@Polymarket A quarter of Muse users shop through it, at over $200 a basket. Brands spent a century paying for eye-level shelf space. Now the shelf is whatever the agent recommends first.
@StockSavvyShay Tesla aimed for 5,000 Model 3s a week by the end of 2017 and got there in the last week of June 2018. Optimus is targeting 20,000 a week within a year. The line is installed. The ramp is the forecast.
Marc Andreessen thinks robotics could be the biggest industry in the history of the planet, with hundreds of billions of robots that someone has to design and build.
The factory floor is where that gets decided.
Marc Andreessen with Joe Lonsdale on American Optimist, via @linasbeliunas
Demis Hassabis had Gemini 4 Argon build a wizard chess game. Watch the pieces move.
A demo you can see beats a benchmark you have to explain.
🎥 via @demishassabis
@typesfast Malcom McLean's Ideal X sailed from Newark in 1956. Loading loose cargo cost about $5.83 a ton. The container got it under 16 cents. Globalization is mostly that one number.
Every operator I talk to thinks their data is the moat.
David Vélez's Blockbuster story says otherwise. They had the customers, the stores, the rentals. Netflix had the systems and the habit of using them.
Capture first. Then build the culture that acts on it.
Invest Like the Best, via @linasbeliunas
The playbook: price AI per finished task. Budget by workflow, not by seat. Run two budgets. Name an owner for the token P&L. Retire the usage leaderboard. Keep the right to switch.
The winners will know what a finished job costs.
https://t.co/EOXRQ66djp
The AI bubble debate is arguing over the wrong number.
Bears count tokens times price. Bulls count demand. Buyers count what a finished task costs, and companies are only now finding out.
So the budgets are getting owners. Microsoft: "more impact per token." Meta and Microsoft cut back Claude Code. Accenture: $29 a month, the rest billed to a project code.
Every useful input runs the same arc. Perk, then habit, then a line item with an owner.
Cisco sold routers to dot-coms spending venture money in 2000. In spring 2001 it wrote off about $2.2 billion of inventory. Know who's paying your customer's bills.
1% of companies represent 90% of AI spending.
Of that 90%, 80% of this spend are from unprofitable VC backed companies.
So, roughly, $0.70-75 of every dollar of AI spending right now comes from AI companies spending VC investment dollars.
As a result, the revenue quality in AI is currently poor. This happened in previous cycles as well, like cloud when early users of AWS were mostly venture backed startups.
The thing, though, is that before AWS could scale and pull thru GCP and others as legitimate cash machines, there were a few clearing events to sort out these brittle revenues.
This is the extrapolation of Ken’s point. We will need to transition from speculative AI spending to consistent, reliable spend that shows up in public market earnings reports.
This hasn’t happened yet because most of the breathtaking revenue growth comes from LPs investing in VC funds who then send it to startups.