in case you need this as well 👉 「Claude For Marketing」claudecode.sg/slides/claude-…
always happy to see Evan in person 🫶
Almost 100 folks registered for the first NERDS meetup with @evanyou in 2 weeks. If you're in Singapore, join us.
NERDS.sg/1
Met @trungvose today, thanks for the Vietnamese snacks !
I am confused about instagram rules. I dont think I did any bad things just sharing life. 😅😅 lost my previous account which I used 10 years could not get it back. Now I have to appeal for this new account which I documented my life a lot. @instagram 😅😅😅 now I feel sad for both of accounts. For the memories I have documented and with timeline
🦋 AnneInContext retweeted
I, along with the rest of the Deno company, am joining Cloudflare!
I'm motivated by abstractions that give leverage at scale. The Cloudflare workers programming model is a hermetic computing abstraction that truly embodies the old Sun Microsystems tagline "The Network Is the Computer". The programming abstractions that Kenton designed really force scalability. If you squint your eyes you might even conceive of it as a distributed high-level operating system.
The only major problem with this distributed operating system is that practically people only use it inside of Cloudflare. Cloudflare is an amazing service for nearly all applications - but there are many situations when you might need it to run elsewhere.
I want to solve this problem and make the Workers programming model the default way you write server-side application code.
The time is ripe for new abstractions too - what software we run and how we run it are changing quickly with AI. The number of agents is exploding and I don't think they all need a Linux VM. A much more lightweight Durable Object would suffice for many applications. I'm super keen to talk to people who want to self-host agents at scale on DOs - msg me!
"The top 1% user is spending $903 per month on AI... The median is spending $25."
a16z's Olivia Moore breaks down who actually pays for AI, under 5% of US consumers, with the top 10% of them driving half the revenue:
"About half of Americans report using AI, and about 25% think they're interacting with AI on close to a daily basis."
"The spending data is much more concentrated."
"Our Yipit panel shows around 4.5% of US consumers are paying a subscription to an AI product. Some other sources say as low as 2% or 2.5%. It is expanding, that's doubled from a year ago."
"Even within that top 4.5% who do spend, the top 10% of those are more than half of the revenue, and the top 1% are 20% of the revenue... The top 10% of users are driving this market."
"We could also see what products they're actually spending on. Probably unsurprisingly, it was mostly developer tools, productivity tools, creative tools, things used to build, make, sell."
@omooretweets
The seventh edition of our Top 100 Consumer AI Apps is here, including a new dimension this time: what consumers are actually paying for.
a16z's Elena Burger sits down with Olivia Moore and Josh Elman to unpack the current state of consumer AI:
The data reveals a striking power-user economy. Only a small share of consumers currently pay for AI, but among those who do, spending is heavily concentrated at the top. Olivia and Josh discuss why developers, creators, and other power users dominate spending today, and why subscriptions may not be the business model that ultimately brings consumer AI to everyone.
They also dig into the rise of personal agents, the different trajectories of ChatGPT, Claude, and Gemini, how ads could reshape AI economics, and the enormous amount of consumer white space still left to build, from shopping and entertainment to social, dating, and marketplaces.
00:56 Inside the 7th edition
05:55 Muse and Instinct's launch numbers
09:14 The privacy wall for personal agents
14:39 The AI spending power law
20:20 Why subscription is the wrong model
23:51 OpenAI's $1B ad run rate
29:21 ChatGPT vs Claude vs Gemini
32:30 Where creative tools still win
45:12 The white space: dating, shopping, entertainment
YouTube: youtu.be/aCvrzhwUxg0
@omooretweets @JoshElman @VirtualElena
you said you wanted to code as antfu? now you can !
Introduce @antfu/skills
It works just like @antfu/eslint-config, an opinionated pack of skills curated from the ecosystem.
Instead of vendoring skills, you get a package-manager-like experience: install packs with their skill deps.
github.com/antfu/skills-pack
🦋 AnneInContext retweeted
She landed us on the moon without
- Coding agents
- Autocomplete
- TypeScript
- CI
- Google
- Web browsers
- Objected oriented programming
- Version control
- Debuggers
- GUIs
- Programming languages
- Compilers
RIP Margaret Hamilton
Time flies fast . Congratulations 🎊
Apparently today also marks 3 years since I joined @voidzerodev :)
It's kind of crazy thinking about how much has happened since then — and somehow we ended up becoming part of @Cloudflare along the way.
More than anything, I'm just really grateful that I get to work with @evanyou and everyone on the team.
I've learned a ridiculous amount from everyone here, and I honestly couldn't have asked for a better group of people to build things with.
Still feels like we're just getting started. Excited to see what we build next!
Replying to @rolldown_rs
@rolldown_rs just crossed 100M weekly downloads🎉
🦋 AnneInContext retweeted
Quick update on Vite's bundled dev mode (aka full-bundle mode, powered by Rolldown)
The whole Vite playground suite now runs under bundled dev, and ~74% of the tests that had gaps now pass.
(1/5)🧵
🦋 AnneInContext retweeted
Jev vs LLM feels like System 1 vs System 2 from Kahneman’s Thinking, Fast and Slow.
@typesafeai’s Jev handles fast, automatic decisions, while LLMs handle slower, deliberate reasoning.
But there’s a third layer I find even more interesting: intuition is compressed reasoning.
Agents can reason deeply today, but what if their past reasoning could become persistent memory and turn into fast intuition tomorrow?
That’s the direction I’m exploring with @waku_agent: a memory layer that lets agents carry what they’ve learned across different harnesses.
Maybe the future path is:
Reasoning → Memory → Intuition.
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
PSA: if you have a @voidzerodev sponsorship on GitHub and saw it cancelled - don't worry. We are in the process of switching our billing method and will re-activate them soon.


























