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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

#291
post #21

Earlier quoted context omitted.

1. Our backlog of bugs gets processed quicker because instead of staring at the code for 10 minutes fiuring out what's happening, there's a tool that can reason about it quicker. 2. Code reviews and security reviews happen quicker and produce more findings. I would think that (m)any team(s) using AI might also be seeing a higher rate of finding and fixing issues. Even the Linux Kernel (I'd say Windows and Apple too)…

Linus: "it keeps finding embarrassing bugs" Linux Kernel: https://lore.kernel.org/all/CAHk-=wi4zC+Ze8e+p3tMv8TtG_80Kzs... The idea that software has gotten so complex that a machine can evaluate code paths better than a human, seems to bristle the fur of many. Some people didn't think we would see the day where that comparative human limitation was laid bare in simpler tasks than they expected. I believe older develo…

> The idea that software has gotten so complex that a machine can evaluate code paths better than a human, seems to bristle the fur of many

Lol! What about fuzzers, linters, typecheckers and formal tooling? There’s plenty of machine code evaluators that people do use because it’s better than relying on human skills.

The issue is the actual report and the lack of information.

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

#292
post #66

Earlier quoted context omitted.

Which model/agent/harness tool did you use? I've found what you describe was my exact experience some ~6-8 months ago, but since about a month or so the game has completely changed. Using 5.6 Sol with highest reasoning setting in Codex or Fable in Code, the models come up with a list of possible improvements from static analysis (ranked by complexity/benefit), write and run their own custom profilers and deliver sign…

Very hard to say anything definitive on this because it's a moving target, but last time I tried models still had a distinct sense of "consistently good, sometimes great at micro, bad at macro". Similar to how, even for relatively pedestrian CRUD, they'll do code that's objectively fine at the function/file/class level but can still make a mess if you don't supervise them at least at a high-level.

Which model and harness did you try?

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

#293

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…

I am not denying what you are saying but I am interested in what models you were using for these tasks?

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

#294
post #137

Earlier quoted context omitted.

You're using it wrong. No really you are. Give Fabe 5 access to a test database with some data, or even restricted access to your live DB and tell it to optimize then. I've had stunning success optimizing for performance this way. In a single day, I made the core part of our app 2-3x faster.

Thats fine but then Fable 5 should have requested this information instead of blundering along. So why didn't it? An expert human asked to do the same task would have surely asked for the additional data.

Let me translate this for you:

"I have not spent the time cultivating the soft skills necessary to leverage this tool successfully therefore it's the tool that sucks."

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

#295

Earlier quoted context omitted.

> It would be useful if people always explained their exact use cases when making claims one way or another. I understand it's not feasible for many use cases to reveal exact details, It would be useful if people _ever_ explained the use cases. Even Anthropic when they're publishing their materials are hand wavey about this. > Gamedev is a good example of where AI shines, since the risks of fucking things up are not…

AI is great at reading, so give it things to read. Claude will try to throw big markdown docs in your repo, but you don't have to do that. Make it keep docs by the code. I include a line in AGENTS.md that says "We *always* add docstrings to methods, classes, structs, and namespaces - there should be 100% coverage of docstrings." It will make better choices about what functions to make or remove if you force it to jus…

It’s clear at this point that agents don’t actually follow agents.md

They try to but they don’t. As an example, we use perforce in games. I regularly have to stop an agent and remind it to use p4 edit rather than blasting through the read only flag, despite the first paragraph of Claude.md being “this is a project using perforce. Batch call p4 edit on all files before modifying, do not manually remove the read only flag”

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

#296

Earlier quoted context omitted.

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…

> The place to find them would be performance profiles, query plans, telemetry. Tbh, once this information is available (which is the tricky part), in 99% of cases there's really no AI needed to analyze the data, since the 'low hanging fruits' will usually stand out anyway. And once you get into the area where optimization hotspots are no longer obvious, you're already deep in the diminishing returns area and optimiz…

>in 99% of cases there's really no AI needed to analyze the data

As I've seen it, there's a large chunk of those getting the most out of AI doing so because they weren't aware of or couldn't be bothered by already existing, more reliable alternatives.

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

#297

Earlier quoted context omitted.

Linus: "it keeps finding embarrassing bugs" Linux Kernel: https://lore.kernel.org/all/CAHk-=wi4zC+Ze8e+p3tMv8TtG_80Kzs... The idea that software has gotten so complex that a machine can evaluate code paths better than a human, seems to bristle the fur of many. Some people didn't think we would see the day where that comparative human limitation was laid bare in simpler tasks than they expected. I believe older develo…

I don't know, this more and more feels like a sentiment projected on to people than anything real these days.. Like even in that linked thread, is personal offense like you lay out here really were you can place Laurent Pinchart's push back? You don't read anything else there at all? And either way, what, we are going to keep this line going for another 5 years? Aren't you bored?

> You don't read anything else there at all?

The citation was in support of the post above mine and was incidentally a link to a mailing list. I did not read the mailing list threads out of personal interest, admittedly. I think it's a particularly bad way to communicate (took 15 years for me to figure it out), so I avoid them.

> Like even in that linked thread, is personal offense like you lay out here

Taking it personally, is a concrete demonstration of what I described. The replies to my comment, are unsurprising.

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

#298

Earlier quoted context omitted.

Ultimately the harness is me and the experience is like managing an unruly toddler. You have to pay attention to what it does and issue corrections. Skills and prompts and AGENTS.md do some, nested sets of agents do some, but over it all is me keeping track of what it's doing and needs to do. You have to size the unit of work to its useful attention span, you have to have code architecture that is conducive to units…

Gotcha, so no.

You don't need a "blog post." You need experience managing projects, tracking progress, coordinating conversations, mentoring less experienced engineers, etc. That experience comes with practice and time.

If you really need something to latch onto, there's plenty of educational material available about how to be an effective scrum master. Start there.

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

#299

Earlier quoted context omitted.

In my mind there are three tiers: The SOTA: Fable, GPT 5.6 Sol, Opus 5 The "enterprise admin did not turn on the new models": Opus 4.8, GPT 5.5 The "I love hallucinated garbage": Sonnet, Qwen 3.6, GPT 5.4 mini, GPT 5.3 Codex, etc. Results vary widely

What did your tiers consist of when GPT 5.3 was the latest?

I believe I was still using Opus 4.6 with the Claude Code CLI.

Before that, Gemini 3 Pro in Antigravity.

I have no experience with GPT 5.3 beyond seeing the nightmares colleagues produced in their MRs with GPT 5.3 Codex. It could be that they had the distilled 5.3 Codex Spark selected, I am not sure.

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

#300

Earlier quoted context omitted.

I agree with you. > I think detractors believe you should just let AI do the job blindly instead of leveraging it as a tool to accelerate you. However this is how it’s marketed. C-suite is telling people eventually you won’t need to read code, frontier labs saying programmers won’t exist etc. The reality is like you said, a tool to accelerate you.

You can today develop a mobile app with 20 screens without ever reviewing any of the code generated. If you test each feature and have it iterate on your feedback, you can build a decent product in this way. Does it write too much code? Perhaps. Could I bring those 100k lines through code review in a team where some members nitpick? No. That does not change the fact that it works, and that you do not need to read the…

Unless the app is released and running on user’s device, your “it works” is on the level of hackathon’s demo. Being on prod has always been the true testing ground of code.

It seems like when people are talking about production level quality and how the AI. should be helping them there, plenty of people comes up with their “it works on my machine” anecdotes.

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