19 posts found
Why temperature changes the answer, not the knowledge
Turning temperature down does not make a model more accurate. It makes it more repeatable — and confusing the two is how...
Why models hallucinate, and what actually reduces it
Hallucination is not a glitch that a better model will one day remove. It is what generation does when it has nothing to...
Structured output beats parsing prose
If your code needs a value from a model, ask for JSON and validate it. Regexing an answer out of a paragraph is a bug wa...
Choosing between a large model and a small one
Most production traffic does not need the largest model available. Routing by task rather than defaulting to the top of...
An agent is a loop, not a personality
Strip away the branding and an agent is a small loop: call the model, run the tool it asked for, feed the result back, r...
Tool calling is an API contract the model can read
A tool definition is documentation with a schema attached. Write it for a capable colleague who has never seen your syst...
Why agents fail on long tasks
An agent that handles five steps beautifully can fall apart at twenty. The reason is rarely reasoning — it is that the c...
When a workflow beats an agent
If you already know the steps, do not ask a model to rediscover them on every request. A fixed pipeline with model calls...
What an AI agent can actually do with a design system
Given a real design system, a model stops inventing interfaces and starts assembling them. The difference is not the mod...
Design tokens are the interface AI needs
A token that only names a hex value has saved you nothing. A token that names a job tells a model which decision it is m...
Generating layouts that respect a grid
Generated layouts usually look almost right, and "almost" is where the eye catches. Most of the fix is stating the rules...
Reviewing AI-generated UI: a checklist
Generated interfaces fail in a predictable set of places. Knowing which ones turns review from a vague unease into a lis...