Jev engineering playbook: cutting agent costs with structured decisions
TypeSafe's Jev replaces generative calls with structured decisions, with a customer-support example estimating AI bills could drop by about 90%.
Diogo Almeida (ex-OpenAI researcher) showed AI Engineer how to stop burning billions on AI inference without building a single bigger model six weeks later, his startup TypeSafe AI shipped Jev, a model that doesn't write a single word, it only makes decisions while OpenAI and Anthropic are pouring billions into smarter models, developers are still paying premium prices for agents that waste tokens deciding what to do next Jev flips the equation, structured decisions instead of endless generation, fewer unnecessary LLM calls, and more work done for every dollar spent on compute one example shows how an online store handling 100,000 support messages a month could slash its estimated AI bill from $7,950 to $772.65, cutting costs by 90.3% with Jev and Kimi K3 Diogo turned the approach into a one-page Jev Engineering playbook, here's how to build AI agents that stop wasting compute and actually scale ↓
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