13h • 📚 Resources & Finds
The Best Model Is Not Always The Right Model
The frontier moved. Our model-selection habits did not.
When the floor rises, model choice stops being a prestige ladder. It becomes an effort-allocation problem.
Haiku, Sonnet, Opus, Codex. The question is not “Which one is best?” The question is “What level of effort does this outcome deserve?”
That changes the prompt, too.
Older prompts explained the route:
Read this, extract that, then format the answer.
With a stronger model, you define the outcome:
- What must be true when the work is finished?
- Who is it for?
- What constraints matter?
- What counts as evidence?
- What failure would make the result unusable?
- What review gate should it pass?
You are not explaining less. You are explaining at a higher level.
Spend deeper effort where ambiguity, failure cost, synthesis, or time horizon justify it. Use lighter effort when the path is clear and the review loop is cheap.
The best model is not always the right model.
The right model is the one whose effort matches the outcome.
//A<3
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The Best Model Is Not Always The Right Model
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