Agents make dozens of small decisions before producing useful output: which source to trust, which tool to call, what context to keep and when to stop. Jev brings those hidden choices into the open by turning them into typed decisions with probabilities, instead of relying on free-form text alone. That makes it useful across browser […]
The post 10 Jev Projects on GitHub You Should...
You’re coming to Cleveland for MAICON 2026. Excellent choice.Now let’s make sure you get the most out of it.
An AI agent can function as designed yet produce results an organization cannot verify or safely use. In this episode, Melissa Ramey, Director, AI Transformation – Data Insights and User Experience at Salesforce, joins Emerj's Yolandi de Weerdt to examine who owns agent behavior after deployment and why correcting individual outputs does not fix the underlying workflow. She explains how...
Many teams now use LLM-as-a-Judge to check AI answers, especially when exact-match tests fail for long or open-ended responses. But every judgement adds cost, delay, and possible bias, making this hard to scale. Jev, a small decision model from TypeSafe AI, takes a leaner route: it returns a short choice with confidence instead of full […]
The post JEV vs LLM as a Judge: The AI...
Today's guest is Keenan Venuti, CTO & Co-Founder at Vector Legal. Founded in 2026, Vector Legal is an AI-native law firm based in San Francisco serving startups, growth-stage companies, venture capital firms and private equity investors. Combining experienced attorneys with proprietary AI technology, the organization supports clients from company formation through fundraising, commercial...
Traditional public relations taught marketers to pitch stories and build relationships with journalists. That work still matters, but it no longer decides whether a brand shows up when a buyer asks ChatGPT, Gemini, or Google's AI Overviews for a recommendation.
Drug discovery teams are running short of new ideas to test, and AI models that simulate how cells respond to drugs only pay off once leaders know when those predictions can be trusted with experiments, timelines, and budget.
In this episode, Daniel Veres, Co-Founder and Chief Scientific Officer at Turbine, and Giorgio Gaglia, Head of Systems and Disease Biology at Sanofi, examine...
Most AI coding demos stop at task managers, weather apps, or simple chatbots. For this project, we take on something more demanding: building an enterprise customer-support platform that can investigate complaints, retrieve relevant policies, recommend resolutions, and keep risky actions behind human approval. This gives us a practical way to test Claude Fable 5.1 as […]
The post...
For all the data that AI systems continually amass and analyze, enterprise AI agents often suffer from a curious shortcoming: a lack of knowledge. More than data, knowledge is the understanding of what the data means in the context of individual organizations. AI agents need this understanding to reason about situations, make decisions, and ultimately…
In 2026, the question for enterprise AI is no longer whether predictive models can outperform statistical forecasts—that argument is settled. The big question now is how to enable predictive systems to act on their own conclusions without drifting from business intent. The frontier has moved from prediction to autonomous decision making, and the gap between…