great example of why i didn't even consider applying for openai. think of implications in a country with a racist president

https://x.com/gabrielpeterss4/status/1973120058907041902?s=46

You can now connect Slack to Claude. It can search your workspace channels, DMs, and files/gdocs to provide context for deep work.

You can also connect Claude app to slack, e.g. ask something in the app and claude can read your slack, search info there, etc.

Video below

https://x.com/claudeai/status/1973445694305468597?s=46

🦀 i recommend spending a year with Rust

i don't think i can explain all the reasons why do that in a way that's both short and clear. most likely i'll lose the reader in the middle of the post before i'd get to the point. it is only after some first-hand prolonged experience of learning the Rust way you start getting it.

just trust me on this 😎 go ahead and do yourself a favor

fair warning: first 6mo can be painful, but we have LLMs now that help a lot

haiku 4.5 (just released) is as smart as sonnet 4.0, but it's 2x faster and 3x cheaper. i've been using it in claude code for a while (primarily because of speed) and i can recommend it. i use it more often than sonnet 4.5 and definitely more than opus

https://www.anthropic.com/news/claude-haiku-4-5

Addressing seemingly common misunderstanding.

- Sonnet 4.5 is smarter than Opus 4.1.
- Haiku 4.5 nearly as smart than Sonnet 4.0

how come? Scaling laws suggest that the intelligence of models grows with scale (aka the bitter lesson). We increase training scale all the time, so it is not surprising that a newer model is more intelligent than an older model.

Besides, smaller models are:
- much faster, so you are getting more done
- cheaper, so your quota lasts longer

per aspera ad astra!

Anthropic + NVIDIA + Microsoft

video: https://x.com/anthropicai/status/1990797993281536420?s=46

i started feeling the agi with this model

if you are building frontend, enable the frontend plugin
https://x.com/trq212/status/1993786552233939042?s=46

RIP coding

I started coding approx 26-28 years ago. There were many months that i wrote code every day. It was my main hobby. I no longer write code and I don't think I will.

I still produce a lot of code, but i don't type it myself. I mostly direct agent(s) and review their code

It was fun 🫗🫡

Claude as a Compiler

I often operate on spec files.
- I describe a key idea to Claude and ask it to write a spec file in Markdown
- Claude reads existing files and documents and writes a spec based on my idea
- I review that spec. We iterate on it.
- I ask Claude to write tests that cover the spec 100%. Whether this is actually possible depends on the project, e.g. how easy it is to establish an edit-debug-test loop. These tests serve as the success criteria or a burn down list
- I ask Claude to implement it and to keep working until those tests pass.
- I ask what are the limitations of the solution and how they can be addressed, e.g. is the solution generic. We iterate more, often until it is fully implemented
- Sometimes we leave some tests ignored because the feature is too large to implement in a single change. They serve as documentation of the current limitations

I might or might not read the code, depending on the criticality of the project. I am 70% confident that I'll stop reading code this year and 95% confident this will happen within 2y.

Spec files become the key source files I need to focus on. The executable code is becoming a derivative. The spec files stay in the source control for other Claudes to read.

I wrote this in May 2024, while still at Amazon. This is now our reality, and yet it still feels like a beginning https://xn--r1a.website/nodir_log/59

Now let's generalize "Claude as a Compiler" from above.

What i provide is the least probable but very useful information that is not in the model's probability distribution. The insight. That's the key that the model might be missing. It can do the rest.

In that post I provided key info, from which the model writes a spec. The main purpose of the spec file is for the model to prove it's understanding

here is another. i gave key tokens. claude expanded it into a post

one kind of job that might still be available is generate rare brilliant ideas that model couldn't figure out. and from here we split into categories of universes. in one there is no exponential acceleration - in which this has a chance to be true. and another, where AI eclipses us in the ability to generate brilliant ideas - that's asi. i'm putting more than 50% on the latter because alphago won

The FAANG dream

IDK if people are watching the news but it is becoming increasingly apparent that the FAANG dream is dying, for two reasons:

1. If the trend continues, AI will eclipse humans in intelligence per dollar, so it wouldn't be economically viable to bring immigrants: you'd have to be a genius.

2. The U.S. is turning into a nazi nation, for white people. The latest news is that all immigration visas in 75 countries, including Uzbekistan, were stopped indefinitely today. We also have armed people operating on the streets.

The situation is getting rapidly worse on both dimensions. I am not an expert in these things, but I'd avoid the US for now, unfortunately.

[trigger warning] If you are using ChatGPT 4o, then you should read this article

Update: it might apply to deepseek too, see comments

https://arstechnica.com/tech-policy/2026/01/chatgpt-wrote-goodnight-moon-suicide-lullaby-for-man-who-later-killed-himself/

for those who care about this, second uzbek at anthropic, and third from central asia, afaik

https://www.linkedin.com/posts/shahboz-ibragimov_im-super-stoked-to-announce-that-ive-joined-activity-7417702640584937472-k8pl

A good article on effective agentic coding from Joe Magerramov, Distinguished Engineer at AWS Bedrock

https://blog.joemag.dev/2025/10/the-new-calculus-of-ai-based-coding.html