IRR Driver retweeted
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.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
IRR Driver retweeted
Cheeky Pint is back! Mark Zuckerberg @finkd and Alexandr Wang @alexandr_wang came to the pub to discuss their new frontier model, Muse Wonder.
00:00:24 Muse’s breakout use cases
00:07:28 The model is the product
00:14:35 Muse Wonder
00:24:56 How frontier models are built
00:48:26 Betting $100B
01:07:21 Agentic commerce
01:19:34 OpenRouter
01:20:06 Beyond the smartphone
01:27:00 Funding
01:34:06 Why AI won’t be winner-take-all
01:40:46 Meta Superintelligence Labs (MSL)
02:08:11 Working for Mark Zuckerberg
IRR Driver retweeted
fun interview. we cover:
- story of muse
- why my 19th bday attendees are now all billionaires
- diamond mining vs building skyscrapers
- my 200+ direct reports
Watch the full conversation with @danshipper and Willie Williams on how they built it: youtube.com/watch?v=z7cNbsr3…
IRR Driver retweeted
exiting whoop after 18 months.
kept the strap, ditched the subscription. it now runs fully local on zhoop (my fork of noop). no fluff metrics, my data stays on my phone.
ai killed vendor lock-in.
IRR Driver retweeted
Zuckerberg just made the biggest move no one expected. Meta is now selling AI to businesses.
It's called Meta Enterprise Platform. The full AI stack, Muse Agent, Meta Business Agent, Muse API, Muse Code, packaged for businesses and developers.
Most AI companies are fighting for developers and enterprises. Meta is going after something bigger.
Meta already has hundreds of millions of businesses on its platforms.
WhatsApp, Instagram, Messenger. These aren't social apps anymore. They're how businesses operate.
Think about India.
Millions of small businesses run entirely on WhatsApp. Orders, deliveries, customer support, payments. Their whole operation lives there.
Now they get an AI agent inside the platform they already use. No new tool to learn.
Meta spent $130 billion on AI infrastructure this year.
This is where that money is going. Not just better reels. An operating system for every business too small for enterprise software but big enough to need it.
We believe superintelligence will create significant new opportunities for all people and businesses. Meta already serves billions of people at scale and helps hundreds of millions of businesses reach customers. Today we are starting the next major pillar of our business, Meta Enterprise Platform, to help businesses use AI to grow and transform in new ways as well.
IRR Driver retweeted
I’m slowly cleaning up the suburbs with Muse.
Saw this mess of wires on a pole. Took a picture and asked Muse to contact Verizon to get them cleaned up.
It went to their website and got to work.
There is a 0% chance I would’ve sat in a Verizon support chat over this. I would’ve just been mildly annoyed every time I walked past it for the next five years.
“Someone should do something about that” is now a prompt.
🤝 @alexandr_wang
IRR Driver retweeted
It’s funny, Meta went from having my Instagram and WhatsApp data to now having access to my email, calendar, DoorDash, Amazon and pretty much everything.
In the last 24 hours, it bought me socks, ordered my Whole Foods groceries, booked a cleaning service and got me a burger for dinner.
Meta’s last disclosed North American Facebook ARPU was around $227/year, largely from ads. I suspect it can push that number significantly higher now that it understands not only what I look at, but what I need, what I buy and what I’m planning to do.
Also the much bigger opportunity might be becoming the aggregation layer between me and the entire internet. If Meta can take even a tiny percentage of the commerce it facilitates, or of the money it saves me, this could become enormous!
It already saved me $200 by canceling subscriptions and services I no longer needed. This feels much bigger than better ad targeting. Ads are useful but giving me money back is better imo.
One additional thought: the agent is increasingly making the decisions for me. I knew nothing about that burger place. The agent researched it, told me which burger I should order, and I just said “okay” without giving it much more thought.
Agents are becoming the decision makers in both B2C and B2B. Increasingly, every business will be selling not just to humans, but to their agents.
Everything becomes B2A: business to agents.
IRR Driver retweeted
Our house in Toronto had this fancy glassed wine cellar, but we are not big wine drinkers.
Anyways, it had good climate control so here is my rack cellar.
A historic moment at the #SOTEU address.
European Commission President @vonderleyen opens the door for Canada to become the first associated member of the European Union.
"In short, we want to bring the relationship with Canada to the highest level possible," she said in the presence of Prime Minister @MarkJCarney.
IRR Driver retweeted
TL;DR: Owning assets is no longer optional.
You have about 3 to 4 years to stack wealth and build real distribution.
Once AI takes over half of cognitive work, selling your hours on a laptop won't protect you. In an AI economy, pure salaries get crushed while asset owners capture the entire upside.
Own equity, businesses, or real-world reach before the window shuts.
