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 :

Thursday is the new Monday for podcast producers. Analyzing hundreds of tech & VC podcasts over six weeks this fall through MotherDuck’s MCP server, I found 42% of episodes drop mid-week, between Thursday & Friday. Sunday? A publishing desert at just 3%. Here’s what else the data reveals.

Gemini 3 Flash represents a step function increase in model deflation : a gauntlet thrown.

Despite open-source AI models being 10-100x cheaper, proprietary providers haven’t lost pricing power. OpenRouter’s data reveals a market splitting in two.

It’s not often that venture capital thinks about the credit markets. I remember becoming a venture capitalist three months before Lehman fell, when mortgage securities topped the news of the global financial crisis.

No, founders are not adopting Bryan Johnson’s regimen to reverse aging. Quite the opposite : the average founder raising capital ages six months every year.

Enterprises learned a lesson from cloud data warehouses. They handed over both data & compute, then watched as the most strategic asset in their business, how they operate, became someone else’s leverage, which created an opportunity for Iceberg. Fool me once…

A new study from OpenAI shows AI saves the average white-collar worker 54 minutes per day. Where does all that value go?

Streaming is the next category to consolidate within the modern data stack. IBM announced its intent to acquire Confluent.

Since I watched software engineers using AI, I’ve become jealous. I’ve seen the most sophisticated software engineers assign 15 to 20 coding tasks in GitHub to an AI. They play foosball. They grab coffee. They return to evaluate the agent’s work.

While OpenAI signed $1.15 trillion in compute contracts through 2035, DeepSeek trained a frontier model for $6 million. This was 2025’s central question : are we building on bedrock or quicksand? The top 10 posts of 2025 examined some of these topics :

I remember hosting a dinner of sales leaders to talk about AI. I asked them what will your CRM do for you in the future? Nearly unanimously came the reply : enable salespeople to spend most of their time with customers.

Private equity firms have emerged as the newest distribution channel for AI startups. While public companies have decreased from 6,639 in 2000 to 3,550 in 2024, PE-owned companies in the US have grown from 1,950 to 14,300. The rate of growth continues to accelerate.

The AI market today is bacon in a hot skillet. Everything is sizzling, moving, & changing at an incredible pace. We’re all watching it closely.

Two revelations this week have shaken the narrative in AI : Nvidia’s earnings & this tweet about Gemini. The AI industry spent 2025 convinced that pre-training scaling laws had hit a wall. Models weren’t improving just from adding more compute during training.

70% of production AI teams use open source models. 72.5% connect agents to databases, not chat interfaces. This is what 375 technical builders actually ship - & it looks nothing like Twitter AI.

Ten months ago, DeepSeek collapsed AI training costs by 90% using distillation - transferring knowledge from larger models to smaller ones at a fraction of the cost.

By Monday lunch, I had burned through my Claude code credits. I’d been warned ; damn the budget, full prompting ahead.

Datadog is becoming a platform company, & its Q3 2025 results underscore how successful this transition is. If nothing else, the consistency around 25% growth for the last 12 quarters exemplifies this point.

Just how much are we spending on AI? Compared to other massive infrastructure projects, AI is the sixth largest in US history, so far.

I sleep better knowing my agents work through the night. Less work for me in the morning. My podcast processor transcribes & analyzes conversations. I started on my laptop, needed a little database to collect podcast data & metadata, & booted up a DuckDB instance.

Microsoft & Google both announced earnings yesterday, & the scale of AI adoption remains staggering. The infrastructure businesses are growing at accelerating growth rates that are the envy of businesses one-hundredth the size.

As the world follows every whisper & rumor from AI, what has happened to public SaaS? The answer is not much! All the fun is in the private markets. Multiples haven’t moved outside of a narrow band since the post-Covid crash in 2022.

There’s this notion that product market fit is this binary condition that once you pass the gate, you’re done. And that’s no longer the case. Product market fit is like United Miles. You continue to fly to maintain 1K.

When I worked at Google, I was lucky to collaborate with some of the brightest machine-learning (ML) engineers. They worked on feature engineering. By picking the factors to guide the ML model, their advances could generate tens to hundreds of millions of additional revenue.

It’s 9:30 AM. Do you know where your agent is? As we enter the era of agentic AI, this is an increasingly important question. ChatGPT launched the consumer use of AI, compressing all of human knowledge into a single model. Now we are asking AI to act on our behalf at work.

I asked Claude this morning about the most important news in tech. A few follow-up questions about Salesforce’s Dreamforce, Samsung’s XR headset, & TSMC earnings later, I popped over to ChatGPT Pulse. It suggested some updates about the Fed’s rates policy.

Why was the Fivetran-dbt merger all but inevitable? Fivetran & dbt Labs announced their merger yesterday. The all-stock deal combines two companies into an entity approaching $600 million in ARR.

Philip Schmid dropped an astounding figure yesterday about Google’s AI scale : 1,300 trillion tokens per month (1.3 quadrillion - first time I’ve ever used that unit!). Now that we have three data points on Google’s token processing, we can chart the progress.

Watching the OpenAI Dev Day videos, I listened as Thibault, engineering lead for Codex, announced “Codex is now a senior engineer.” AI entered the organization as an intern - uncertain & inexperienced. Over the summer, engineering leaders said treat it like a junior engineer.

Chris Klayko brings over two decades of sales leadership experience transforming technology companies from promising startups to multi-billion dollar enterprises. As SVP of Sales at Databricks, Chris leads the charge in democratizing data & AI for organizations worldwide.

Walk into a bookstore’s self-help section , rows of productivity systems : Getting Things Done, Bullet Journal, Zettelkasten. Each promises transformation—if you commit weeks. The market thrives , hundreds of new titles annually.

I discovered I was designing my AI tools backwards.

“The way to do a piece of writing is three or four times over, never once.” Writing is hard. John McPhee, who invented literary nonfiction that reads like a novel, developed a four-draft writing method that transforms chaotic ideas into compelling narratives.