What AI is really for
Best case: we’re in a bubble. Worst case: the people profiting most know exactly what they’re doing.
Best case: we’re in a bubble. Worst case: the people profiting most know exactly what they’re doing.
That is the heartbeat of contemporary AI. The models are creating meaning, yet their pathways remain opaque.
LLMs, humans and the old tricks that still work.
A prediction essay for the next 20 years of intelligent robotics.
Software development is fundamentally a practice of problem-solving, and so, most of the work is done in your head.
AI’s infinite memory could endanger how we think, grow, and imagine. And we can do something about it.
The shift in product design with the advent of AI and a potential generative experiential future.
Practical examples across research, writing, coding, analysis, and everyday tasks on how to collaborate with Claude AI.
A look behind a design-first diabetes education game, built by hand-crafted pixel art and powered by an AI that mostly knew what it was doing.
When software development teams experience huge productivity booms, how do design teams respond?
We are in an AI Bubble: the big question is if this bubble will be worth it for the physical infrastructure and coordinated innovation that result?
AI tools are commoditizing single-skill roles. The future belongs to people who can think, build, and ship across the entire stack.
Report by McKinsey on agents, innovation, and transformation—and how companies are in the early stages of capturing value with AI.
We’re in 1995 again. This time with Artificial Intelligence.
Telling Amazon leadership that we need a more responsible rollout of AI. Every single signature makes the message stronger.
“Artificial intelligence” is a failed technology. It’s time we described it that way.
AI erased trust in remote interviewing. Here’s how the system broke and how companies are rebuilding interviews around real human reasoning.
What happens now that AI is everywhere and in everything? 17 readings from the furthest reaches of the AI age.
The problem with AI coding isn't technical debt. It's comprehension debt.