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EAT. LEARN. PLAY.Family AI Coach

Proposal for foundation reviewPrepared by Jon Jessup

EAT. LEARN. PLAY.Family AI Coach

Build reading confidence and AI judgment through the experiences Oakland families already share.

Oakland children are already meeting machines that answer confidently and are sometimes wrong, usually with no adult beside them to show what to do about it. The same children are working to build reading confidence. Family AI Coach proposes treating those as one skill: a five-minute activity, run by a caregiver with a child aged 7 to 10, in which they read a short reviewed passage, answer a question, point at the sentence that proves it, and catch a mistake the Coach makes on purpose. Founded by Stephen and Ayesha Curry, EAT. LEARN. PLAY. supports Oakland children through nutritious meals, literacy resources, and equitable opportunities to play, and this proposal asks whether a small guided activity could travel with what those programs already put into families' hands.

What is new here is the deliberate mistake. Most family AI tools try to be right; this one is designed to be caught. Asking a child for the sentence that proves an answer is a reading exercise and a judgment exercise at the same moment, and it is the one move that stayed in the design from the first version to this one.

Type A AI Concept BriefScripted demonstrationNot a deployed Agentforce implementation

Who does what

The caregiver operates the service and the child supplies the ideas. A caregiver receives one short activity, reads it with their child, and asks the questions on the card. The child answers, points to evidence in the text, and decides whether an answer holds up. Nothing is designed for a child to use alone, and there are no child accounts. The initial age range is 7 to 10.