Kayley

[Brian Cates - Political Columnist & Pundit @drawandstrike]

Guess why someone never shows you this?

[Aziz Sunderji @AzizSunderji]

The financial advantage of owning over renting is much slimmer than most people think.

[Adam Cohen @adambcohen93]

Founder friendly VCs in the 90's

[Joe @electionsjoe]

This may be the funniest image of the entire Trump administration.

[Chamath Palihapitiya @chamath]

A framework to understand how value accrues across the AI stack.

This is a blueprint for understanding what builds AI into its pragmatic parts: what each layer is, where it ends, and where value is accrued. So here’s how you can think about it:

1. Layer 1 - Infrastructure

Before any AI model trains or any robot moves, an industrial foundation must exist. Land, energy grids, cooling systems, critical minerals, and fabrication facilities. Infrastructure is the constraint that all the other layers depend on.

2. Layer 2 - Chips

Transistors that are etched onto silicon wafers using extreme ultraviolet light. This is what allows both physical and digital AI to take an input, process it, and return a predictive output. The more transistors that fit on a chip, the more computation it can perform.

3. Layer 3 - Data

Both digital and physical models train on data. Digital models train on text, code, and images; physical models train on gravity, friction, depth, and sensor streams. The more accurate the data, the more accurate the output.

4. Layer 4 - Models

A model is a system that learns from examples. Feed it enough examples of inputs paired with correct outputs, and it adjusts its internal structure until it can predict correct outputs on inputs it has never seen before.

LLMs represent a specific class trained on text. They learn by processing billions of examples of human language, developing the ability to write, reason, summarize, and generate code.

5. Layer 5 - Execution

This is what lets models take actions on behalf of users. The execution layer lets models pursue objectives through sequential action: observing the environment, reasoning about the next step, acting, and looping until the goal is reached.

6. Layer 6 - Application

All of the AI Stack’s revenue originates at the application layer, then goes to the layers below.

Every dollar paid for AI is paid for an outcome, a task completed, and an answer delivered. Nobody wants H100s for their own sake. They want H100s because someone, somewhere, wants to run an application.

These are the different layers that make up the entire ecosystem of AI.

We did a full study on the AI stack. If you want to read about it, head over to my Substack (https://t.co/uaxeJk63aO)

[ChatGPT @ChatGPT]

A preview for Pro users: a new personal finance experience in ChatGPT.

Pro users in the U.S. can securely connect financial accounts, see where their money is going, and ask questions based on the information they choose to connect.

Your full financial picture, now in ChatGPT.

[Charlie Bilello @charliebilello]

13.1% of credit card balances in the US are now 90+ days delinquent, the highest since 2011.

10.3% of student loan balances are now 90+ days delinquent, the highest since 2020.

5.6% of auto loan balances are now 90+ days delinquent, the highest level on record.

[The Kobeissi Letter @KobeissiLetter]

https://t.co/c0j31oiWSm

[Quant Science @quantscience_]

A Bloomberg Terminal costs $30,000 a year.

Someone just built one for free.

In minutes.

With no local setup.

[Andrew Curran @AndrewCurran_]

Striking image from the new Anthropic labor market impact report.

[Michael Saylor @saylor]

100% of distributions paid by Strategy during 2025 on its Digital Credit instruments were treated as a nontaxable Return of Capital (ROC), to the extent of a shareholder's tax basis, for U.S. federal income tax purposes. $STRC https://t.co/mfIuKGPvKM

[Michael Saylor @saylor]

HODL

[Plan C @TheRealPlanC]

Bitcoin Statistical Framework

*Not Financial Advice*

[Sherlock | DeFi Researcher @Sherlockwhale]

Bitcoin bear market drawdowns have a clear pattern:

2011: -93%

2015: -86%

2018: -84%

2022: -77%

Every cycle, the drawdown gets smaller as the market matures.

Following this trend, the 2026 bottom should be around -70% from the $126K ATH. That puts us at $38K.

Good luck buying your bottom at $69K, $60K and $50K. I’ll see you at $38K.

[Max Crypto @MaxCrypto]

Bitcoin has NEVER dropped below its electric cost.

Current Electric Cost = $58,740

[Jackson @macrojack21]

Bitcoin Hall of Fame drawdown days:

June 2011: -99%
April 2013: -43%
December 2013: -50%
December 2017: -33%
March 2020: -50%
May 2021: -30%
November 2022: -14%
February 2026: -14%

today joins the list

and every single one of those days was the best buying opportunity of the next cycle

either this is major cope or you will be rewarded for your conviction, carry on! 🫡

[Charlie Bilello @charliebilello]

Bitcoin is now down 48% from its peak last October, its biggest drawdown since 2022. $BTC

[💗 @JustinChanges_]

This is what 2016 sounds like

[tumblr @tumblr]

welcome back #2016

[Arthur MacWaters @ArthurMacwaters]

California's wealth tax will follow the same pattern as every other tax:

1. target "just the rich"

2. set a precedent

3. expand to everyone else

Except this tax is even more corrupt because it allows the state to seize *assets* not just income

In 1913, only the 1% paid income tax, now everyone does.

This will destroy California's innovation, and backfire on the people voting for it.

True Bolshevik move