JevMade field notes / Measured experiment guide

How to test what an AI assistant should remember

This guide explains a testing tool that helps an AI assistant decide which facts to keep. It checks if a detail matches the original conversation, will be useful later, and keeps the original meaning.

Original by Cairn InkEvaluation

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Credits and license

“Cairn Jev Lab” by Cairn Ink. Read the original source.

This expanded guide is an AI-narrated adaptation of the source’s essential explanation, examples and caveats, not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

License: MIT

MIT License

Copyright (c) 2026 Cairn-ink

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Our summary

This project is a testing tool that helps an AI assistant decide what information to keep from a conversation. Builders use it to check if a proposed memory is accurate and useful before the software actually saves it, preventing the assistant from remembering false details.

The software uses Jev, an AI tool that chooses from options rather than writing an answer. It checks if a detail matches the original text, if it will be useful later, and if it keeps the original meaning. Based on these answers, a strict rule recommends whether to save, skip, or wait.

This tool only recommends what to save; it does not actually store or delete information. It is useful for people building AI software who want to test memory rules. To test your own text, you must provide a private access code to connect to the service.

Key takeaways

Test if a memory matches the original text, keeps the same meaning, and will be useful later.
Save the AI tool's choices and confidence scores next to the clear rule it followed.
Use your own examples to see how the software handles tricky or unclear statements.

More guides →See the experiments →