gentl ◎

[pbit @0xPBIT]

*taps sign*

[Akshay BD @akshaybd]

on the tokenization supercycle

imagine discovering youtube in 2010 and thinking: great, american tv shows can now be distributed globally.

you’d be right. but you’d miss the point.

the real 1000x was that youtube created an entirely new class of global-native content that traditional tv could never compete with (ie., medium is the message)

tokenization will do the same to capital markets

it won’t just make american equities easier to buy. it will take high-quality, under-distributed companies around the world and violently reprice them.

the subtler point is: distribution is valuation.

distribution was always one of the great moats of US capital markets.

and that monopoly has now met its final boss: internet-scale distribution of any stock in the world to anyone with a smartphone.

imagine every public company on earth were listed on the NYSE, and every person on earth had robinhood installed

do you think today’s relative valuations would survive?

that is the multi-trillion dollar question

[Michael Mauboussin @mjmauboussin]

We recently (re)launched a number of websites. I will point out some features hat may be fun and useful. Thanks to @pjmauboussin for leading this effort!

[Silicon Data @Silicon_Data]

Our LLM Token index continues to decline while the debate over open vs closed model rages on. So we decided to take a closer look at how closed and open models respectively contributed. Interestingly, we are seeing some convergence btwn them.

The effective prices paid for proprietary models have decreased sharply over the last few weeks as OpenAI releases powerful frontier models at lower prices. Open models otoh have in fact seen their effective prices increase as more powerful near-frontier Chinese models like GLM 5.2 and Kimi K3 are released and served at higher prices.

Overall, this should be unsurprising. Econ 101: competition is up and prices are down. This is good for consumer and enterprise users of AI (agents) and promotes much wider and faster AI adoption.

[James @Darpinian]

@SebastienBubeck

[ℏεsam @Hesamation]

Anthropic in 2037 after finding out your grandma has a handwritten diary that they didn’t scan and burn

[Arnaud Bertrand @RnaudBertrand]

Eric Schmidt saying the quiet part out loud: "What I don't like about [China's AI] is that it's all open source which means it's largely uncontrolled and not controlled in any way by us."

He adds, "if that makes you feel any better," that only 2 or 3 countries can be independent AI powers.

In other words, it's all about hegemony: the ideal scenario is a world where AI is controlled by the US - and the fewer countries that can resist that, the better.

Src for the video: https://t.co/Gk5iAMtBqa

[gentl ◎ @Gen7le_]

@typesfast His shares are locked

[gentl ◎ @Gen7le_]

@dampedspring Do you think they will issue $STRC below par if it doesn’t recover or keep increasing the dividend rate?

[gentl ◎ @Gen7le_]

@phtevenstrong @Schlagonia so may red flags - this is not going to end well.

[gentl ◎ @Gen7le_]

@ArchitectIncome

[Matt Stockton @mstockton]

Agree.

You can get *incredibly* far with

- A well structured filesystem of markdowns
- Integrated tools for the model to use these files (grep, etc)
- Some specialized representations of that raw data (eg embeddings)
- Some specialized tools for the model that can use the data (eg custom tools you create for your specific use-case that the model can use)
- A well-designed feedback loop that incrementally updates all of the above things (eg learn something new? Write that to the file system. Or did a trace indicate a tool wasn’t performing well? Update the tool)

I guess you could build a ‘product’ around this. But this is essentially just what good emergent compound engineering / agentic engineering looks like.

We’re still early though because most people have no clue how to actually do it right yet

[Sentora @SentoraHQ]

1/ Kelp's rsETH bridge was drained for $292M on Apr 18. Aave and other lending markets saw heavy withdrawals as users assessed contagion risk.

But markets won't tell you when stress actually reaches the system. These 4 metrics will👇

[plur daddy @plur_daddy]

What actually makes the stock market go up and down?

I was chatting with friends who were frustrated with the market's resilience despite what they viewed as adverse datapoints. There has been tremendous confusion over the market's recent action, and in an attempt to organize my own thoughts about it, I went through the exercise of breaking it down to its underlying drivers.

