As an aside, recently I wanted to refresh my gaming PC, but the price shock and general lack of availability of buying components individually made it seem hardly worth it, so I just kept deferring the project.

Then, mostly by chance, I saw that my local Microcenter had some pre-builts for sale, and I ended up picking one up for <$5k that had "best in slot" components across the board, including a 5090 and even a high-end power supply.

The last time I built a gaming PC was upwards of a decade ago, and at that time the prevailing wisdom was to never buy a pre-built unless you had a massive amount of disposable income and couldn't spare even just one weekend to dedicate to a hobby project that could benefit you for years. Now, it was absolutely a no-brainer.

> I ended up picking one up for <$5k

I'm struggling to put this in context. For comparison, what was your budget for refreshing the pc you had? Were the planned upgrades going to exceed $5k at current prices? Or is the situation that a pre-build machine with far better components was now only marginally more?

Or is it that pre-built gaming PCs have stopped being a joke? I had the experience building a bicycle: I was certain I was taking the frugal path sourcing each component individually and putting it together myself. At the end I was horrified to realize I spent far more than a new bike with superior components. It was pointed out that bicycle makers are buying by the pallet and will beat diy every time — so long as they're building something I want to buy.

I did the exact same thing during Covid, the prebuilt ended up being ~20% cheaper than buying the individual components (I needed a full upgrade). Maybe a little less since I could have reused my case.

> and at that time the prevailing wisdom was to never buy a pre-built

That's still the case, and always will be — with a pre-built you're at the very least paying for someone to assemble it for you, so it's always going to be more expensive as a baseline.

Beyond that, the chance they've chosen good components and haven't tried to screw you over on less flashy ones like the motherboard and power supply is low.

That's not to say it's literally impossible to ever find a good deal. You very well might have. Doesn't change anything though.

> with a pre-built you're at the very least paying for someone to assemble it for you, so it's always going to be more expensive as a baseline

Except isn't it possible that pre-built companies actually get better deals on hardware bought in bulk, and therefore could offset the labor costs with cheaper materials?

I believe this is exactly what's going on -- they're buying parts in bulk, often months in advance, and locking in deals that a single consumer can't easily go get on the open market right now.

Hardware pricing and availabilty pre-COVID was pretty predictable and stable, which meant the consumer could extract a meaningful cost advantage if they were willing to do the relatively modest amount of work of sourcing components individually and personally assembling the build. Right now, though, some places like Microcenter appear to have a cost advantage that fundamentally relies on market and pricing instability and can only be achieved through deeper integration with the supply chain and bulk purchasing in advance -- something a retailer like Microcenter can do, but I personally cannot.

I don't completely agree. Estimation is nontrivial, but not necessarily a random guess. Teams of human engineers have been doing this for decades -- not always with great success, but better than random. Deciding whether to put an intern or your best staff engineer on a problem is a challenge known to any engineering manager and TPM.

or tech lead. or whoever. the point is, someone has to do the sizing. I think applying an underpowered agent to a task of unknown size is about as good as getting the intern to do it.

Even EMs and TPMs are assigning people based on their previous experience, which generally boils down to "i've seen this task before and I know what's involved," "this task is small, and I know what's involved," or "this task is too big and needs to be understood better."

This take is out-of-date by months (which is an eternity in this space). Codex today has caught up and is very much on par with CC.

> Look at popular projects -- a few minutes after an issue is filed they have sometimes 10+ patches submitted. All generating PRs and forks and all the things.

I think this is a really important point that is getting overlooked in most conversations about GitHub's reliability lately.

GitHub was not designed or architected for a world where millions of AI coding agents can trivially generate huge volumes of commits and PRs. This alone is such a huge spike and change in user behavior that it wouldn't be unreasonable to expect even a very well-architected site to struggle with reliability. For GitHub, N 9s of availability pre-AI simply does not mean the same thing as N 9s of availability post-AI. Those are two completely different levels of difficulty, even when N is the same.

Not even talking about how useless it is to create tens of PRs to solve the same issue.

But GitHub karma botting is a thing now.

Remember those elitist ppl who removed answers on stackoverflow coz their answer is better with 90000 answers?

Yup, now they are on GitHub farming karma with bots.

yeah this is indeed a good insight. Back in the days, who would expect so many bots to "review" code and leave overly verbose comments under every PR in a popular repo?

I feel like it's pretty easy to predict what OpenAI is trying to do. They want their codex agent integrated directly into the most popular, foundational tooling for one of the world's most used and most influential programming languages. And, vice versa, they probably want to be able to ensure that tooling remains well-maintained so it stays on top and continues to integrate well with their agent. They want codex to become the "default" coding agent by making it the one integrated into popular open source software.

This makes much more sense as an zoom-buys-keybase style acquihire. I bet within a month the astral devs will be on new projects.

Bundling codex with uv isnt going to meaningfully affect the number of people using it. It doesnt increase the switching costs or anything.

This sounds like grief and depression to me. You're struggling because you're still mentally filtering everything you do through another person who is no longer part of your life. You must learn to do things for you, not for someone else. You may find that some things you thought you enjoyed you actually were only doing for someone else. Likewise, you may discover that what you want do purely for yourself is different from what you might expect or predict.

Time will heal some of this naturally. But the #1 recommendation I would always make to anyone in this situation is to pursue exercise. Weightlifting, hiking, etc., generate rapidly compounding results across multiple dimensions of your life and also often generate some of the most authentic social experiences you can find as a 30+ year old adult.

Same here. The initial version of WSL back in the day could certainly be rough, but modern WSL2 seems totally fine to me. It is the key ingredient that allows me to have one workstation that can do "everything".

I'm surprised people still think this. Google has the strongest position of any company in the world on AI. They have expertise and capability across the entire stack from chips to data centers to fundamental research to frontier models. Just because they weren't first-to-market with a chatbot doesn't mean they almost lost or made some terrible durable blunder.

That's about Google, though. The picture about Sundar specifically is harder to evaluate. The pessimistic take is that Google had that position already and Sundar failed to proactively lead through a fundamental product shift, forcing the company onto the defensive for some time. The optimistic take is that Sundar, having occupied the top spot since 2015, prioritized investments in the company's overall technology development, then successfully executed a rapid product pivot when the market changed, securing a dominant position in both research and product that nobody else can compete with long-term.

All of Google's advantages in AI are despite Sundar Pichai's leadership, not because of it.

That's not clear to me. He's been in charge for over a decade, and the company he's in charge of has the most dominant position in AI in the world.

People give him way too many breaks, he's a money manager. He was asleep at the wheel when OpenAI absolutely steamrolled them, even though they very easily could have won that race.