Statewave Guide — Day 3: True is not the same as relevant

Описание и применение

Внедрение граф‑ориентированного подхода в Statewave Guide повысило достоверность AI‑генерируемых заявлений о продукте с 20 % до 95 %, устранив неверные утверждения о функциях и сохранив безопасность.

Задача

Ensuring AI-generated product claims are both factually correct and contextually relevant to the specific feature being queried.

Результат

The graph‑driven workflow improved verifiable claim yield from ~20% to 95% and eliminated wrong‑feature claims, demonstrating that context ownership is essential for safe AI product knowledge generation.

Рабочий процесс

• 1. Build application graph with features, routes, services, and relationships.
• 2. Identify deterministic claim opportunities within the graph.
• 3. Pass these opportunities to the model to add product meaning.
• 4. Verify claims against evidence and feature scope.
• 5. Iterate to improve claim yield and safety.

Доказательства

Verified claim yield went from roughly 20% → 95%.

Источник

Wrong-feature claims went to 0.

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The model found the right evidence about 89% of the time… but only turned it into a verifiable product claim about 20% of the time.

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Truth is not enough. Context owns truth.

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