Jev case: Devs have spent years wrestling with JSON parsing

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Used Jev on the Venice API to get typed answers, probabilities, scores, and options instead of parsing JSON from LLM prose.

The original post

Devs have spent years wrestling with JSON parsing from LLMs. Jev on Venice API sidesteps the whole problem — typed answers, probabilities, scores, options your code branches on. No more prompt engineering just to get structured data out. This is what AI integration should have

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Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.

Where this case fits

Filed under coding & developer tools. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the coding & developer tools page.

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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post