Why Jev Is Changing How We Build With AI with Diogo Almeida - #779
Article image or reusable cover for TWIML AI
In this episode, Diogo Almeida, co-founder and CEO of TypeSafe, joins us to discuss Jev, TypeSafe’s recently released model for bringing fast, reliable intelligence directly into software.
We explore the idea of “machine-native intelligence” and why Diogo believes models optimized for generating text are poorly suited to many of the decisions required for real-world automation. He explains how Jev differs from traditional classifiers and LLM-based approaches, the role of reinforcement learning from calibrated decisions (RLCD), and why calibration and reliability are central to making AI useful as a software primitive. We also discuss the relationship between models and code, why Diogo believes AI systems should become more engineered rather than relying on a single model to do everything, and how Jev-like models could reshape agents, tool use, and the architecture of AI-powered software. 🗒️ Full show notes: https://twimlai.com/go/779.
The text is the source's own description of its publication. The content belongs to TWIML AI.
More to read
Ex-Ramp engineers raise $20M for platform Melius after scrapping their first product
TechCrunch AI 1 h ago
How AI decision models could change content moderation
TechCrunch AI 3 h ago
Point-Counterpoint: Consumers Will Never Pay for AI
The AI Daily Brief 4 h ago
AI computing startup Lambda to raise $4B ahead of planned IPO
TechCrunch AI 4 h ago