I'm concerned that there's no real way to "opt out" of an AI future realistically. Is this something that people are seriously thinking they'll be able to do and successfully stay gainfully employed and contributing to the world?
> Is this something that people are seriously thinking they'll be able to do and successfully stay gainfully employed and contributing to the world?
No. I resisted for a bit but have started using it at work. Mostly because I believe usage is now being monitored. I'm in a very high-scale engineering environment involving both greenfield and massive brownfield codebases and the experience is largely a net loss in productivity. For me and some others who I've spoken to in my org, opting in is a theater that we're required to engage in to keep employment and not a genuine evolution of our craft.
These tools struggle with context once you get deep into a codebase with many, many millions of lines of code and sprawling dependencies. Even for isolated Python scripts or smaller, supporting .NET apps, the time spent correcting subtle bugs or bullshit, or just verifying the bullshit, often exceeds the time it would take to have written it from scratch.
Regardless, what I've observed is that these tools do nothing for the actual bottlenecks of software engineering: requirements gathering (am I writing the right thing?) and verification (does it work without side effects?). Because LLMs are great at generating text, they're actively exacerbating these issues by flooding our process with plausible looking noise.
Agreed. I think the starting comparison actually works here. It's a bit like the automobile. The advice of "just don't" doesn't work for cars. It takes a deliberate effort on every scale of society to accomplish, it's not something an individual can just do and succeed at. An American can't just not have a car the same way someone from the netherlands might be able to.
Over hundreds of hours of actively using AI for basically every area of my life, it has just never actually achieved anything besides giving me the feeling of productivity.
Ideas are mediocre. Plans are arbitrary. Research is untrustworthy. But telling it "generate me 100 ideas for X" feels really productive.
I think a version of me with no access AI will not just stay competitive, but even outcompete the version of me with unlimited access to AI.
There isn't. Just like with climate change and governments, we're all effectively in one big boat together. You can stop paddling towards the waterfall, but you can't stop everyone else from paddling and you can't get off the boat.
No. I resisted for a bit but have started using it at work. Mostly because I believe usage is now being monitored. I'm in a very high-scale engineering environment involving both greenfield and massive brownfield codebases and the experience is largely a net loss in productivity. For me and some others who I've spoken to in my org, opting in is a theater that we're required to engage in to keep employment and not a genuine evolution of our craft.
These tools struggle with context once you get deep into a codebase with many, many millions of lines of code and sprawling dependencies. Even for isolated Python scripts or smaller, supporting .NET apps, the time spent correcting subtle bugs or bullshit, or just verifying the bullshit, often exceeds the time it would take to have written it from scratch.
Regardless, what I've observed is that these tools do nothing for the actual bottlenecks of software engineering: requirements gathering (am I writing the right thing?) and verification (does it work without side effects?). Because LLMs are great at generating text, they're actively exacerbating these issues by flooding our process with plausible looking noise.