Labels that explain a generated result
A clear description helps people interpret how a piece of content was produced.
Stories that connect ideas with everyday life
Stories & ideas.
An independent journal about practical, bounded AI use. We explore clear requests, useful examples, and the checks that help a generated result become working material.
11 stories to explore
Filenames that carry context
A useful name can answer a small question before the file is opened.
A prompt that states the work
A clear request gives the output a purpose that a person can evaluate.
Compare groups that share a start
A cohort can make a comparison clearer by naming a common starting condition.
Context is an input with a boundary
A tool can only use the information actually available to its current process.
Notes you can find again
A note becomes more useful when it has enough context to survive the moment.
Examples shape the model’s task
The choice and labeling of training data influence what a system can learn.
The denominator changes the story
A percentage describes a relationship with a group that needs to be named.
A benchmark measures a defined task
A score becomes meaningful through the test that produced it.
Choose the information you submit
A useful input should include the necessary context with a clear understanding of its handling.
Prediction and the appearance of understanding
A fluent response can be useful without explaining how the model reached it.
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A small idea to take with you
Define the check before the prompt
Choose a low-stakes task and write what a useful output must contain. Name one check you can perform independently of the tool.