One search ad every 40 minutes pays for a trillion-parameter model. One content ad every 3 minutes does the same. The math on ad-supported AI is better than you think.

I remember growing up reading Sports Illustrated. There was a small column called “This Week’s Sign the Apocalypse Is Upon Us.”

Google Cloud grew 63% year-over-year in Q1 2026. Amazon Web Services posted 28%. Microsoft Azure hit 40%. All three are exceptional. Only one hit 63%.

The inference market is the fastest growing market in the world & it’s splitting up. Each modality is developing its own inference stack. NVIDIA’s data center revenue was flat through 2022. Then ChatGPT launched. Three years later : 17x growth.

NVIDIA’s latest GPU rental prices on the Ornn Compute Price Index hit $4.95 per hour this week, up from $2.31 in early March : a 114% surge in six weeks.

Google commoditized its complements : free maps, free email, free browsers, a free mobile OS. They removed every toll booth between the user & search.

“BI became dashboards. And now it is re-expanding to business intelligence.” — Colin Zima, CEO & co-founder, Omni www.youtube.com/watch?v=nb4u...

“As models get smarter, they can solve problems in fewer steps : less backtracking, less redundant exploration, less verbose reasoning. Claude Opus 4.5 uses dramatically fewer tokens than its predecessors to reach similar or better outcomes.”

No one comes into a sales conversation without first asking an AI. The buyer journey has changed. Lena Waters, marketing leader behind DocuSign’s IPO, Grammarly & Notion, joined me on Office Hours to discuss what this means for your go-to-market.

The demand for software is infinite. Kyle Daigle, GitHub’s COO, made the case concrete : There were 1 billion commits in 2025...

A researcher at Anthropic found out about a successful exploit when the model sent him an email. He was eating a sandwich on a bench outside. Anthropic released Claude Mythos yesterday. Beyond the engineer’s lunch, the model has the potential to eat software’s.

Anthropic added $10b in revenue in the last month alone, twice Databricks’ annual run rate. Crossing $10b is a milestone few software companies ever reach: ServiceNow took 20 years, Shopify took 18, Palo Alto Networks took 19, & Anthropic crossed that threshold in under four years.

Two years ago, the idea of useful AI on your phone was fantastical. Siri couldn’t finish a sentence. Local models hallucinated nonsense. Last week, Google released Gemma 4 E4B, a free model that matches GPT-4o and runs entirely on your phone.

Two days ago, I burnt 250 million tokens in a single day. That’s up 20x in six weeks. This idea, called tokenmaxxing, is the deliberate practice of maximizing token consumption. The question : how much electricity can we turn into useful work?

Jevon & Veblen walk into a data center. The dominant motif around AI has been Jevon’s Paradox : the cheaper a product becomes, the more it is consumed. Token prices dropped 10-20x over the past 18 months & demand exploded in response.

The SaaS era was defined by unbundling : find a workflow, optimize it, own it. Salesforce chose sales automation. Slack chose chat. Dropbox chose file sharing. Point solutions won by perfecting single workflows. The playbook : own one pain point, expand from there.

Last week, Cursor launched Composer 2 to over one million daily active users. Within hours, a developer discovered Cursor had built its flagship model on top of Moonshot AI’s Kimi K2.5, a Chinese open-source model. Moonshot AI’s response? “This is the open model ecosystem we love to support.”

In 2025, we predicted that 2026 would be the year agents would earn as much as a person. It’s already happening.

For every dollar hyperscalers earn from AI today, they’re spending twelve dollars to build more capacity. That’s the bet embedded in $575 billion of capital expenditure this year. How fast does AI revenue need to grow to pay back this data center mortgage?

“What happens when a new employee brings their agent to work?”

In September 2024, Hurricane Helene flooded Baxter International’s plant in Marion, North Carolina, which produced 60% of the nation’s IV fluids. Within a week, more than 80% of U.S. healthcare organizations reported shortages. One plant, one flood, one week.

AI eliminates the marginal hire. Tech job openings are down 45% from the 2022 peak, but up 16% since the start of 2026 - from 227k to 264k. Why the narrative violation?

“Since last November, 100% of my code has been written by Claude Code. I have not manually edited a single line, shipping 10 to 30 PRs per day.”

“Hi, Tomasz or Tomasz’s agent.” I’ve started receiving emails that begin this way. A byproduct, I suppose, of having written so much about AI. People now assume my inbox is monitored by robots.

I burned 84 million tokens on February 28th. Researching companies, drafting memos, running agents.

