially when coupled with world models
adelmotsjr•2h ago
F7F7F7•38m ago
But not defining what an SRE is feels like a glaring, almost suffocating, omission.