-24.6
net board stance
what this means
68.36
+4.3% · close 2026-11-06
+5% / +8% / +15%
1m / 3m / 12m
+13%
vs SPY since 2025-08-01
35%
of 52w range · -19.8% off high
2/4
hit rate as primary · vs SPY -7
Where All-In Alpha stands — 1 live idea
| idea | call | play | conviction | contributes | moved yet? | scored in |
|---|---|---|---|---|---|---|
| 🤖 Personal AI agents put the App Store's 30% take and opaque subscription/retail economics on notice POD DISAGREES | ▼ SHORT | adjacent ×0.5 | 49.3 | -24.6 | NOT MOVED YET | 323d |
Where the winds are blowing
NET BOARD STANCE, LAST 60 EPISODES —
rising = the besties are building this position, falling = abandoning it. From the
conviction ledger; an idea counts from birth until its window closes. Dots mark episodes
where this ticker's ideas were actually mentioned; a dashed stretch is silence.
Last mention E294 · silent for 2 episodes.
PRICE VS SPY OVER THE SAME WINDOW, % — did the
talk lead the tape or follow it?
Who's pushing which way
each voice's net push ON THIS TICKER — their most recent stance per idea × that idea's direction ON THIS TICKER × strength, so supporting a bearish idea pushes down, unless this ticker is listed as the other side of it. Not conviction (that lives on the idea); this is direction of travel per person. what w= means
What resolves next
scoring dates for the live ideas holding this ticker — each one turns into a scored result on that date, whether it flatters anyone or not
Track record on NYT
As a PRIMARY play the besties are 2 hit / 1 partial / 1 miss over 4 closed windows — credit 0.62, average vs SPY -7.3. Adjacent plays are listed but never scored.
| idea | call | play | result | return | vs SPY | scored |
|---|---|---|---|---|---|---|
| 📈 Legacy journalism is obsolete - the opinion economy takes the audience | ▼ SHORT | primary | WRONG | -46.8% | -69.3 | 2023-10-14 |
| 📈 The intermediary layer of traditional media is being dismantled | ▼ SHORT | primary | RIGHT | +19.6% | +19.9 | 2022-05-31 |
| 🏛️ Defamation litigation wave hits media balance sheets | ▼ SHORT | adjacent | HALF | +5.0% | -16.8 | 2024-04-21 |
| 🏛️ AI's training data gets a copyright bill - citations, links and licences | ▲ LONG | primary | RIGHT | +116.3% | +35.2 | 2026-01-13 |
| 🤖 Training-data owners (NYT, Reddit, X, YouTube) win 2024 | ▲ LONG | primary | HALF | +12.0% | -15.0 | 2025-01-06 |
| 🏛️ Australia's news code spreads and platforms end up paying publishers | ▲ LONG | adjacent | WRONG | -4.4% | -18.1 | 2022-02-20 |
The tape — what was actually said
every capture on any idea holding NYT, newest first · quotes verbatim, timestamps deep-link into the episode
Amazon has blocked these and subsequently, Grok now will tell you, my Amazon shopping bot says, I can no longer check out for you, but I can put it into your shopping cart, tell me which address, which card you want and I'll tee it all up for you, but I won't hit the buy button. So it's being adjudicated in real time right now and I think that's probably where we wind up.
NI
Nikesh Arora
oppose ×1
▼ on
🤖 Personal AI agents put the App Store's 30% take and opaque subscription/retail economics on notice
E294 · 2026-10-23
▶ 23:11
So I think you see banks saying, do not, I do not allow you to interact with me with your agent period.
You can go run 50 website searches at the exact same time. And you can short circuit the loop because the software's ability to get that data is faster than the human's ability. So now the loop is go check 50 websites instantly, give me a result right away.
But you look at Amazon blocking agents combined with Shopify saying, let's go for it, or Uber and DoorDash are now letting agents go in there and order your burrito or your car. But there's a whole compression of the commerce layer occurring at the same time of the compression of software that Chamath is talking about, which will lead to massive deflationary cost savings and speed.
someone was describing to me that they in Grok Bot said, save me money. And it just kind of like goes through their inbox, it finds all of these different things, and it went and canceled a couple of subscriptions and it changed their phone plan and all of a sudden, they're saving like a few thousand dollars a year.
