mc-0

I'm 3.5 years into my career. I was able to enjoy the first 10 months of it ignorant of the storm LLMs / agentic development would bring.

The never ending promise of my job being automated away is soul crushing, especially considering I made a career change & got a 2nd BS degree in computer science to get into the software space.

I'm really at a loss given how bleak things are made out to seem and its really crushed my motivation. I don't have a lot of senior engineers around me and I am eager to find a better environment. But in trying to prepare to do so I don't know how I evolve as the career changes (or dies?).

Where should I be spending my time? What should I be learning?

Claude can make decisions about architecture and create an implementation in code. If I've never been experienced to real system design in practice or know much of the programming language it chose to use, how do I bridge that gap?

I'm almost 4 years into my career as a software engineer. Before widespread LLM adoption I had to do a lot of research when writing code.

When replacing SWEs in the future gets discussed, a lot of people say things like "Oh someone has to review the code" and "they'll always need to be a human in the mix". But when are these humans supposed to acquire this knowledge?

Claude Code can help me create things a lot faster. I can vibe code stuff that would take me a lot of time to learn and build. But I understand none of it. When people talk about productivity, it seems like most gloss over the fact that those who already know how to do things & have experience are going to be the most productive. Yet I often hear no discussion as to how people should be bridging the knowledge gap.

I am sure others make a deliberate effort to learn while they leverage these tools, but human beings are lazy. With the constant pressure to increase velocity & productivity at all costs, people aren't going to prioritize learning things. At work I already see SWEs & people in technical roles taking the path of resistance:

- Asking copilot in agent mode to run a command instead of literally typing it themselves

- Suggesting a mermaid diagram for a large legacy system written in COBOL is accurate because "that's what the LLM said"

- Making the statement that "we really won't need to understand data structures & algorithms in the future, those problems are already solved"

Doesn't it seem like the era of AI is devaluing knowledge or talent and dressing it up as though it's making people more productive in ways they otherwise wouldn't be?