# AI SDK 7

TypeSafe AI's probabilistic decision model Jev is now available on Vercel AI Gateway, letting an application hand in a state and get back typed Choice, Score and Boolean answers with probabilities. Regular language models generate text one token at a time for the application to parse and validate; Jev evaluates all declared questions in parallel and returns structured answers directly. TypeSafe reports Jev was up to 193.6x faster and 444.6x cheaper than LLMs on its workflow evaluations, for uses such as picking the next tool in an agent loop, deciding whether to continue or stop, scoring risk, and verifying outputs.

TypeSafe AI's probabilistic decision model Jev is now available on Vercel AI Gateway, letting an application hand in a state and get back typed Choice, Score and Boolean answers with probabilities. Regular language models generate text one token at a time for the application to parse and validate; Jev evaluates all declared questions in parallel and returns structured answers directly. TypeSafe reports Jev was up to 193.6x faster and 444.6x cheaper than LLMs on its workflow evaluations, for uses such as picking the next tool in an agent loop, deciding whether to continue or stop, scoring risk, and verifying outputs.

At Ship 2026, Vercel shifted its platform from frontend hosting toward agent infrastructure, announcing that Python is now generally available on Vercel and introducing Vercel Daemons in public beta for continuously running background workers. The platform also pairs agent-facing command-line access, connectors, and persistent workspaces so agents can deploy software, be deployed, and take part in operating the platform itself. The stated scope covers running FastAPI, Flask, or Django with standard CPython, with the platform keeping a set instance count and replacing failed workers.

At Ship 2026, Vercel shifted its platform from frontend hosting toward agent infrastructure, announcing that Python is now generally available on Vercel and introducing Vercel Daemons in public beta for continuously running background workers. The platform also pairs agent-facing command-line access, connectors, and persistent workspaces so agents can deploy software, be deployed, and take part in operating the platform itself. The stated scope covers running FastAPI, Flask, or Django with standard CPython, with the platform keeping a set instance count and replacing failed workers.