Friedberg
Does his own confidence mean anything?
the same scored calls, split by how hard he was pushing at the mention that set his final stance. If credit rises with strength, his table-pounding carries information and you should weight it. If it's flat or inverted, his confidence is noise — treat a ×3 like a ×1. Cells under 5 calls are provisional and get no weight in the replay.
| he was | calls | credit | right/half/wrong | avg vs SPY | read |
|---|---|---|---|---|---|
| ×3 table-pounding | 97 | 0.39 | 29/18/50 | -16% | worse than coin flip |
| ×2 stated with reasoning | 239 | 0.48 | 96/38/105 | -8% | coin flip |
| ×1 offhand aside | 20 | 0.45 | 7/4/9 | -9% | coin flip |
Which kind of claim to trust
by the tier of the mention that set his final stance — a dated prediction is a different animal from a passing lean, and they don't have to score alike
| tier | calls | credit | right/half/wrong | avg vs SPY |
|---|---|---|---|---|
| annual_prediction | 2 | 0.0 prov. | 0/0/2 | -25% |
| explicit_prediction | 228 | 0.46 | 84/42/102 | -9% |
| positioning | 6 | 0.5 | 3/0/3 | +5% |
| sentiment | 120 | 0.45 | 45/18/57 | -11% |
What he's actually good at
his row of the scoreboard — these are his scored record by category, unlocked at n ≥ 5 resolved calls. Track record only — it does not weight his mentions or move any conviction.
Live book — 40 positions
his latest stance on every ACTIVE idea. Expression = what he is effectively long or short: supporting a bearish idea is a SHORT, opposing one is a LONG.
Where his book points
net push per primary instrument across his live stances — conviction × his agreement × the idea's direction. This is his implied book, not a position he disclosed.
Where he's out on a limb
the differentiated part of his book — nobody else has taken a regular stance, or the rest of the table is on the other side. High information either way: these are the calls that make his record, and the ones with no cross-voice check on them.
Best and worst calls
How he argues
Latest from him
And then the one big beautiful bill passed in July of 2025, which had some entitlement cost reductions, but all of the fundamental spending of the government had not been reduced. And we're still running a $7 trillion a year government budget with a $2 trillion a year deficit. So I don't think Congress was ever on board.
And as we talked about a couple weeks ago, I think the bond market will tell you where they think that's headed. Because if we continue this $2 trillion your deficit spending, things are going to remain expensive, they're going to get worse.
I still think, I could be wrong, but I still think we end up in a place where the government says we want to regulate compute.
I think the data centers end up being treated like utilities in the future. And I do think that the government are going to try and move down this path.
So if you just say, hey, look, Anthropics customers that could spend $100,000 or more, and have it be less than 1% of their total spend, the addressable customer base is about a million customers. So they're only, call it 1% of total customer penetration potential.
But generally speaking, if AI is delivering value to the customers, I think this shows that there really is true productivity arising from AI, that across the whole value chain, there is such margin to be had, so much value being created, all the way through to the customers
So I just thought like to me, it was so striking how early we are, but also how incredibly profitable everyone is, which indicates there's quite a bit of productivity being produced across the whole value stack.
And then that gets sold to SpaceX, and then SpaceX turns around, and they're making, you know, an 83% margin on that chip spend because they're kind of looking at a five-year depreciation. So they spent $10 billion on Colossus One, five-year life, $2 billion a year depreciation. And so that's kind of the cost per year, but then they're making $1.25 billion a month on Colossus.
I've talked a lot about moving to open source, and we have our own cluster installed with our own kind of open source now.
But I think what Claude is showing is that they have such a high margin. They actually have good elasticity on pricing. So they could push price down, and you could start to see them start to segment the market a little bit, where they could start to be more competitive, perhaps, with cheaper tokens for cheaper, easier tasks, and then premium tasks charge a higher price for intelligence, and start to stratify the value of the intelligence that they're providing by changing the price points.
I think that you're going to end up seeing compute get regulated in the future, where compute capacity is going to be assigned by government, and they're going to pass laws to try and do that post-production, that is, like, meaning they're not going to control the chips. They're going to control the actual compute layer, and they're going to determine who's going to get access to what amount of compute.
The governments aren't going to want to let that happen. So they're going to try and stop the data centers
When I say it's complicated, I think there's a story you can build in the Cloud business that shows the next couple of years of really progressive growth in that business.
As some people have pointed out, this may largely be driven by a change in the pricing algorithm for ads and how Google is now, in some cases, over earning for those clicks. And over time, advertisers will see that, they'll experience that, they'll reduce spend, they'll attrit some dollars, and it won't look as good of a business.
So it's a really hard question of what do we want to be at Google right now? I don't think that they have a great answer, and I don't think it came across well in the earnings report.