Read & learn
Written guides.
Understand Jev, one idea at a time. Walkthroughs, recipes, and writeups — our notes first, the original next.
Explore the Jev ecosystem.
Learn, build, and play with Jev — from deep technical guides to creative experiments.
Watch & learn
Video guides.
See an idea take shape. Tutorials, demos, and deep dives, organized by topic and credited to their creators.
Make & explore
Experiments.
See what builders made with Jev. Games, tools, repositories, articles, and more — traced to their sources.
The directory03 / 03 · Experiments
Find something worth exploring.
Every category, from games and tools to repositories and writeups, traced to a primary source.
Same ideas.
Different paths.
This is the full registry, not just the featured picks. Figures like speed, cost, and stars are maker-reported or captured snapshots, not JevMade measurements.
378 experiments · showing 61–120
Jev flies a drone across a randomly generated city while avoiding obstacles between two points.
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A text-only Jev agent navigates Pokémon Red by turning parallel yes-or-no judgments into emulator button presses.
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A browser piano played by Jev, with your chosen mood guiding the performance.
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Watch Jev battle Pokémon in Showdown or FireRed by selecting one legal move or party switch each turn.
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Play chess or Connect Four against Jev, or spectate both sides while every legal move's probability remains visible.
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Watch a ViZDoom agent move at game speed while Jev periodically chooses its goal, target, direction, aim, jumps, and shots.
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Watch a U.S. equities dashboard combine fixed entry rules with Jev’s five-second review of market direction and risk.
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Edit a Mermaid support-routing flow, submit a ticket, and watch Jev’s answers illuminate the route it takes.
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Watch posts suspected of AI writing turn red or fold away on X, LinkedIn, and Reddit as you scroll.
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Give a browser one goal and watch Jev choose the next operation and indexed page element at every step.
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Plays Clash Royale on a real Android device by choosing a strategy, card and legal square from live screen perception.
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from the source
from typesafe_sdk import Choicecriteria = { strategy.name: {"what": strategy.meaning, "not_for": strategy.not_for}}
Let Jev choose destinations and battle actions while deterministic code reads Pokémon FireRed RAM and presses the controls.
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A terminal interface pairs OpenAI answers with Jev routing, clarification and uncertainty decisions.
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from the source
flowchart TD U[Human asks a question once] --> J1[TypeSafe Jev: routing decision] J1 --> D1[Choice: response mode] J1 --> D2[Noul: clarification required] J1 --> D3[Noul: uncertainty notice required]
Every ten minutes, Jev revisits an absurd existential verdict using the day's strange news.
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from the source
wrangler pages secret put TYPESAFE_API_KEYnpm run deploy
A playground gathers 110 editable Jev examples, from practical use cases to games and dilemmas.
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noul
Does the message ask for an unresolved action?
Describe a use case and Jev selects the ingredients for a user interface without generating code or copy.
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A simulated Franka arm tries to stack a blue cube on a red one through a sequence of Jev-selected actions.
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Set 22 Jev-controlled footballers loose on a 3D pitch, then inspect or take over any player.
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Pit Jev's seven-move fighter against a simulated fly connectome and compare several live and offline control strategies.
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Spectate two Jev-controlled Snake games side by side as each agent clicks only safe on-screen direction buttons.
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An isometric world where Jev chooses actions for people with their own memories and limited knowledge.
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A local browser runner reads a chess.com bot board, asks Jev for a legal move, and clicks it on the page.
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A custom object detector helps Jev steer a watering can through Lazada's raindrop game on an attached Android device.
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Guess whether a de-branded service belongs to AWS, Azure, or Google Cloud, then compare your answer with Jev’s probabilities.
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Type beside a WebMCP-enabled page and watch Jev predict a schema-valid tool call as your request takes shape.
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A word-by-word text generator built from Jev choices.
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A deliberately impractical text generator that asks Jev to choose every word.
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A simulated Perseverance rover where Jev classifies terrain and hazards while Claude plans the mission.
