ozgur

building @ solodot, spark fellow, techno‑precariat

[ozgur @ozgur_back]

https://t.co/QJ5vnK2SVE

[banteg @banteg]

fact check: true btw
another reason not to trust anthropic.

[ozgur @ozgur_back]

time to lock tf in

[Citrini @citrini]

We only write 1-2 primers a year because we want them to be durable. It’s simple to publish something market relevant for 6 months, but our goal is a piece you can return to years later and still derive value.

Our Robotics primer meets that standard.

https://t.co/qPSAXaLgYN

[ozgur @ozgur_back]

https://t.co/9cPuhSGMS9

[ozgur @ozgur_back]

@Etched congrats!
inferencemaxxing

[gabriel @gabriel1]

inference will be the biggest market in the world, intelligence is in infinite demand

etched is bringing the AI Summer

[Max @minordissent]

the singular most important graph that exists if you’re high in trait agreeableness

[Ion Petropoulos @ionpetropoulos]

When you tell a YC partner you wanna build things that scale

[shﾑn @preset_2m3]

Every day i wake up and i channel my life through the OODA loop and I lose and i do it over and over and over and over again and i lose over and over and over again

[signüll @signulll]

i suppose a lot of ppl will find this to be super obvious but the mechanics of competition with respect to behavior & attention are at a somewhat maturity phase.

most interesting though is that one side is going towards infinity (supply) & the other is fixed & finite (time).

it’s like a 50 lane highway having to converge to one lane, imagine the bottleneck that creates.

[ozgur @ozgur_back]

izlenmesi gereken inanılmaz bir konuşma https://t.co/FCyJzSO6RX

[ozgur @ozgur_back]

never kill yourself

[Boris Cherny @bcherny]

As engineering, product, design, DS, etc. melt into a new kind of role, I was reflecting on what roles might look like in the future. For example, when I look at the Claude Code team I see what I think is five archetypes:

1. Prototyper: comes up with brand new ideas; churns out many ideas, most of which don't ship
2. Builder: quickly turns a prototype/idea into production-grade product/infra
3. Sweeper: cleans up the UI, simplifies the code and system, unships, optimizes performance
4. Grower: takes a product that has been built and iterates on it to improve Product-Market Fit
5. Maintainer: owns a mature system to make it secure, reliable, fast, and efficient as it scales

Many people span across 2 roles, and sometimes 3 roles. I also notice that these roles are not really tied to job function -- eg. across Anthropic, some designers match category 1, some 2, some 3; same for engineers, PM, DS.

A healthy team needs a mix of these, depending on the product:

- A product that is new and pre-PMF needs people that are strong at 1+2+3
- A product that is growing and has found PMF needs 2+3+4 and some 5
- A product that has strong PMF needs 3+4+5 and some 2

Maybe product roles of the future will look more like this, and less like the domain-specific roles of today?

[Chubby♨️ @kimmonismus]

The worst-case scenario for the United States is becoming increasingly realistic, and I will briefly explain why.

@quxiaoyin raised many valid points, and I agree with her. First of all:

-China certainly does not place such strong emphasis on open source because it cares so deeply about humanism, but because it is a strategy to attract many users, gain market share, put pressure on US models, and also because the models are increasingly being trained on Huawei hardware (think of DeepSeek 4), allowing China to host the entire stack domestically.

-But the underlying logic is far more important: The United States is still building too few data centers to meet future demand. @ChrisGillett wrote an outstanding analysis on this, which I shared a week ago. In short, based on SemiAnalysis data, demand is greater than what is currently being built in terms of data centers.

-Even more importantly, however, the United States lacks sufficient energy and grid capacity. This is a problem that will become much more severe in the near future. China, by contrast, is addressing the issue through a massive expansion of its energy supply. Solar capacity: in 2025 alone, China installed as much solar capacity as the United States did in 10 to 15 years. China is also building 36 nuclear power plants, significantly more than the United States, and is installing them faster.

-In addition, China is managing to become more independent through Huawei chips, even though the country still lags far behind NVIDIA. But here, China is betting on quantity rather than quality.

In short: China is a real threat in the AI race, and the situation for the United States is becoming increasingly precarious. This is also the main reason why China is to be kept away from SOTA LLMs at all costs, so as not to jeopardize the lead under any circumstances.

[Will Manidis @WillManidis]

subtle point but this appears to be the first de-novo trained model released by USG in any capacity

big moment

[Gergely Orosz @GergelyOrosz]

I talked with a few folks inside Anthropic and I am starting to understand what @karpathy is saying (and what lots of people are misunderstanding)

It's not about Slack, but about a cloud AI, hooked up to ALL internal company systems, that "just works." THIS is the breakthrough

[yung macro 宏观年少传奇 @apralky]

It’s a little surprising that a large cohort seems to consider it highly improbable that both of these can be true:

1. People with meaningful capital ownership in AI labs do recognize that in some ASI limit they might not be treated differently from the rest;

2. But they still prefer to bring about that future than to not, even if they believe it to be a net-bad one, because it makes them multi-trillionaires in the interim.

You're talking about a species that near-universally fails to keep itself from chronic overeating -- what makes you think that we're dealing with decision process so low on time preference that it's going to say no to a gamble which offers: "you get to start farming infinity wealth and status right now, for an ambiguous amount of time, probably multiple years, but afterwards there's some decent probability that you'll end up just as badly off as the average person. And if you say no, all of the same almost certainly still happens except without the part where you get to farm infinity wealth and status."

[Alejandro AO 🤗 @_alejandroao]

introducing tau τ — an educational agent harness that teaches you how to build agent harnesses

i will be publishing tutorials and demos on how to use it to create your own TUIs, harnesses, extensions, etc.

Happy Tau Day!! 🤓

👉 https://t.co/5sWxNtXTZP

[David Senra @davidsenra]

My conversation with @ScottWu46, founder and CEO of @Cognition, the company behind Devin, the first AI software engineer.

0:00 Scott Wu's Obsession With Winning
2:06 Competitive Programming, Games And Finding His People
4:24 Family, Go, And The Roots Of Scott's Competitiveness
8:35 Why Losing Hurts More Than Winning Feels Good
9:38 What Winning With Devin Looks Like
12:55 Devin Today: The AI Software Engineer
13:52 Software As The Human-Computer Interface
18:45 Why AI Progress Is Hard To Intuit
20:39 Thinking About AI From First Principles
22:57 What Happens When Agents Can Work For Months
30:18 The Original Thesis Behind Cognition
31:12 Launching Devin And Handling Criticism
37:17 Finding Product-Market Fit In The Enterprise
42:41 How Cognition Deploys Devin Inside Large Companies
48:34 Measuring ROI Instead Of Token Spend
50:01 Why Cognition Wants To Be Model-Neutral
52:18 Why Focus Lets Startups Beat Giants
57:14 Independence, Acquisitions, And Building A Generational Company
1:00:27 Why Money Is Not The Goal
1:03:42 One Life: Going For It All

Includes paid partnerships.