Older Windows bugs seemed fair: mostly edge cases, weird UI interaction, or stuff that only came out under heavy workload (also, windows file system).

This past few year, the bugs are incomprehensible. I understand non-professional versions are considered as Beta since Win10, but what it felt like is that Home version are actually alpha, and windows pro seems more and more like a beta.

Windows bugs have moved more and more into the 'edge case' territory. Not that major issues don't crop up for "everyone" today, but BSODs used to be much more common. Part of that was due to the architecture, thus drivers, but the other side of it was core Windows functionality that just had bugs.

But Explorer has had it's fair share of issues. I have a 98SE machine to prove the stalls, lockups, lack of refreshing directories, etc...

I don't really agree. Aside from how it handled frontend code, changes in Sonnet did not truly impact my overall productivity (from Sonnet 3.7 to 4 to 4.5, i did not try 3.5). Opus 4.5/Codex 5.2 are when the changes truly happenned for me (and i'm still a bit distrustfull of Codex 5.2, but i use it basically to help me during PRs).

I also chat with these models for long hours about deep, complicated STEM subjects and am very impressed with the level of holistic knowledge and wisdom compared to models a year ago. And the abstract math story has gotten sooooo much better.

The worse part is reading a PR, and catching a reintroduced bug that was fixed a few commit ago. The first time i almost lost my cool at work and said a negative thing to a coworker.

This would be my advice to juniors (and i mean basically: devs who don't yet understand the underlying business/architecture): use the AI to explain how stuff work, generate basic functions maybe, but write code logic/algorithm yourself until you are sure you understand what you're doing and why. Work and reflect on the data structures by yourself, even if generated by the AI, and ask for alternatives. Always ask for alternatives, it helps understanding. You might not see huge productivity gains from AI, but you will improve first, and then productivity will improve very fast, from your brain first, then from AI.

Losing your cool is never a good idea, but this is absolutely a time when you should give negative feedback to that coworker.

Feedback is what reviews are for; in this case, this aspect of the feedback should neither be positive nor neutral.

Now question is..

is AI providing solutions smarter than the developer using it might have produced?

And perhaps more importantly, How much time it takes AI to write code and human to debug it, even if both are producing equally smart solutions.

* Force the AI to write tests for everything. Ensure those tests function. Writing boring unit tests used to be arduous. Now the machine can do it for you. There's no excuse for a code regression making it's way into a PR because you actually ran the tests before you did the commit, right? Right? RIGHT?

* Force the AI to write documentation and properly comment code, then (this is the tricky part) you actually read what it said it was doing and ensure that this is what you wanted it to do before you commit.

Just doing these two things will vastly improve the quality and prevent most of the dumb regressions that are common with AI generated code. Even if you're too busy/lazy to read every line of code the AI outputs just ensuring that it passes the tests and that the comments/docs describe the behavior you asked for will get you 90% of the way there.

I agree with the idea, I do it too, but you need to make sure the test don't just validate the incorrect behavior or that the code is not updated to pass the test in a way that actually "misses the point".

I've had this happen to me on one or two tests every time

To give some further advice to juniors: if somebody is telling you writing unit tests is boring, they haven’t learned how to write good tests. There appears to be a large intersection between devs who think testing is a dull task and devs who see a self proclaimed speed up from AI. I don’t think this is a coincidence.

Writing useful tests is just as important as writing app code, and should be reviewed with equal scrutiny.

For some reason Gemini seems to be worse at it than Claude lately. Since mostly moving to 3 I've had it go back and change the tests rather than fixing the bug on what seems to be a regular basis. It's like it's gotten smart enough to "cheat" more. You really do still have to pay attention that the tests are valid.

Of course, for customers it is just one more reason you need to be looking at every AI outputs. Just because they did something perfect yesterday doesn't mean they won't totally screw up the exact same thing today. Or you could say it's one more advantage of local models: you control the knobs.

The irony is when company did lay off him due to covid the actual velocity of the team increased.

And since it's way, way less wrong than sonnet4, it might also improve my whole team velocity.

I won't lie, AI coding has been a net negative for the 'lazy devs' on my team who don't delves into their own generated code (by 'lazy devs' here I mean the subset of devs who do the work but often don't bother to truly understand the logic behind what they used/did. They are very good coworkers, add velue and are not really lazy, but I don't see another term for that).

> The new Trump-class battleships will replace the Navy's previous plans to develop a new class of destroyer, the DDG(X). However, the sea service intends to incorporate the capabilities it had planned to employ on that platform into the new Trump-class ships.

If we talk about my whole team output, I'd say the impact on code production is like 80-100%, but the impact in velocity is between 10% and -25%. So many bug in production, security holes, so many poor models definition making it to production DB only for me and the other true senior to have to fix it.

We are seniors, we read your PRs and try our best to do it thoroughly, but with AI multiplying your code output, and writing quite convincing solutions, it's way harder, so please: if an AI have written the code in your PR, verify the tests are not superficial, verify everything works, think for yourself about what the model is used for and if it can be improved before release. Re-verify the tests (especially if the AI had issues writing/passing them). And do it once more. Please (hopefully one of my coworkers will read this).

Don't read this person. I'm not saying you have to read the whole book to use a quote, but talking this confidently while doing what we call in French a "contresens" is a sign that the author have no business talking about serious books or philosophy.

It's like Ayn Rand who believed Kant "critique of pure reason" is about criticism of the scientific method and now a huge part of US authors think the same while never having read Kant.

Virginia’s 23 Democratic electors (Southern) refused to vote for Democratic VP candidate Richard Mentor Johnson due to his open common-law relationship with Julia Chinn, an enslaved woman of mixed race (octoroon). Interracial marriage was illegal under anti-miscegenation laws. They voted for Van Buren (president) but switched VP votes to William Smith (another Democrat), denying Johnson a majority. The Senate elected Johnson anyway.