Frame
Start with a specific question about a user, capability, or operating constraint.
Our research examines how AI capability becomes product, how adoption actually happens, and what durable advantage looks like.
We look at architectures, tooling, data, and evaluation through the lens of what makes a system useful in the real world.
We study workflows and industries where intelligence can unlock a step-change in cost, quality, speed, or access.
Our point of view is informed by conversations with builders and users, then tested against practical operating reality.
The most useful way to assess an AI agent is not by how autonomously it appears to reason, but by whether it can own a valuable piece of work safely and repeatably.
Field note / AIGCAIGC creates an abundance of first drafts. Its lasting value will be measured by whether people can use that abundance to make better choices and more original work.
Field note / AI & workThe point of workplace AI is not to make people busier. It is to reduce avoidable coordination and give expertise, care, and judgment more room to matter.
Field note / TrustAs an AI product moves from a small group of enthusiastic users to consequential use, trust becomes an engineering, product, and leadership discipline.
Field note / AI & lifeAI can make daily life more dignified when it helps people understand complex systems, access services, learn new skills, and maintain more time for one another.
Our editorial lens favors research that helps a builder decide what to test next.
Start with a specific question about a user, capability, or operating constraint.
Use a relevant baseline and explain the conditions under which the comparison holds.
Describe what a product team would do differently, and what evidence could change the conclusion.