we spent 3 years learning how to write prompts Jev from
Split large prompts into small Jev yes/no questions like urgency and billing, then combined the answers in code.
The original post
we spent 3 years learning how to write prompts
Jev from @typesafeai breaks big prompts into smaller decisions you can build around
instead of one giant prompt hoping the model gets everything right, you ask smaller questions:
- is this urgent?
- is this billing?
- does a human need this?
then combine the answers in your own code
less prompting, more building
Quoted post
@CompleteSkeptic34.6M viewssourceAfter co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x
Engagement when collected
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