Building a team to operate based on your own personal preferences is selfish leadership... or even dictatorship.

There's a very strong "focus culture" which relies on the idea that work is not done in meetings. This is wrong. Progress comes in many forms.

> Building a team to operate based on your own personal preferences is selfish leadership... or even dictatorship.

Is there really anything wrong with that? Most managers manage their teams the way they're used to. Founders build their startups the way they're used to—based on their own experience and mistakes. Founders and managers don't adapt to the team's needs. Instead, they look for a team that will adapt to them.

Is it even possible to build a team and _not_ operate based on own personal preferences?

With AI it feels writing software that is open is less attractive. It's hard to trust OSS made recently b/c you can tell if someone knows what they're doing and even spent any time on quality. Also, often times people don't reach for software others make (unless it's boring and old stuff, in which case this advice doesn't apply.)

IMO types are the main lever you can use other than procedural abstraction. I feel that Haskell gives you both in a way that marries them for maximum constraint-building. Constraints that prevent illogical or illegal programs are the bread and butter of reliable software.

I've been poking at running LLMs in the browser. It feels like we're definitely close (<1 year) to seeing real use cases there.

Ubiquity and coverage of devices is what will take longest. Largely dependent on how well we can shrink models with similar performance and how much we can accelerate mobile devices. This feels like it's but further (<3 years?)

Reading only the abstract: LLMs prefer output of their own generation over humans or even other models.

This is a very good reason to avoid using model-generated data to train future models. We'd be deepening this bias by continuing to do that, essentially forcing society to reshape their output using LLMs to increase engagement. This feels like a form of enshittification that doesn't just touch one product but all of society.

You can get better results faster by just doing step 1.

This is depressing, don't you think? :/

Legit first post I've wanted to upvote in a long time.

This type of thing requires an economic driver to monetize the service.

I'd have a strong inclination to run such software if I knew that I was both helping host repos and getting paid.

I feel like it's not news that a company with (probably) millions of DAU is not able to handle a single case like this one.

At the same time, it's clear that after this happened, Anthropic took action. 3 DAYS AGO! (https://news.ycombinator.com/item?id=47954655)

That's before this comment was made on the issue:

https://github.com/anthropics/claude-code/issues/53262#issue...

I'm surprised Anthropic didn't also say this on the issue. Weird that they wouldn't. It seems to have made for unnecessary bad PR.

It feels to me that Anthropic is less focused on quality, and more focused on PR stunts/flash. My experience with Claude is always "it's pretty and feels cool", where-as codex feels like "solid and boring". I realize I'm probably biased. Am I alone in this thinking?

The timing makes me wonder if this is a direct response to Deepseek V4 having performance comparable to SOTA models.

This was published two months ago. Even though it was at a time that open source models are publishing comparable swe bench scores.