In fact, SI will eat the internet because there's no reason to basically go looking on a website when you can just ask your question to your highly personalized agent or model, and it's going to give you the answer.
Shopify, Sacks, added API access to all the Shopify stores there. So this seems like maybe Amazon's making a strategic mistake here by not embracing the tech.
The second thing though is really interesting. Things like Grokbot and Muse really put the App Store and its 30 percent rev share on notice. Why? Because all of a sudden, what you do is you force many of these services to exist headlessly, right?
I will guarantee that this will be the beginning of the deals and the deals will go up from here.
I read that and I thought, this is the peak of these deals. These deals will only go down in terms of dollar value from here. And it actually brought me to this point where I was thinking to myself, is it even realistic to believe that patents and copyrights actually exist in five years?
you just can't have a situation where China can train on the entire internet, and our AI models are hamstrung by needing to contract, negotiate contracts with every single website.
I strongly disagree with the idea that AI getting trained is the same as AI replicating copyright material.
I told you about this. We did a licensing deal with OpenAI, we meaning Beast. They paid us, and they're using it for pre-training. It's quite reasonable.
And then Chachipiti and the New York Times should do a deal. And I predict they will do this, or with another language model that's smart enough to do it
if all they're doing is transforming the work, they're doing positional encoding, and then coming up with their own unique work product, this judge said that that is not a violation of copyright. I completely agree with that.
I philosophically disagree with all of your nonsense on this topic. All three of you are wrong. And I'll tell you why. Number one, if information is out in the open internet, I believe it's accessible and it's viewable. And I view an LLM or a web crawler as basically being a human that's reading and can store information in its brain.
This is lossy compression. It is absolutely... I'm now on your page. I hate to say this, Jason. I agree with you. You were right.
I have a prediction here. I think this is all going to wind up like the Napster Spotify case. ... I think that there is a non-zero chance, like it might be 5 or 10 percent, that OpenAI is going to lose the New York Times lawsuit and they're going to lose it hard and there could be injunctions. And I think the settlement might be that these language models, especially the closed ones, are going to have to pay some percentage in a negotiated settlement of their revenue, half, two-thirds, to the content holders. And this could make the content industry have a massive, massive uplift and a massive resurgence.
I'm going to go out even thinner limb and say I largely agree with you. I think it's a bit rich to crawl the open web, hoover up all the data, offer direct substitution for a lot of use cases, because now you start and end with the AI model. It's not even like you link out like Google did. And then you just close off the models for safety reasons. I think if you trained on the open web, your model should be open source.
I think it's for three years is the license and they just did this blanket license for every book. They didn't look at yourself. They didn't look at how desirable it was. It was just like a blanket deal. Everybody gets $2,500 bucks per book for three years. And I think I'm going to just do it just to support proper licensing so that people can start going down this path.
So I think that in order to train a model, you need access to information. And the Internet ain't what it used to be in terms of being a source of information. And so IP is becoming more valuable. You're not, I think everybody by this time expected all the foundational models to have all this healthcare information. But if I'm Mayo Clinic, I'm not giving Microsoft or Google or OpenAI my IP, because that's what brands me. And so there's going to be a lot of money available there.
we can train these models, like training is like reading. And like reading things is, like when something's available to be read, and you've engaged in the right economic thing for reading it, I think that's a kind of a reasonable, fair use thing.
don't try to hold out for money on the training side of things, because we're going to create synthetic data, we're going to do all kinds of other things that are going to mean that no one's particular data is really going to matter. What you should be is on freshness, on brand, on other things
It's pretty crystal clear that their content's behind a paywall. And that's how they make money.
What happens in these content cases is they get settled almost every single time. So, the case law doesn't get codified, they just get settled out of court. If you go look at all the Fair Use cases, they almost never go to the mat. And so, this one will just be settled. It'll just be a question at what price.