Sam Altman's Algorithm

Hey everyone,

Welcome back to Stocks To Space, where I curate the best ideas, tools and resources I’ve found each week as I explore my curiosities.

There’s a lot today, so buckle up. Reading time: ~8 minutes…

If you find something thought-provoking, forward it to a friend.

IDEAS
Sam Altman's Algorithm

A framework for convincing people to give you what you want, whether you’re pitching an investor for a fundraise or asking the CEO of Microsoft to give you unlimited access to compute to build AGI:

Structuring your entire pitch around that will identify and directly address a person's deepest desire.

That is Sama’s algorithm, a simple principle for persuasion.

(Click here to share this idea on X/Twitter.)

RESEARCH
How Robinhood Makes Money

When Robinhood burst onto the scene more than a decade ago with their revolutionary 0% commission model, everyone wondered:

How do they actually make money? How is 0% commission trading sustainable?

Well, it turns out their model is more than sustainable.

In 2024, Robinhood generated $2.95B in revenue, an increase of 58% year over year. They even posted a $1.4B net profit, their first since 2020.

Here's exactly how Robinhood generates revenue while letting you trade for free:

• Payment for Order Flow (PFOF): This is the key unlock enabling 0% commission trading. Within a PFOF structure, Robinhood routes customer trades to market makers who pay them fractions of a cent per share.

• Interest on Cash: When customer funds sit uninvested in their Robinhood account, Robinhood earns interest.

• Margin Lending: Robinhood charges interest when customers borrow to multiply their investments, creating a lucrative lending operation hidden behind the free trading experience.

• Securities Lending: Robinhood loans out customer shares to short sellers (institutions or hedge funds) for a fee.

• Robinhood Gold: Their $5/month premium subscription offers enhanced features and higher interest rates on uninvested cash, bringing in steady recurring revenue.

Robinhood's business model is fascinating. Its brilliance lies in creating multiple revenue streams that are invisible to most users.

Because of the leverage they’ve built up over a decade, they are now expanding into other financial products, like wealth management, banking, and, of course, AI.

If you are as intrigued as I am by Robinhood's journey from startup to fintech giant, and want to learn more about their rise, the controversies they've navigated, and what founders can learn from their story, let me know by replying to this email.

There is no better candidate than Robinhood’s story for a Stocks To Space deep dive.

If not, just remember that next time you make a "free" trade, nothing in finance is truly free.

INSIGHTS
1 Chart

The bootstrapped AI-powered solo founder is happening

A fascinating shift is happening in startup land that's flying under most people's radar: the rise of the bootstrapped solo founder.

Nearly 40% of all startups on Carta now have a single founder and zero VC funding, nearly double the number from 2017.

This starkly contrasts with the number of VC-backed solo founders, which has barely budged over the same time.

VCs remain reluctant to back individuals, even as technology increasingly enables solo success. The fact is, the startups’ solo founders are building may be less ‘venture-backable.’

What's driving this?

I believe we're seeing AI's early impact as a force multiplier for individual creators.

A solo founder with GPT-4o, o3/o4, Claude, Replit Agent and Lovable can now accomplish what previously required multiple team members.

We're entering an era where ambitious founders can build significant businesses without selling out to VCs or even co-founders.

The ultimate arbitrage opportunity for founders is to use AI leverage to get ahead while the funding ecosystem still operates on outdated team size biases.

Taking a step back, the million-dollar question remains:

Is this the beginning of a permanent shift in company formation, or just a temporary aberration?

My bet is on the former.

1 Post

• Paired well with one of my older pieces.

1 Video

TL;DR

• Start with the problem, not the product.

• Hire for talent & ambition over expertise.

• Look for broken industries.

• Don't compete against the best.

• Great leaders have a mission mindset.

• Optimize for long-term equity over short-term salaries.

(Click here to share this on X/Twitter.)

TOOLS
Deep Research

I've been fascinated by the new generation of AI-powered research tools, which promise to deliver comprehensive analysis at unprecedented speeds.

Think of them as your personal research department, ready to synthesise vast amounts of information into actionable insights without the cost of hiring analysts.

While preparing the Robinhood segment above this past week, I decided to run an experiment.

Why not pit the leading deep research tools against each other in a head-to-head battle to see which delivers the most comprehensive analysis?

My own personal Chatbot Arena, if you will.

Here's what happened:

First, I leveraged Claude to craft a rigorous prompt framework that detailed:

• Context

• Level of Detail

• Evaluation Criteria

• Areas to Explore

• Refinement Instructions

I then fed Claude’s exact prompt to the contenders:

• Perplexity Research

• ChatGPT Deep Research

• Gemini Deep Research

• Grok DeeperSearch

(Seriously, could these companies have been any less creative with their naming?)

When all was said and done, the differences were striking.

While each tool responded quickly, ChatGPT emerged as the clear winner, producing an exhaustively detailed report that:

• Followed my requested structure precisely

• Tagged statements with confidence levels as requested

• Provided detailed citations for every factual claim

• Included quantitative breakdowns with proper context

• Addressed regulatory nuances across markets

• Analyzed competing viewpoints with balance

Despite their impressive capabilities, the others delivered what felt more like executive summaries, lacking the comprehensive depth I needed.

They skimmed the surface where ChatGPT went deep, as the name suggested it should.

The ChatGPT report was so comprehensive that it took nearly a full day to read it completely. It felt more like reading the work of a dedicated financial analyst rather than an AI assistant.

If you're making strategic decisions that require deep context and comprehensive analysis, ChatGPT's Deep Research currently delivers the most value.

The others excel at quick insights, but for the kind of meticulous analysis that drives competitive advantage, ChatGPT is in a league of its own.

THOUGHTS
Quote I’m Pondering

“Frankly, I don't think it's feasible to opt out of learning the skill of applying AI in your craft; you are welcome to try, but I want to be honest I cannot see this working out today, and definitely not tomorrow. Stagnation is almost certain, and stagnation is slow-motion failure. If you're not climbing, you're sliding.”

— Tobi Lutke, CEO of Shopify

(Click here to share this on X/Twitter.)

Was this email forwarded to you? If you liked it, sign up here.

If you loved it, forward it along and share the love.

Thanks for reading,

— Luca

P.S. Markets got me feeling like Larry Summers on All-In…