I’m sure there will be a better term but that’s my term for a multi-modal searchable vector-store where you can use words to search spaces ala “that sculpture where the man is thinking on a door?” Which returns a physical point in an indoor or outdoor map.
Huh? We are spending a lot of money. (which we were doing before). However we are fixing a lot of bugs. 2024 was not that long ago, it is insane to think we might have fixed all the bugs in that time. I have personally used an LLM to fix a few long standing rare bugs that were hard to figure out. Those bugs are now gone, but there are still many more that we haven't discovered.
LLMs are a great thing for bug fixing. However they are not a miracle. You still need to do all the other things about finding, testing and fixing bugs.
You also need to care about bugs - vibe coding rarely cares about bugs.
Are there good tools for doing context audits? I feel I have no good way to visualize what a new session is getting by default in a given repo without crawling through every potentially included markdown file
I don't know how long visionOS will survive, it seems Apple has scaled down further development of Vision Pro quite substantially. And for something like Meta-style smart glasses, visionOS is probably not a good fit.
Actually that’s supposed to have switched this year. Reportedly the legacy stuff is now wrapped SwiftUI so they all render the same buttons/text boxes/etc.
No more 2 (or maybe 3 for carbon?) implementations.
Hopefully this will let them add features and fix bugs faster.
If you are talking about AI's opening PR's then maybe you have a point. But a person opening a PR should not be met with unvetted feedback.
To be absolutely clear, AI should be used for PR review. It should be used many times. By the PR author and by all the reviewers. It should not just be piped directly from the agent to the author inside the PR. That causes the author to triage every comment.
That sounds good. But it doesn't work in practice from my experience.
The exact same skill in the hands of one person will have vastly different outcomes in the hands of a different person. The review skill I built myself has been shared with folks. They (say they) use it before they put up a PR. I still catch things with the same skill. That is evolving as I catch the model(s) at BSing. Even if I would re-share it all the time, when I catch it, these other people using the same skill wouldn't catch it.
And that is exactly why building a general purpose review agent (or skill) is harder than me having my own evolving skill. If I have to "properly" release a skill/some automation, I will likely err on the side of not having too many false positives. That is harder than still relying on a human to review the AI reviewer. The same people that were really good actual human reviewers of a PR are probably the ones that are good doing the same thing while AI assisted. And the ones that really needed these other human reviewers and processes to help them be productive are probably going to produce a vibe coded mess if left to their own devices with nothing but some AI.
Have you tried running the same review skill back to back in fresh sessions? My experience has been: 1) build complicated thing with LLM, 2) run code review, 3) it finds like 8 things, 4) fix them, 5) run another code review, 6) it finds another new 8 things, rinse and repeat.
I'd guess people truly are finding things pre-review. It's just that LLM review seems to have a limit to the number of problems it can or will find. While at the same time, LLM-written code can be an almost limitless source of bugs and errors.
It has no sense of when an architecture is doomed and needs fundamental changes. Instead, it will happily continue to chase individual bugs nearly to infinity.
But, maybe your review skill is better than the ones I've tried.
With the way memory systems work, I can see the value in having a different person's AI conduct the review as that AI's 'memory' is going to have a slightly different perspective aligned with the developer piloting it
Stock price aside, I’ll be happy using them when everyone moves on
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