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from the source
questions[`${f.id}__type`] = { type: "choice", instructions: {
A Mineflayer survival bot where Jev chooses threats, actions, eating and escape direction from a state shaped by memory and emotion.
ACTUAL RECORDING12 SEC ↗
from the source
const response = await client.systemOne({ model: config.jev.model, state: cleanState, questions: { threat_level: score(
A Catan-style multiplayer game with Jev-controlled AI seats.
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from the source
const questions: Record<string, Question> = { move: choice('What is the best move right now?', moves), ...(corners.length ? { where_settlement: choice(
A WebAssembly DOOM port whose autoplay adds Jev tactical calls to a deterministic route follower at chosen danger points.
ACTUAL RECORDING12 SEC ↗
from the source
safeToRun: noul({ question: 'Is it safe for the player to keep running along the route right now, wi... context: `${OBJECTIVE_BRIEF} The player is following a known route to the exit. Ju... }), response: choice({
Watch Doom through a spacecraft-style mission dashboard: Jev judges where to explore while code uplinks the moves.
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Simulate evacuees choosing roles, routes, and rescue actions over an FDS-GPU fire field.
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Jev turns plain-English goals into sequences of hardcoded actions for a simulated Franka arm.
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A browser-based Doom agent acts on structured spatial state and exposes its decisions live.
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Two Jev players compete at Gomoku through a nine-cell input window, with every move open to inspection.
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Scramble a 3D Rubik's Cube and watch Jev try to solve it, move by move.
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from the source
# 1. installpnpm install# 2. configure the engine (server-only secrets)echo 'JEV_ENGINE_API_KEY=<your-key>' >> .env.localecho 'JEV_ENGINE_BASE_URL=<endpoint>' >> .env.local
Jev plays the original Civilization II in a browser while displaying its action probabilities.
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Jev attempts to solve the sliding-tile game 2048.
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Clarity Judge checks writing along several named dimensions and reports a verdict and confidence for each.
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A Game of Thrones story demo uses a language model for narration and Jev for parallel game-state judgments.
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from the source
your action ──► Narrator (GPT-5.6 Luna, via OpenRouter) ──► the scene │ ┌────────────────────────────────┘ ▼ Jev — multiple questions, evaluated in parallel
A side-by-side comparison of GPT's written responses and Jev's yes-or-no judgments.
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A moderation demo screens text for seven hazards and a severity score in one call.
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A decision board asks Jev which livestream idea should become the next working prototype.
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from the source
npm installcp .env.example .env.local# paste TYPESAFE_API_KEY from https://console.typesafe.ainpm run dev -- --port 4317
A compact Next.js playground for testing Jev's Choice, Score and Noul questions.
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Toolgate decides whether an agent's tool or MCP call should proceed, ask a human or be denied.
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A Rust playground scores source code for load-bearing importance and serves the results in a viewer.
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from the source
typesafe-ai load-bearing example.ts > scores.jsonltypesafe-ai load-bearing ./src --model jev-latest > scores.jsonltypesafe-ai load-bearing-serve scores.jsonl# Or pipe directly (the viewer starts after scoring reaches EOF):typesafe-ai load-bearing ./src | typesafe-ai load-bearing-serve
A Rust playground for experimenting with Jev's three question types.
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Race Jev at the card game Speed while the interface reveals its legal-move beliefs, chosen play, and pressure rating.
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Play Battleship against Jev, follow its probability heatmap, or match it against text models on identical fleets.
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Jev ranks the available moves in a Python 2048 engine designed for AI search and browser spectating.
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Browse an arcade of Jev-piloted experiments spanning Flappy Bird, Pong, Invaders, flight, driving, space, and survival.
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Chat with a model that cannot write: Jev can only pick from yes/no, pirate, headline, fortune, or custom canned replies.
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A synthwave highway racer where Jev suggests lanes, tactics and nitro while a per-frame governor watches the moving road.