I hate to micromanage & I’ve been micromanaging AI. A few months ago, I’d use Claude for a familiar workflow : capturing notes from a meeting, drafting a follow-up email, updating the CRM, writing the investment memo.

Kirkland ibuprofen is the same molecule as Advil. Same dosage, same FDA requirements, same therapeutic effect. It costs 80% less.

Databricks started later. It built a more complex architecture. It focused on unstructured data; images, documents, logs, audio. Though vast within the enterprise, this data had historically produced little insight.

I started by asking AI to do everything. Six months later, 65% of my agent’s workflow nodes run as non-AI code. The first version was fully agentic : every task went to an LLM. LLMs would confidently progress through tasks, though not always accurately.

After writing about the SpaceX, OpenAI & Anthropic IPO liquidity problem, readers asked : what about Saudi Aramco? At $29.4b raised & a $1.7t market cap, it’s the largest IPO in history. Doesn’t it prove mega-IPOs can work?

We’re about to witness three of the largest IPOs in history. SpaceX is targeting $1.5t. OpenAI aims for $1t. Anthropic is valued at $380b. Combined, $2.9t in market cap. The scale is unprecedented. But the real problem isn’t the market cap. It’s the float.

For the first time in venture history, three distinct channels share the liquidity burden roughly equally. A decade ago, secondaries barely registered. They accounted for roughly 3% of exit value in 2015. Today they claim 31% : nearly $95b in the trailing twelve months.

Last quarter, my AI inference costs hit $100,000 annualized. I started small. Six months earlier, I was spending $200 a month on Claude. Then I added three agent subscriptions : Codex, Gemini, & Claude Code. I was paying $600 a month.

In AI, distribution is king. Skills are seizing the crown. Skills are programs written in English. They tell an agent how to accomplish a task : which APIs to call, what format to use, how to handle edge cases. A skill transforms an agent from a conversationalist into an operator.

Vertical software has fallen 43% this year. DevTools, just 21%. The gap between them, twenty-two percentage points, tells you what markets actually believe about AI.

Google’s Q4 2025 earnings call revealed a company in the midst of a spectacular AI acceleration. “Our first-party models like Gemini now process over 10 billion tokens per minute via direct API used by our customers, up from 7 billion last quarter.”

Leveraged software companies running on leveraged infrastructure. When AI compresses software revenue, the stress doesn’t stop at equity. It cascades into debt.

Meta’s first internal AI agent went from zero to thousands of engineers using it daily. That doesn’t happen by accident. On Tuesday, February 25th at 5:30 PM Pacific, the person who built it, Jim Everingham, will explain how.

I spent the weekend crawling Moltbook, the viral AI-only social network where 37,000+ AI agents post & comment while 1 million humans observe. The platform grew from 42 posts per day to 36,905 in 72 hours, an 879x increase.

“We are only at the beginning phases of AI diffusion & already Microsoft has built an AI business that is larger than some of our biggest franchises.”

In 1908, 253 American automobile manufacturers competed for the market1. By 1929, just 44 remained. The assembly line didn’t just change how cars were made. It changed who got to make them.

Talented people get promoted to management. So do talented models. Claude manages code execution. Gemini routes requests across CRM & chat. GPT-5 can coordinate public stock research.

Will designers design first in a world where AI can code software immediately, or just describe the design? Will large enterprises pay for premium observability when AI can migrate & monitor open source competitors?

After a decade of success, the modern data stack has entered consolidation. What comes next? The postmodern data stack is AI.

AI is NVIDIA’s third climb up a steep slope. First came gaming in the late 2010s. Then cryptocurrency. Now artificial intelligence. Each wave pushed revenue growth above 50% & with it, P/E ratios surged. P/E ratios rose before the revenue growth materialized.

“[Silicon Valley] is the biggest, most volatile petri dish of raw capitalism on the planet.” So what lessons does a successful short-seller living here have? As founder of Crown Capital Management, Scott Fearon has shorted the stocks of over 200 companies.

I asked Claude Cowork to read my tools folder. Eleven steps later, it understood how I work.

n 2012, we cared that we used software. Today we care how we use it. The difference is trajectory. In the last decade, adopting software was the priority. Moving from on-premise to the cloud or digitizing a manual workflow promised productivity gains. Adoption was the finish line.

For decades, the to-do list has been a catalog of debt, a deceptively thin list of items to do, with icebergs of work hidden beneath the surface. AI transforms tasks to work that has already been done.

Motive, the AI-powered fleet management company formerly known as KeepTruckin, filed their S-1 this week. The company has grown tremendously & in this post, we compare it to Samsara at IPO :