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Building AI Decision Systems with Jev: A Practical Guide to Typed Outputs, Confidence Thresholds, and Reliable Workflow Automation
Paperback
Publisher: Independently Published
Published: Oct 27 2026
Pages: 206
Weight: 0.81
Height: 0.44 Width: 7.00 Depth: 10.00
Language: English
Inside, you will explore:
- Define clear decision contracts and choose appropriate categorical, scoring, and binary questions.
- Prepare evidence snapshots that preserve provenance, missingness, chronology, and freshness.
- Validate responses and distinguish integration failures from errors of judgment.
- Apply confidence thresholds, abstention rules, and monitored human-review paths.
- Evaluate routing quality, coverage, error costs, and the workload left for reviewers.
- Control authorized actions using version checks, durable state, idempotency, security boundaries, and operational monitoring.
This book is for software developers and AI engineers with basic knowledge of programming, JSON, and HTTP who want a disciplined way to integrate text-based model decisions into applications. It emphasizes bounded authority and measurable behavior rather than guaranteed accuracy or automatic success. Get your copy and start building a decision architecture that makes uncertainty visible and keeps automation under control.
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