rhines
Joined 5 years ago
Joined 5 years ago
The typical employee is not given the leeway to spend time building up the infrastructure needed to enforce good output from LLMs. Previously understanding the codebase was just part of doing the work you were assigned, but now it requires that side effort of creating infrastructure. And unfortunately a lot of teams won't approve letting developers spend their time on that infrastructure, they just want the deliverables they're asking for.
The one exception is for stuff that I care very deeply about. For a very small subset of projects where I'm willing to spend hundreds of hours ensuring that what I build is the best possible thing, AI still hasn't been able to match my work unless I micromanage it, but at that point just writing the code myself is actually faster.
For almost all jobs though AI is probably the future, most software developers never cared that much about their company's code anyway.
I would much rather see an overall assets tax that scales with the value of the assets. That would incentivize more smaller businesses, long-term thinking, and wealth distribution. It would hit big corporations in the same way a LVT would, forcing them to be more and more productive with their assets the more they have, without pricing out smaller entities.
For painting, realism was really what made works great for a long time. Then photography came along and realistic depictions of things were no longer novel, so painting became about representing things in a more surreal way, and novel representations of perspective and emotion became great. Meanwhile with photography initially just capturing a clear image was impressive but now you need to capture something truly rare to have a great photo.
With AI I'm struggling to imagine what will be hard enough to achieve that it remains novel.
If Trudeau had actually pushed for election reform like he'd promised to, maybe we'd be in a better place. But people forgave him for that because he made weed legal...
For example, I used to do integrations for sports betting sites. AI is going to help with the basics, like understanding the default puck line is 1.5 in hockey. AI is not going to realize that Bet365 changes their API endpoints for each season, so you need to be ready to fetch the updated ones before the new season starts, whereas most other sportbooks have consistent endpoints that you don't need to keep updating.
How much domain knowledge is actually unavailable to AI is going to vary by domain, as will the value of that. Chess is probably one extreme, where all knowledge is public, whereas something like military R&D might be the other extreme where domain knowledge is tightly guarded.
Interests: Programming
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