Guardrails: checks around the model
Layered guardrails for LLM applications: screening input with a small model, validating and redacting output, checking actions, limits, and what to show the user when a check fails.
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Layered guardrails for LLM applications: screening input with a small model, validating and redacting output, checking actions, limits, and what to show the user when a check fails.
The main risks of LLM apps, from prompt injection to excessive agency, and the defenses that work: keeping data apart from instructions, least privilege and screening.