What is Jev?
TypeSafe Jev is a System One evaluation model: it returns typed Choice, Score, and Boolean answers with probabilities — not free-form prose.
Curated external starters and indexes so you can learn Jev without waiting on every chapter card. Named links only — we do not mirror awesome lists in full, invent livestream official cases, or promote clone tutorials as first-class paths.
TypeSafe Jev is a System One evaluation model: it returns typed Choice, Score, and Boolean answers with probabilities — not free-form prose.
Choice picks one named option; Score places state on an ordered rubric; Noul (boolean) estimates P(true). Confidence comes from the option distribution.
Low confidence → human queue with no default action. Money, refunds, and irreversible side effects stay human-owned — suggestions only.
Official map, docs, hello world, then optional community explainers and demos.
What you learn: See where System One / Jev decisions fit before you pick a pattern.
Link: docs.typesafe.ai/concepts/use-case-map
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Read the docs baseline, then the launch post on models and Jev.
Link: docs.typesafe.ai · Introducing System One models and Jev
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Minimal first repo to call Jev and see a typed decision return.
Link: github.com/nishimotz/hello-jev
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Community essay framing when a decision model beats text generation.
Link: zenn.dev/mizchi/articles/jev-is-gpu-for-llms
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Watch short demos of Jev in action (community uploads).
Link: YouTube · QbYBRjOaGOo · YouTube · -5d0otNVZ1Y
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Recorded walkthrough of a Jev setup / decision flow.
Link: loom.com/share/18c4dbcf8db546dfb2d7f2ef018e78e4
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Try a live Val Town demo without standing up your own stack.
Link: typesafe-demo.val.run
Notes: Community-sourced · not affiliated with TypeSafe
High-signal public repos that show Jev under load or in agent harnesses.
What you learn: Browser-use launch demo focused on speed and low-latency decisions.
Link: github.com/browser-use/jev-ultrafast
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Compaction / context-control patterns with Jev in the loop.
Link: github.com/tamaratran/fast-jev-compaction
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Harness scaffolding for evaluating and wiring Jev decisions.
Link: github.com/AntonioCoppe/jev-harness
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Agent / tooling experiment that gates actions with Jev-style checks.
Link: github.com/Nyarlathoteppppp/pi-heed
Notes: Community-sourced · not affiliated with TypeSafe
Index links only — open the list on GitHub or the directory site; we do not expand each repo as a fake case here.
What you learn: Community index of Jev links and projects — browse the list, do not copy it here.
Link: awesomejev.cc · github.com/daftAI2026/awesome-jev
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Community “by TypeSafe” curated awesome list (index only).
Link: github.com/Anil-matcha/awesome-jev-by-typesafe
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Another community directory site + GitHub index of Jev resources.
Link: awesomejev.com · github.com/hellogumbo/awesome-jev
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Additional community awesome list — use as an index, not a mirror.
Link: github.com/AnotiaWang/awesome-jev
Notes: Community-sourced · not affiliated with TypeSafe
What you learn: Use-case-oriented awesome index for discovery (not chapter cards).
Link: github.com/aliaihub/awesome-jev-usecases
Notes: Community-sourced · not affiliated with TypeSafe
Use the Start here paths: official map and docs, then a minimal hello repo. Killer demos and directories are optional indexes — not full mirrors.
No. Awesome-style directories are community indexes. This site does not expand every repo as a fake case or treat clones as first-class tutorials.
Paid starters stay under Templates and Livestream. Learning paths link out; they are not a substitute for the Gumroad pack.