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A collection of 9 posts

The Upstream Problem: Why Context Graphs Are Starving

The Upstream Problem: Why Context Graphs Are Starving

Foundation Capital just published what they're calling AI's trillion-dollar opportunity: context graphs. They argue that enterprise value is shifting from systems of record (Salesforce, Workday, SAP) to systems of agents. The new crown jewel isn't the data itself. It's the context graph:

Data Infrastructure

The $1B AI Drug Lab That Can't Touch Its Own Data

Nvidia and Eli Lilly just announced a billion-dollar AI drug discovery lab. The coverage is all about GPUs. Nobody's asking the hard question.

Emergence vs. Engineering: The Industry Just Bet Against the God Model

AI Infrastructure

Emergence vs. Engineering: The Industry Just Bet Against the God Model

Monday, OpenAI, Anthropic, Google, Microsoft, and AWS jointly donated their agent infrastructure to the Linux Foundation. If any of them actually believed a single model would achieve AGI in 2-3 years, this would be the dumbest move in corporate history. You don't standardize the plumbing when you'

The Shift Left Nobody's Talking About: When Your Data Stack Becomes the Next X-Acto Knife

Data Infrastructure

The Shift Left Nobody's Talking About: When Your Data Stack Becomes the Next X-Acto Knife

Data’s 1971 Moment In 1971, knowing how to assemble a magazine spread with an X-Acto knife was a career-defining skill. Art directors spent years mastering the geometry, the wax, the precise cuts. Then desktop publishing arrived. By 1985, Aldus PageMaker shipped on a floppy disk for the Mac, and

Will I Make It To The Restaurant Before The Soup Dumplings Get Cold? (And Other Problems In Machine Learning)

I'm chronically late. Not because I want to be rude - I feel terrible about it every single time - but because I'm catastrophically bad at predicting how long it takes to get anywhere. Turns out machine learning algorithms have the exact same problem. Here'

WebAssembly 3.0 and the Infrastructure We Actually Need

"We've finished the model... when do we get to the value?" Here's what I'm watching happen in real time: DevOps teams are spending $$$$$$ annually on cloud egress fees just to move ML models between environments, and flow data to centralized hosting. Platform

They Don't Have the Money (And Neither Do You): The Coming Era of Small Models

OpenAI is burning $115B through 2029. If they don't have the money, you definitely don't. The future of production AI isn't trillion-dollar datacenters—it's small, efficient, specialized models running on your infrastructure with your data.

The Anthropic $1.5 Billion Settlement Nobody's Reading Right: Your Enterprise Data is a Ticking Time Bomb

data governance

The Anthropic $1.5 Billion Settlement Nobody's Reading Right: Your Enterprise Data is a Ticking Time Bomb

Anthropic's $1.5B settlement underscores data legal risks; prioritize data rights and use secure, governed datasets over external sources

Why Your 'AI-Ready' Data Isn't: The Hidden Pipeline Problem Breaking Production AI

Companies spent millions on GPUs and AI talent, only to discover their data pipelines can't actually feed production AI. The revolution isn't waiting for better models—it's waiting for intelligent data pipelines.