At the most foundational level, equities are obviously driven by earnings times multiples.

Earnings are straightforward and driven by factors such as broader economic conditions and the performance of the underlying business.

Multiples are more complex to unpack but I posit they are a function of liquidity conditions + flows.

Liquidity conditions are driven by central banks, fiscal stimulus, the movement of liquidity between the real economy and financial assets (the demand for liquidity, see my pinned post), market-based elements (such as DXY and the MOVE index), market plumbing, and other factors.

Flows can be broken down between passive and discretionary flows. The boom in passive flows have been one of the biggest changes in the market during my lifetime, and have radically changed the way the indices trade.

If you look back at market history, you will see that significant declines in the indices were much more common in the past. Part of that comes from the will of the free market once being more dominant, and since the GFC, factors such as the Fed put and direct government management of the market becoming a greater force. The reality is that the stock market has become the economy, and the government has a massive incentive to find ways to manage it higher.

The other main change has been passive flows. Today true passive flows like 401ks are roughly $2-3bn in flows per day on average, while corporate buybacks are another $2-3bn per day (outside of the blackout window). This is an incredible tailwind that shifts the odds of market performance towards being long, and this has correspondingly affected market participant behavior significantly. Ironically, the least sophisticated normies seem to have absorbed this lesson to the greatest degree (perma long index).

So once you factor in these market tailwinds, it takes a greater proportion of discretionary flows to make the market go down. Discretionary flows are driven by psychology. Yet this psychology is also heavily influenced by the passive flows, since they make the index a comfy hold.

You can argue this is like the bell curve meme, where the left curve simplistically believes stocks only go up, while the right curve understands passive and the reflexive impact of those flows on psychology as synergistically driving an environment where it is +EV to staying long most of the time.

I am saying this partially in jest, and personally find it difficult to stay perma long equities, despite understanding these dynamics intellectually. So this is a reminder for myself as much as it is sharing this view with you all.

What drives psychology? Greed and fear.

Yet more so than greed, what seems to be driving the market currently is fear, but not fear of the potential economic impact of the war and shortages caused by an extended blockade of the Strait of Hormuz. No, the real fear is of being sidelined through a painful rally like last year. That incident deeply imprinted market participants.

We did have some real fear of the blockade, but at the first hint of Trump showing a willingness to deal, psychology firmly shifted over to fear of being sidelined.

The reality is that the market is allowing itself to be trained, like a snake charmer with a king cobra. The market is believing more and more in Trump's ability to jawbone the market higher, and as people throw in the towel and stop fighting it, it becomes a progressively more powerful force. It's memetic consensus at its finest. Everyone agrees that Trump can manipulate the market up, and because they believe it, the markets respond accordingly.

Now with the market having gotten over its prior fear of Hormuz and the war, I question whether going back to the prior state of play pre-negotiations, would have the same ability to drive fear. The market has become de-sensitized and would require much greater intensity to get back to the same level. We saw the same thing with tariffs and Covid once the initial fever broke.

Yet despite everything I've just said, I'm having trouble being balls long here. So I have been gradually buying favored single stocks and trying to reduce the number of decisions I'm making.

I often find commodities easier to trade than equity indices because they are a pure distillation of supply and demand. In commodities you can get a trending market when there is a clear supply shortage and inelastic buyers, and these conditions can persist for an extended period of time. The game becomes more about finding hidden sources of demand and supply, and understanding how they are impacted at various price levels. When a commodity market doesn't do what you expect, it always boils down to misunderstanding the actual levels of supply and demand, and the embedded reaction functions.

However I don't see many home runs in commodities at the moment. Usually great opportunities only come around a couple times a year at best. So in the meantime I believe that grinding out single stocks is the best place to play.

[Garry Tan @garrytan]

https://t.co/EVPCod6rxu

[fabiano.sol @FabianoSolana]

Drift had a 2/5 multisig with 0 timelock

$280M gone...