Anthropic’s Economics team is sharing a new model of how AI might affect economic growth, jobs, wages, and more by 2030.
Explore the scenarios, tell us what you think will happen, and see how your answers compare to more than 10,000 Americans. anthropic.com/institute/econ…
IRR Driver retweeted
This is the MOST asymmetric window I've ever seen in business.
It's honestly hard to comprehend. Never in history have this many categories opened at once, ALL ripe for the taking:
1. Take a boring business doing 20% margins, an accounting firm, an IT shop, a local service company, and swap the human labor for agents until it runs at software margins with customers it already has.
This is the Thrive Holdings model.
2. Build the picks and shovels, the clean API or data source that agents call 1000 times a day, and get paid per call instead of per user.
I call this being in the building blocks business.
3. Buy a sleepy SaaS with real customers and a tired founder, then rebuild it AI native and 10x what it can do while building a media machine along side it.
4. Run a service business that looks like an agency on the outside but is really you plus a team of agents doing the delivery, priced like consulting, delivered like software.
5. Watch what people are still hiring for on Upwork, the "data entry specialist," the "appointment setter," the "research assistant," and build the productized agent that replaces that exact role, then sell it to every company posting the job. Vertical agents are here!
I could keep going forever but you get the point.
Contrary to what a lot of people believe (AI is coming for us, you need to raise venture to compete etc), the opportunity right now is endless.
You don't need to quit your job. Finally, you can build a real startup on the side.
It's starting season.
If you've EVER thought about starting a something of your own, this is the moment to stop thinking about it.
Seasons like this don't last forever.
Start.
IRR Driver retweeted
Google just bought 100 million emails and 500 million Teams chats from a dead airline for $10 million.
Spirit shut down on May 2 with $8.1 billion in debt, and the bankruptcy court is selling everything. JetBlue paid $58.5 million for 22 LaGuardia gate slots. Google paid a sixth of that for the company's entire digital exhaust. Employee records back to 1986. Pricing data on 7.2 billion competitor flights. Booking curves, refund histories, 30 million lines of production code.
Run the per-unit math. 600 million internal messages for $10 million works out to under 2 cents per thousand. Spirit charged $69 for a carry-on.
Why does Google want a budget airline's inbox? Frontier labs have strip-mined the public internet, and the thing models are still worst at is exactly what this dataset contains. Real enterprise work. How a pricing decision actually gets argued out over email. How an ops team handles a grounded fleet in a 2am Teams thread. What production code looks like with all the compromises left in. You can't scrape that. It only exists inside companies, and companies only sell it when they die.
Mercor, the losing bidder at $7.5 million, has been paying individual workers for documents from their old jobs. That is the retail version of this trade. Bankruptcy is the wholesale version.
17,000 employees were laid off in May. Every email they wrote over 34 years was just sold as raw material for the systems built to do their old jobs. The workers got severance. The work sold for $10 million.
IRR Driver retweeted
I think Grok @Bot is a glimpse into the future of personal AI agents.
Here's my new tutorial where I show you how to set up 5 useful bots:
1. An advisor to create and manage your bots
2. A YouTube researcher to find outlier videos
3. An X scout to find viral and funny tweets
4. A digital Marie Kondo to clean up your inbox and save money on paid subscriptions
5. A personal concierge to save money on trips
I also tested a Gamer bot to see if Grok Bot can install and play classic games like Doom, Red Alert, and Commander Keen.
Plus, I discuss the biggest barrier to Grok Bot adoption and whether it can replace ChatGPT as my daily driver.
📌 Watch now: youtu.be/MkVcHbviYOw
GBrain actually works with any AI Harness (Grok Bot, Claude Code, Codex, Hermes Agent, OpenClaw, OpenCode, all work) and any Postgres with pgvector hosted service
This is what it means to truly own your own AI agent's memory and skills.
GBrain bootstraps in Codex or Claude Code: open a new empty folder, paste the bootstrap block from github.com/garrytan/gbrain. It interviews you, builds SOUL.md + 70 skills, and spins a local PGLite brain.
Wire it to your stack by pointing GBrain at Polygres (any Postgres+pgvector works as the engine). Run gbrain serve as MCP on a Nebula virtual computer so your agents get the memory layer. Use Replit to iterate the agent repo or glue code.
GBrain now supports personalized agent generation/onboarding for Codex and Claude Code
It'll generate an agent AI-style SOUL.md and install 70 of my personal agent skills to get you started.
In 12 questions, you get setup with an agent just as smart as my personal OpenClaw
IRR Driver retweeted
This is insane beautiful-ui-five.vercel.app…































