Venture Capital
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Silicon Valley predicted the 2026 AI crisis perfectly.

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🤖 Anthropic takes the first step toward an IPO

Anthropic confidentially filed a draft S-1 with the SEC, marking the company's first official move toward a public listing.

The filing does not mean an IPO is imminent. Anthropic said any offering will depend on SEC review and market conditions. The company has not disclosed the number of shares or a target valuation.

The filing comes as AI companies attract record investor interest.

Some market observers are already speculating that Anthropic could debut with a valuation above $1.8 trillion, though the company has not provided any guidance.

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Bernie Sanders introduced a bill proposing the government take a 50% stake in the country's largest AI companies, such as Anthropic & OpenAI, to give the public “direct ownership”.

The stakes would be acquired by a “one-time” 50% tax.

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Meanwhile in San Francisco, luxury homes are being sold for OpenAI and Anthropic shares.

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Most business owners do not know their credit card likely comes with purchase protection, extended warranties, and trip insurance they are already paying for.

The bank buries it in 40 pages on purpose.
The perks are real.

The hope is you never read far enough to use them.


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💰 Alphabet plans an $80B raise to fund AI infrastructure

Alphabet announced an $80 billion equity raise as it ramps up spending on data centers, compute capacity, and AI hardware. Berkshire Hathaway will anchor the deal with a $10 billion investment.

The company expects capital expenditures to reach $180–190 billion in 2026 as demand for AI continues to outpace available compute.

The financing includes a $10 billion Berkshire placement, $30 billion in public offerings, and a $40 billion program that will gradually sell shares into the market over time.

The AI race is increasingly becoming a capital race. The companies with the deepest pockets can build the most compute.

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⚡️ Victoria's Secret Shares Jump 50% After Ticker Change

Shares of Victoria's Secret surged nearly 50% in one day after the company changed its stock ticker from VSCO to VSXY.

The lingerie maker's new ticker spells out "very sexy," a playful rebranding move that caught investors' attention.

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📊 Building a stock portfolio is simpler than most people think

If you're investing for 20+ years, putting everything into the S&P 500 isn't necessarily the obvious choice. Valuations remain near historical highs, which could mean future returns look very different from the last two decades.

A different approach is to focus on quality growth companies:

🖱 Revenue growth above 10%

🖱 Returns on capital above 15%

🖱 Strong cash generation

🖱 Durable competitive advantages

🖱 Management teams with a solid track record

A portfolio of 10–15 companies is often enough. Beyond that, diversification benefits start to shrink while the amount of research and monitoring grows quickly.

Position sizing matters just as much as stock selection. Average ideas might deserve 5%, stronger ideas 10%, and only the highest-conviction opportunities should reach 15% or more. Building positions gradually can also reduce timing risk.

The biggest lesson is simple: finding great companies is important. Having the patience to wait for the right price is what separates good returns from mediocre ones.

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🇺🇸 The White House will get early access to the most powerful AI models

President Trump signed an executive order creating a classified government benchmark for advanced AI systems.

AI companies will be able to test new models against the benchmark to determine whether they qualify as frontier AI systems. If they do, developers can voluntarily provide the US government with access up to 30 days before a public release.

The administration says the framework is not a licensing system and does not require approval before launching new models.

As AI becomes more strategically important, governments increasingly want visibility into capabilities before the rest of the market sees them.

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📈 How 8 of the fastest-growing startups evolved

Most startup stories look obvious in hindsight. In reality, many of today's fastest-growing companies started with a very different product and only found their current direction after a major shift.

🖱 Replit started as a browser-based coding environment, then shifted into a vibe coding platform after launching Agent.

🖱 Sierra started by building AI agents for large enterprises, then moved into AI customer service and support automation.

🖱 Granola started as an AI meeting notebook, then became a memory and context layer for workplace AI agents.

🖱 Perplexity started as a Slack bot for answering questions, then evolved into an AI search engine and agent platform.

• Harvey started as an AI assistant for lawyers, then expanded into an enterprise platform for legal teams and large organizations.

🖱 Lovable started as a developer tool that turned prompts into code, then repositioned as a consumer platform for building apps from plain English.

🖱 Freepik started as a search engine and library for design assets, then transformed into a generative AI design platform.

🖱 Mercor started as a small outsourcing operation handling projects worth $500 per week, then became a marketplace for hiring contractors who create training data for AI.

The biggest startups often don't start with the right idea. They find it along the way.

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