71–80 of 668 posts
Earlier quoted context omitted.
The thing that makes it work really well is to make sure it has all the tooling to verify its hypotheses. If you allow it to run the full lifecycle in loops you will be surprised how well it works.
What tooling makes this go?
Earlier quoted context omitted.
The thing that makes it work really well is to make sure it has all the tooling to verify its hypotheses. If you allow it to run the full lifecycle in loops you will be surprised how well it works.
What tooling makes this go?
I’ve been working on UI component improvements and it was doing a lousy job until i specifically told it to test in a headless browser to validate it works. I think somewhere in an AGENTS.md i have an instruction to “don’t state your guesses as fact - validate findings and results”.
A lot of people here seem to be living in a different universe than me or simply don't know how to work with AI. I think detractors believe you should just let AI do the job blindly instead of leveraging it as a tool to accelerate you. They get mad at Excel for the poor investment returns. At this point, this is such a strawman, it isn't worth counter arguing. I think I'll abandon this discussion and keep using AI qu…
> A lot of people here seem to be living in a different universe than me I feel this way on this topic too. > I think detractors believe you should just let AI do the job blindly instead of leveraging it as a tool to accelerate you. The problem is; how _should_ I use AI? On a previous thread, I had two replies to the same comment, one saying "provide the LLM all the context it needs and let it go ham", and the other…
How many of those automated fixes were reverted? How many introduced a new bug? What's the false positive rate on the finding agents? The post has counts for everything that went right and nothing for what could go wrong.
Possible (probable?) scenario:
- Marketing: "we found and fixed lots of bugs thanks to AI"
- Reality: the KPI is now to fix as many bugs as possible with the help of AI, so they used AI to search old and easy bugs in the backlog, and then fixed it manually
I've recently been using AI a lot for performance optimisation during a particularly busy period at work. I would say it was almost completely useless at the high-level direction - it would point out suspicious parts of SQL queries for example but on back to back testing these almost never resulted in any performance change. In fact, if it wasn't for the fact that it made making the actual changes I identified much e…
That might work better. I haven't tried it with SQL but it worked with a few complex UI issues I had. It identified the actual issue after a few false starts.
But since Google cares mostly about its investors, the numbers and a mention of Gemini in such a blog post are more important.