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I dunno man. Claude has been very effective given enough context and specifics on tooling.
Another thing is that I work in a really big org vs the far more free world of indie / bitcoin Dev.
I also see a bug spectrum of effectiveness with LLM operators and paradigms that seem to fit better than others.
Functional programming and smaller modular approaches seem to be easier to leverage LLMs. Massive complex OOP projects are much harder to reason about. Even strongly and loosely typed languages seem to have different levels of effectiveness in this world.
And I also wonder how many people taking about LLMs are still using chatbots with limited context and memory vs tools like Claude Code, Pi, or Open Code. These things make a massive difference in the results.
On top of all this is learning how to use the LLMs instead of forcing them work the way you prefer. There are always tradeoffs. No silver bullets. We lose something when we use LLMs for sure
Yeah... we might need to define devops. The kind of tasks I am thinking of are tool configuration mostly. Not architectural design if systems. LLMs are good at patterns. Not so much at creativity.
IMO It’s a bit like how folding laundry is less complex than programming. Maybe it’s more rote for humans but bots are not trained to do devops and have a harder time with that class of problems.