ppeetteerr

Tesla’s move to austin had little effect on california. These people also hide their income so it doesn’t risk much in way of taxes.

As a hiring manager, I approve this message.

Good. Keep spending. Keep advocating.

CEOs are motivated by money and power. They will say anything to get either. If they truly wanted to slow down research, they would spend lobby money on the candidates who could enact laws.

Instead, they are partnering with some of the most disliked companies (x, meta) to further their goals.

There is a real possibility that either something you saw triggered the conversation and/or that you remember the ad because you spoke about it. It’s enough to linger on an ad for the platform to recognize your interest and serve you more ads like it.

Gruber was a good voice in the industry but this article misses the mark in a lot of ways.

A company the size of Anthropic would not voluntarily jeopardize their massive valuation if they didn’t feel the resulting output would maintain a similar level of quality as before. Is there a similar worry that their system prompt, which is injected at the start of every conversation also influences token generation in an artificial way?

If regulation will ruin Claude as a product, market forces will fill the void. There are also a ton of open weight models to choose from. It’s going to be okay.

I hate to be that guy, but I'm not reading a readme written by AI, nor using their tool. You don't care to put in a few hours to describe your project, I'm not going to bother learning about it.

Read through it an I'm curious whether setting the date and cmd on every system prompt call will cause the cache to invalidate.

I guess the cache would only be invalid if the day changed or the root directory, which would technically happen infrequently enough.

Isn't Apple about to license some variation of this from google for on-device AI? Maybe it’s their sales pitch to Apple and then they will lock it down.

Maybe it's my experience, but TPMs were often responsible for coordinating large org-wide or cross-org initiatives. It's prohibitively expensive to have TPMs on anything smaller.

Since engineering with AI is still very technical, I would wager that software engineers would stretch into less technical areas of software development rather than TPMs stretching into technical areas. I only say this as someone with experience with AI and I see how easy it is to write bad code with AI if you're not aware of what it's doing.

Engineers are not going anywhere, they are going to fill the spaces outside of coding that are still critical to shipping new product.

Here is a post that summarizes what I mean: https://substack.com/home/post/p-200064883

Yes, size and performance are not only problems for local LLMs, they are problems for frontier LLM companies like OpenAI and Anthropic. The latter still lose a ton of money on inference and advances in efficient, performant models helps their bottom line.

They are addressed but the core of the thesis is still wrong:

> This is the core problem: our entire evaluation infrastructure is structurally reactive. We measure the system after it has changed. We never predict the change.

That's kind of the point of evals.

The argument in the article is backwards. Evals test the stability and boundaries of a concept. They are not created before the concept has been prototyped (which the author acknowledges).

An eval is not somehow breaking silently due to some new capabilities in an LLM. It wouldn't be a good eval if it did. What it does is steer the LLM towards specific goals. If anything, an argument can be made that they restrict creativity and experimentation by narrowing goals.

If the argument is that evals need to written before some new behavior can be devised, that's incorrect. There are an infinite number of evals that test for things which cannot be done. Only when something has been demonstrated to work in a specific context, can an eval be written.

How does this compare to using Claude Web with connectors to build the same feature?

On a separate note, READMEs written by AI are unpleasant to read. It would be great if they were written by a human for humans.

I applaud the move. It's also a little disingenuous to talk about moral standings when the third opening sentence is "The math hasn’t worked out for a while now." If the numbers were working out, would they continue to turn a blind eye on the privacy tracking?

Too much of code is data transformation. input -> sanitation -> db -> consumer -> api -> client. Business logic defines the shape of that data and some service-level rules but the majority is just shoveling data.

Those are raw numbers. I would look instead at the job changes over total employment numbers. I don't have the numbers but I would wager we have many more people working in tech today (overall) than we did in 2008.

Also, that spike in 21/22 really did a number on people's expectations. The one constant in this industry is its cyclical nature.

Used, yeah

This laptop competes against M2/M3 MacBook Airs. Going to be hard to justify a Neo when the others are so much more powerful.

Wishing the best for all those affected and excited to see many of you start new companies and continue to innovate.

Why anyone is still using X after 2025 is a mystery (I know, it's where everyone is, but the moral implications are wild)

Publishing is more than just authoring. You have research, drafts, edits, source verification, voice, formatting, multiple edits for different platforms and mediums. Each one of those steps could be done by AI. It's not a single-shot process.

Don't let common sense stop you from a good time.

We’re about to see if LLM regress or evolve

That's right, I said TypeScript but yeah, it's v8 under the hood.

Not quite systems programming but this might give you some insight. Swift is memory efficient, and runs stable backend services. I've seen benchmarks showing that it's slightly more performant than typescript but twice as memory efficient (but not as efficient when it comes to memory management compared to Rust, C, and C++).

The other point I've seen is that its string library is slow and very accurate.

Besides that, the C-interop means you have quite a bit of flexibility in leveraging existing libraries.

Nothing particularly insightful other than avoiding messing with previous messages so as not to mess with the cache.

I asked Claude to summarize the article and it was blocked haha. Fortunately, I have the Claude plugin in chrome installed and it used the plugin to read the contents of the page.

Before people in this country can unionize, they have to see their peers and fellows, not as strangers. The structures in this country have put each person against the other in pursuit of wealth.