Do these 3 things before closing this tab:
1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesJev is a typed decision model/API component that an AI agent can call for bounded judgments—not a complete agent. The surrounding application supplies context and a focused question; Jev returns structured results such as a choice, score, or confidence signal. The application’s code then decides whether to continue, ask a person to review, or take another permitted step. Jev does not itself browse, call tools, run an agent loop, or write a user-facing answer.
How Jev fits into an AI agent
Think of an agent as three cooperating parts: a generative model for open-ended reasoning and language, Jev for a defined judgment, and ordinary application code for policy and workflow enforcement. Jev’s API documentation describes it as a component, not a replacement for the agent’s main model. Jev API documentation
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The division matters: a model’s structured answer can inform a decision, but it does not grant permission to perform an action. Keep deterministic checks in code, and use a model where interpreting unstructured input is genuinely useful.
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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →What happens in a Jev decision
- Provide relevant state. The calling application can send text, a JSON object, or an array of related text items. Include the context needed for the judgment and leave out unrelated or sensitive information. Jev AI developer documentation
- Ask a bounded question. Use a predefined
Choiceset when the answer should select a route or action, aScorequestion for an ordered rubric, orNoulfor a yes/no-style criterion. Multiple focused questions can use the same state. Jev AI developer documentation Jev question types - Read the typed result. Jev returns structured decision information, such as a choice, probability, score, or confidence field, as described by its API documentation. Treat these as inputs for the application, not as instructions to execute. Jev API documentation
- Apply application-owned rules. The calling code sets thresholds, enforces business and safety policies, and can route uncertain cases to human review.
- Continue the agent loop outside Jev. The agent harness or service decides what comes next, calls tools, and drafts any response. Jev does not perform those tasks. Jev agent architecture explanation
Good uses—and where Jev is not enough
Jev is suited to judgments that can be expressed as a constrained answer space or rubric. The documentation and architecture guides describe cases such as routing a request, choosing among available tools or models, scoring urgency or risk, flagging an action for review, assessing whether supplied evidence supports a claim, and checking whether a task appears complete. Jev API documentation Jev AI developer documentation Jev architecture guide
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It can judge only what the application provides. For example, it cannot assess a command’s risk if the command text and relevant context are missing. Nor is a judgment about supplied evidence a substitute for retrieving sources or verifying them independently. Jev agent architecture explanation
Use the surrounding generative model or code when the task requires free-form prose, tool arguments beyond the defined choices, or a multi-step plan. A fixed choice set helps keep outputs structurally predictable, but it cannot ensure the selected option is correct. Add an other, unknown, or review route if the listed answers may not fit. Jev AI developer documentation Jev question types
Keep authorization and execution outside Jev
The API documentation puts the safety boundary plainly: “Treat probabilities as signals, not authorization.” The application—not a probability or confidence value—must govern authorization, irreversible actions, and final execution. Keep API keys server-side, and use human review for uncertain, novel, or high-impact cases, as the project documentation advises. Jev API documentation Jev AI developer documentation
- Do not treat a valid option as proof that it is the right option.
- Do not let a model result bypass code-owned policy or permission checks.
- Do not assume omitted facts can be inferred reliably; provide the information needed for the decision.
Jev is a component, not the whole product experience
When referring to Jev itself, “Jev decision model” or “Jev API” is more precise than “Jev agent.” The term “agent” may describe an application built around the component, but the decision model is called by a conventional agent that manages the wider task.
Also distinguish the Jev AI project from the underlying model provider. The project documentation says its app is not the official product site for the model. The available documentation here does not establish current provider-specific authentication, schemas, model identifiers, pricing, or availability; confirm those details in TypeSafe’s current primary documentation before integrating. Jev agent architecture explanation Jev project and provider references
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