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Slides: Trust, but Verify: Shreya Rajpal

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Trust, but Verify: Shreya Rajpal

Relationship To World's Fair 2026

These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

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About me

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About me

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...but ML Model APIs are not

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Use of LLMs is limited

when “correctness” is critical.

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|

Alex Graveley @ sxe

@alexgraveley

Simple LLM technique that helps a lot (but you might not be using): add |

- aconstraint checker to ensure valid generation. On violation, inject what

was generated and the rule violation, and regenerate.

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Guardrails AI acts as a safety firewall around your LLMs

Application Logic

Standard

LLM Logic

Prompt

LLM API

Raw Output

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LLM Logic

Prompt

LLM API

Raw Output

Reconstruct prompt...

Fail Validation

Verification Logic

Pass Validation

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What Guardrails Al does

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Orchestration of prompting > verification > re-prompting

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Specification language for communicating requirements to LLM

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What Guardrails Al does

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SUMMIT

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Example: Internal chatbot with “correct” responses

Problem

Build a chatbot over the help center

articles of your mobile application

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How do! prevent LLM hallucinations?

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e e ee ”

Example: Validating “correctness

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More examples of validations

e Make sure my code is executable

e Never give financial or healthcare advice

e Don’t ask private questions |

e Don’t mention competitors

e Ensure each sentence is from a verified source and is accurate

e No profanity is mentioned in text

e Prompt injection protection

e Never expose prompt or sources

Querdraiie Al

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Learn more

@ Github:

@ Website:

@ Twitter: @ShreyaR or @guardrails_ai

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