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JevMade field notes / Long-form interview

How an AI tool is built to make choices for software

This interview explores how a creator built an AI tool to make choices for other software programs. It explains why training software to pick options works differently than training an AI assistant to chat with humans.

Original by Latent SpaceEvaluation

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JevMade’s plain-English explanation

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AI narration

Credits

“Jev: System One models for Prod, not God — with Diogo Almeida, CEO, TypeSafe AI” by Latent Space. Read the original source.

This expanded guide is an AI-narrated adaptation prepared by JevMade. It expands the source’s essential ideas, examples and caveats in JevMade’s own words and is not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

Our summary

This is an interview with the creator of Jev, an AI tool that chooses from options rather than writing an answer. Software builders use it to help their programs make automated choices behind the scenes without needing a person to read a chat message.

The creator explains that standard AI assistants are trained to write helpful text for people. Instead, Jev is trained to provide a clear choice and estimate how certain it is. Builders break large tasks into small steps so the software can act on these specific choices.

This interview is useful for software builders who want to add automated choices to their programs. However, the claims about how the tool was trained and its goal to be reliable come directly from the creator. These details have not been proven by outside tests.

Key takeaways

  1. Jev is an AI tool that chooses from options rather than writing an answer.
  2. The creator suggests breaking large software tasks into small, measurable choices for the AI.
  3. Standard AI assistants are built for human chat, which can make them hard to use in automated software.

This interview presents the creator's personal views and unpublished claims about how the tool was trained. It does not provide independent proof of how well the software works in real projects.

Podcast transcript · Source reviewed · Original published

Read the original guide Opens the author’s site in a new tab.