The short answer
Agency is about maintaining goals, selecting actions, and responding to feedback; fluency is only one visible part of that loop.
Language is a powerful interface, but fluent language alone does not establish that a system can pursue a goal in the world.
Agency involves choosing an action, observing its result, and updating the next move. The quality of that loop matters more than the confidence of any single sentence.
Give a system a goal, imperfect tools, and changing conditions. Then measure whether it adapts without losing the purpose of the task.
A useful note, once a week
Make room for better signal.
About the author
Maya writes about the systems, people, and practical choices shaping the next generation of AI products.
More from Maya Chen →
More tokens are useful. Knowing which context deserves attention is the deeper product problem.
Intelligence in the real world depends on memory, tools, feedback, and institutions as much as model capability.
Short answers are easy to score. Long-horizon work reveals whether a system can maintain goals, recover from errors, and adapt.
Keep the good stuff coming
One thoughtful note on AI, agents, and AGI. No noise.
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