Solve a real constraint.
The most promising applications help people navigate information or services that were previously costly, confusing, distant, or difficult to use.
AI 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.
The most promising applications help people navigate information or services that were previously costly, confusing, distant, or difficult to use.
Useful consumer and public-interest systems need to work across languages, abilities, devices, time constraints, and uneven levels of digital confidence.
The goal is clearer options and better support, not invisible decisions. People should be able to understand, question, and override the system.
We look for founders who can describe the positive change in a person’s life as clearly as they can describe their technology.
Consider an assistant that helps someone understand a service application. Test it with different languages, accessibility needs, and levels of digital confidence. Ask whether it explains unfamiliar terms, identifies missing information, and distinguishes a suggestion from an official requirement. Let the person review every detail before anything is shared or submitted. An assistant can make a process faster while still leaving someone confused or dependent. The better measure is whether the person understands the next step and has more confidence and control in taking it.
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.
Start with the investor question: What human outcome improves?
Can a person explain their options and the next step after using the product?
Who is excluded by the language, cost, device requirements, or assumed level of digital confidence?
Can the person decline, correct, or seek human support without losing access to the underlying service?