I checked other defi protocols on Solana:

- Jupiter Lend: 4/7 (with 12h timelock)
- Kamino: 5/10 (with 12h timelock)
- Loopscale: 3/5
- Solstice: 3/5 (with 1d timelock)
- Exponent: 2/3

[Pentamerus @pentamerushq]

We built a hedge fund entirely on AI.

[KASM @KASM_Capital]

$SPY ripped 3% today. Most people saw the move. Almost nobody understood why.

It was a gamma squeeze — and you could see it coming hours before it happened. Here’s how.

[EndGame Macro @onechancefreedm]

When Oil Becomes A Macro Wrecking Ball

Oil behaves differently from most assets during conflict because demand does not fall immediately just because price rises. People still need fuel to drive, ship goods, fly planes, run factories, and move food. That is why even a relatively small disruption in physical flows can create a much larger move in price.

Why This Matters More Than The Headline

The first move is inflationary. Higher crude pushes up gasoline, diesel, freight, chemicals, plastics, fertilizers, airline costs, and a long list of consumer goods. Households pay more just to maintain the same lifestyle. Businesses face higher input costs before they can raise prices enough to protect margins. That is the first squeeze.

Then the second squeeze begins. Consumers start cutting discretionary spending to cover essentials. Companies see volume weaken. Hiring slows. Credit quality worsens. Confidence falls. Banks get more cautious. In other words, the same oil spike that first looks inflationary can later become deflationary because it helps break demand.

That is the part people miss. Oil shocks often arrive as inflation and leave as recession.

What History Usually Shows

The pattern has repeated before.

In 1973 to 1974, oil became a geopolitical weapon and helped intensify stagflation. In 1979 to 1980, another major oil shock fed inflation and forced a much harsher policy response. In 1990 to 1991, the Gulf War spike hit confidence and growth, though it was shorter lived. In 2007 to 2008, oil surged into an already fragile economy, squeezed consumers and transport heavy industries, and then collapsed once the broader system cracked.

That sequence matters. Oil spikes do not always cause recessions by themselves, but they often accelerate weakness that was already there. They expose fragility. They pressure central banks. They make policy mistakes more likely.

The Policy Trap

This is where it gets dangerous.

When oil spikes, central banks cannot easily look through it if the move is large and persistent. Headline inflation rises. Inflation expectations can become less stable. But if officials stay tight to fight the inflation impulse, they risk making the growth slowdown worse.

That is why sustained high oil is so destabilizing. It is not just a price issue. It is a policy trap.

My Take

If this is persistent and lasts longer than people expect, oil stops being a geopolitical headline and starts becoming a macro tax.

First comes the inflation shock. Then comes the margin squeeze. Then comes weaker demand, softer labor conditions, credit deterioration, and rising recession risk. If the economy finally buckles, oil can fall hard later not because the world is healthy again, but because demand has been damaged enough to break the spike.

So the real lesson of this chart is simple. A vertical oil move is not just about energy. It is often the beginning of a much bigger sequence where inflation rises first, growth breaks second, and deflationary pressure shows up only after the economic damage has already been done.

[COMBATE |���🇷 @upholdreality]

🇨🇳 Prof. Zhang Weiwei breaks down why China isn't sweating the Middle East energy crisis -- and why Germany's green energy gamble backfired spectacularly.

Key points:

- China is 85% energy self-sufficient thanks to long-term planning

- Coal (54%), renewables (19%), and fossil imports (27%) -- a diversified mix

- Germany blew up its world-class coal plants, shut down nuclear, and now has a 30% energy shortfall. German companies are fleeing to China.

- South Korea and Vietnam are already struggling with fuel shortages. China? No problems yet.

- On Middle East diplomacy: "Be friends with everyone, but keep a clear head -- know who's who. Which ones are true friends, which are fake friends, and which will stab you in the back."

- Calls the US-Israel attack on Iran "strategic deception" -- they were still negotiating in Geneva two days before the strike

- "Anything you sign with Trump, expect him to disavow it the very next day"