水

ductchyhon'せんせい Dev at Bosch

[François Chollet @fchollet]

Some observations about the "total" automation of software engineering:

1. There are more software engineers now than in 2025, and demand is growing.

2. Software engineers have never worked harder than they do now.

3. They largely don't write code anymore, agents write ~100% of the code.

4. The bottom line of the companies that employs these engineers and agents (i.e. the terminal purpose of all this code) is typically not budging as a result of AI adoption.

This is why you have to think in terms of systems. Automating one aspect of a system creates its own friction and moves the bottlenecks elsewhere.

[Hassan @nutlope]

Pictionary, but with open source LLMs

[Andrej Karpathy @karpathy]

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.

The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

[anabology @anabology]

I gave Claude another 18 hours.. and I think this one is the best one yet

Macrohard: Windows XP

I'm blown away

[Elon Musk @elonmusk]

Made this into a @Grok video in 20 seconds by long-pressing on the image

[Andrej Karpathy @karpathy]

I attended a vibe coding hackathon recently and used the chance to build a web app (with auth, payments, deploy, etc.). I tinker but I am not a web dev by background, so besides the app, I was very interested in what it's like to vibe code a full web app today. As such, I wrote none of the code directly (Cursor+Claude/o3 did) and I don't really know how the app works, in the conventional sense that I'm used to as an engineer.

The app is called MenuGen, and it is live on https://t.co/bQonQT88t0. Basically I'm often confused about what all the things on a restaurant menu are - e.g. Pâté, Tagine, Cavatappi or Sweetbread (hint it's... not sweet). Enter MenuGen: you take a picture of a menu and it generates images for all the menu items and presents them in a nice list. I find it super useful to get a quick visual sense of the menu.

But the more interesting part for me I thought was the exploration of vibe coding around how easy/hard it is to build and deploy a full web app today if you are not a web developer. So I wrote up the full blog post on my experience here, including some takeaways:
https://t.co/2kkQh0ElgB

Copy pasting just the TLDR:
"Vibe coding menugen was exhilarating and fun escapade as a local demo, but a bit of a painful slog as a deployed, real app. Building a modern app is a bit like assembling IKEA future. There are all these services, docs, API keys, configurations, dev/prod deployments, team and security features, rate limits, pricing tiers... Meanwhile the LLMs have slightly outdated knowledge of everything, they make subtle but critical design mistakes when you watch them closely, and sometimes they hallucinate or gaslight you about solutions. But the most interesting part to me was that I didn't even spend all that much work in the code editor itself. I spent most of it in the browser, moving between tabs and settings and configuring and gluing a monster. All of this work and state is not even accessible or manipulatable by an LLM - how are we supposed to be automating society by 2027 like this?"

See the post for full detail, and maybe give MenuGen a go the next time you're at a restaurant!

[François Chollet @fchollet]

An underappreciated aspect of productivity: momentum. The more stuff you do the easier it becomes to do stuff (literally anything). And inversely.

[Harris Rothaermel @DeveloperHarris]

its happening

[zore @itszore]

this video is fucking hilarious no matter how many times u watch it

[Andrej Karpathy @karpathy]

The killer app of LLMs is Scarlett Johansson. You all thought it was math or something

[Massimo @Rainmaker1973]

This is how an aurora is created

[📹 University of Oslo / Per Byhring]

[Wonder of Science @wonderofscience]

The Sun unleashing a spectacular solar flare and coronal mass ejection, captured by the Solar Dynamics Observatory spacecraft.

[Fascinating @fasc1nate]

The Serama is a tiny breed of chicken that weighs less than 500 grams. https://t.co/JodTUEQIe3

[Nature is Amazing ☘️ @AMAZlNGNATURE]

A 392 year old Greenland Shark in the Arctic Ocean, wandering the ocean since 1627.

[水 @GtxDutch]

loneliness is stronger when night comes

[Vorachat @vorachatMD]

คนไข้บอกว่าอาการ brain fog หลังโควิด เหมือนตอนอกหักเลย
หลับไม่สนิท รู้สึกหดหู่ คิดช้า ไม่มีสมาธิ รู้สึกฉลาดน้อยลง

นี่แนะนำให้ปรับชีวิตใหม่
- ทานแป้งลดลง โปรตีนมากขึ้น
- ออกกำลังกายแบบคาดิโอ 150นาที/w
- นั่งสมาธิ หรือหาหนังสือมาอ���านแบบ deep reading
- พยายามนอนเร็ว เล่นมือถือลดลง

ถ้านอนไม่สำเร็จ ให้มารพ.ปรึกษาแพทย์ค่ะ
การนอนให้ดีเป็นจุดเริ่มต้นที่ดี 😊

[水 @GtxDutch]

@miafranso เท่ดีนะ ไม่เล่นไอจีครับ อะไรงี้ 5555555

[水 @GtxDutch]

หนุ่มหน้าตาดีไม่เล่นไอจี

[François Chollet @fchollet]

My worst nightmare is becoming someone who plays politics, who angles for titles and accolades but never ships anything.