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Google fixed more Chrome bugs in June than over the past two years, thanks to AI

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Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#211

Earlier quoted context omitted.

That is a stat you invented out of thin air, based upon nothing but pejorative hope, against all logic or rational consideration of the timeline or the scale of the project, and you declare it the "elephant in the room"? HN is so weird on the topic of AI, and so many desperately are trying to contrive a reality. Odd stuff.

It's not an invention it's a question. If the number is <20% that's great news for the Chrome team.

The elephant in the room is how many people in this discussion are actually alien lifeforms.

The elephant in the room is how many turtles obtained law degrees.

The elephant in the room is whether this is worth discussing because we're all in a simulation.

No, it isn't the elephant in the room. You made up some horseshit that betrays how little you know about the field, which will get upvoted because HN has a hearty contingent of "if I pretend AI is actually useless, maybe that will manifest in reality" zealots. It's bizarre.

Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#212
post #210

> Google fixed more Chrome bugs in June than over the past two years, thanks to AI And introduced how many new bugs? thanks to AI ...

At this time, a generic AI snark is tiring. AI is not perfect, but it's an amazingly useful tool, we should accept it and move on.

Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#213

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…

A self validating loop goes a long way with getting AI to optimize stuff. We had some builds that used to take a long time (15-20~ minutes), that i just asked Claude to reduce the build time. It brought it down to 2 minutes and under 10 seconds for incremental builds.

Turns out folks had been copy pasting some setup code which took 2 minutes to run, and only needed to be run once per environment. Claude refactored the code to get it to run once, and since we had tests which validated the build artifacts, it was able to roll back if its change had broke the build.

Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#214

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…

Echoing the other folks, I have a different experience.

I profile sql performance and LLMs find more opportunities than I could. All it takes is real data, a sql repl and an agent. Just ask the agent to use the repl to EXPLAIN and profile the sql. It works amazingly most of the time.

Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#215
post #56

Earlier quoted context omitted.

What tooling makes this go?

Tests! Unit tests, integration tests, random adhoc scripts. You know - TDD! 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”.

>Tests! Unit tests, integration tests, random adhoc scripts. You know - TDD!

Tests =/= TDD

Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#216
post #100

Earlier quoted context omitted.

AI can not fail. It can only be failed. AI can not have limitations. Only the user can be limited.

Are you still speaking about a tool or starting a religion?

When I listen to some people or to stuff that comes out of the frontier labs, they indeed do sometimes sound like a religious cult talking about deity. I find it disturbing.

Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#218

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…

The mistake there is to point it at code to figure out performance optimizations. The place to find them would be performance profiles, query plans, telemetry. The guidance for perf still applies, measure before and after change. The issue is that the code often does not contain the information to do a perf optimization. Eg. you can't tell your cache size, the volumes of data in your DB or the latency of your network…

You can very easily spot performance issues through code. Allocations are often visible, slower hash maps are often visible, loops are visible, etc.

Re: Google fixed more Chrome bugs in June than over the past two years, thanks to AI

#220
post #44

Earlier quoted context omitted.

Have you any example materials that show a harness that an agent can be pointed at an app with some sort of telemetry tool, the results it gained and the cost of doing so? Because my experience is the same as the parents - the LLM goes on massive tangents, and the more tangents it goes on the worse the results get.

Not sure what materials your hoping for, but I've pointed codex at pprof application endpoints and just told it to identify hotspots and propose lowest hanging fruit/highest ROI items to fix, which I then approved it to open PRs for. Reduced application CPU usage by ~30% on loaded servers. It's not magic. Fairly obvious oversights that I or someone else on the team could've found and fixed if we had looked, but it wa…

Ideally a blog post on an open source project that shows harness, model, prompt and the before/after measurements plus the PR.
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