Do I need an LLM?
Words made simple
A few useful meanings before you read the explanation.
- LLM
- A model trained to work with language. It can write or summarize text, but its answer still needs checking against reliable information.
- Deterministic
- Following steps or rules defined by code. The model does not decide which step should run next in a deterministic workflow.
- Use an LLM for language transformation, interpretation, synthesis, and bounded proposals.
- A dedicated classifier, OCR engine, search index, or template may solve the narrower task better.
- Define acceptable uncertainty and what happens when the model cannot answer.
Example: A deterministic template explains in_review; an LLM may help turn a complex supplied narrative into a draft summary. Different routes can coexist in the same UI.
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Do I need an LLM?
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Use an LLM for language transformation, interpretation, synthesis, and bounded proposals. A dedicated classifier, OCR engine, search index, or template may solve the narrower task better. Define acceptable uncertainty and what happens when the model cannot…
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Practice this conceptAdapted from 13_AI.MD · “2. Do I need an LLM?”. Examples are study fragments; framework behavior can depend on your version.