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

that's the first mistake i made as a new claude user. i only knew what prompts people were sharing on forums. but since they had been written by vibe coders it was all complete non-sense. also think about this: software engineering is filled with highly specialised tooling that can easily improve software quality. the thing is, most developers dont know how to use them, and if they do -- using them is so slow that its almost not worth it.

any tool you can name claude can use. obscure academic proof verifiers, memory corruption scanners, debuggers, profilers, coverage tools, backdoor supply chain pattern scanners... it can run these and have results in seconds. really is like living in the future.

I've been using Claude to create a software architecture diagram. It came up with a lot of useful functionality that we had neglected to show but upon further examination a lot of steps didn't make any sense. It added a box to do validation on some data then it put another box downstream to do validation again on the exact same piece of data (the second box had a different name but upon questioning, Claude conceded that it was the exact same validation step). When doing inference on user input, it put a box to extract specific insights from the prompt and then it put another box to do inference again on the inferred data to categorize it... And this would add latency and unnecessarily strip out useful context when doing the second inference... It really only needed a single inference step...

I re-uploaded the diagram to Claude and confronted it and it conceded to all of my points and it even noticed a theme between them and suggested that the diagram exhibited "a pattern of redundant steps." But it was incapable of suggesting viable solutions besides name changes. All of its solutions made the design more complicated. It was incapable of simplifying the design. I've noticed this with AI code; it can make things more complicated, add more features but struggles to simplify things.

Also, AI is horrible at rating things... It's just too superficial. For example, if you write a huge amount of intentionally over-engineered, tightly coupled code with poor separation of concerns but you do proper linting, define all the types, add a lot of comments, it will give it a higher score than a shorter, more readable and maintainable snippet which exhibits loose coupling and high cohesion because it lacks the superficial aspects.

It's horrible because now business people who understand nothing about coding may ask AI about code quality and it will consistently rank low quality over-engineered projects that are full of bugs, unmaintable and less secure, with a higher score.

Frustratingly, if you point out problems in its judgement, it will concede to your points without reservation, even building on top of your argument... but it will never actually tell you this stuff up-front, unprompted if you don't already know it! It never seems to reveal new insights, at best it can only expand on existing insight which you've already had.

It tells you what you want to know but not what you need to know.