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from the source
const questions = { recommended_lane: { type: "choice", instructions: "Select the safest forward lane that guarantees zero collision with oncoming traff...
A crisis-response simulation in which Jev helps decide where to send each team.
ACTUAL RECORDING12 SEC ↗
from the source
const response = await this.client.systemOne({ state: normalizeState(state), model: this.model, questions: toSdkQuestions(questions),});
A table-tennis game where Jev's answer is the paddle's target pixel and a tiny local servo simply moves there.
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from the source
return {"place": { "type": "choice", "instructions": ("The ball is coming toward your face at x=%.0f. Where should the CE... "when the ball arrives, so that the ball hits your face? Work out w... "will be at x=%.0f, then pick the position closest to it. Your padd...
Turns Jev's judgments into conversation by compiling a semantic plan into an English sentence.
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from the source
const CONFIDENCE: NoulQuestion = { id: "confidence", kind: "noul", prompt: "Can this message be responded to substantively, without inventing facts?",
A browser MuJoCo lab where Jev chooses instructions for individual robot ducks or a small swarm.
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from the source
questions: { intent: { type: "choice" as const, instructions: { question: "Which ONE eligible group intention should the four-robot simulator execut...
Replays the same restaurant evening under hand-written rules or Jev-selected service tours for a fair side-by-side comparison.
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from the source
return { model, state: { server: context.server, tasks }, questions: { service_tour: { t...
A ring-maze game that asks Jev for the best move from every cell, then colors each played or overruled step.
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from the source
// A POLICY can be asked for in parallel questions, because a policy is a// function of the cell alone. So: one question per cell — "standing at ring R,// sector S, which move begins the optimal route to the centre?" — with that// cell's own doors listed as the options. Every question is self-contained, so
Jev, briefly
A decision model, not a chatbot.
A chat model generates text token by token and hopes you parse it. Jev never generates a word. Your code sends the state of the world plus typed questions; Jev returns every answer in one parallel pass — typed values with calibrated probabilities and a confidence score your code can trust. About 70–500 ms end to end, $0.042 per million input tokens, output free. Trained with what TypeSafe calls Reinforcement Learning for Calibrated Decisions.
choice Pick one of these.
You define the options. Jev returns the chosen option, a probability for every option, and a confidence. The workhorse of routing, agents, and games — the answer space is always legal, so there is nothing to parse and nothing to hallucinate.
score Rate this on a rubric.
You describe ordered levels — say trivial / normal / critical. Jev returns the level, the probability of each, and a confidence. Scores turn fuzzy judgment (“how severe is this log line?”) into a number-free decision your code can branch on.
noul Is this statement true?
You assert a statement; Jev returns the probability that it is true — a noul. Moderation, verification, guardrails, “does this diff actually fix the bug?”: one question, one calibrated probability.
Official material lives at typesafe.ai and docs.typesafe.ai. JevMade is an independent community registry — not affiliated with or endorsed by TypeSafe AI.
Recurring lessons
Patterns that keep showing up.
One decision per tick
Games, drones, trading bots, and browser agents all converge on the same loop: serialize the state, ask one decisive question, act, repeat. Jev’s latency makes the loop feel instant — the model lives inside the control loop, not outside it.
Confidence as a gate
The answer says what; the confidence says whether to act. The most reliable entries threshold on confidence to route edge cases to a slower model or a human — automation with an honest escape hatch.
Shrink the choice space in code
Makers rarely ask Jev to pick from everything. Local tactics prune 225 gomoku moves to ~40; DOM filters turn a page into an element table; code narrows options, Jev judges within them.
Jev judges, LLMs talk
A recurring split: Jev makes every decision cheaply and instantly, and a small LLM is only invoked when a human-facing string must actually be written. Decision and generation are separate budgets.
Made something with Jev?
Send the link — repo, live demo, post, or video — plus a line on what it does and which primitives it uses. Every entry is verified against its primary source before it ships.
Submit your experiment → hello@JevMade.com