Local Agentic Theory For Mobile Games — Shafik Quoraishee & Joanne Song, The New York Times
Source
AI Engineer
Author
AI Engineer
Date
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
Why it matters
A hard-numbers look at what agentic inferenceRunning a trained model to get answers — the phase where AI is actually used, as opposed to trained.Full definition → costs when it has to run locally inside a real-time frame budget — the constraint that decides whether on-device agents are viable at all.
Key quotes
“Our puzzles are made by people. They're not made by AI.”
Shafik Quoraishee
“RL changes the model itself and changes the weights in the model”
Shafik Quoraishee
“you get a new frame every 16 ms a pound if your refresh rate is 60 Hz. You need to actually fit the agent planning within that”
Shafik Quoraishee
“The agent rewrites the layout live adapting to the human and not the other way around.”
Joanne Song
“the future of AI doesn't have to be one giant centralized brain. It can be billions of small local brains, each running on a personal device, each shaped entirely by the individual it serves”
