Claude for Trust and Verification

A practical framework for advanced users

Top Takeaways

Recognise the most common ways Claude can produce flawed outputs
Decide how much verification is needed based on task risk and impact
Use a practical trust calibration framework for low, medium and high-risk work
Build source checks, logic checks and human review steps into AI workflows

Class Overview

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AI can save time, but only when users know when to trust it, when to challenge it and how to verify its outputs. As teams become more advanced in their use of Claude, the biggest skill is no longer simply writing better prompts. It is learning how to right-size verification and build judgement into AI-supported work. This session helps participants understand...

Available Class FormatsPeople Count

Interactive Workshop

Best for employees who want to talk, connect, and engage in hands-on training.

Best for teams up to 60 people

Facilitated Learning

Best for employees who like to listen with some engagement and discussion throughout.

Best for teams up to 90 people

Lecture Followed by Q&A

Best for employees who like to listen, absorb and ask questions at the end. Can also be a keynote or speech.

Best for teams up to 120 people

Class Durations

Flexible class lengths to meet your team’s needs.

60Mins
75Mins
90Mins
2Hours

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Irma K.

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