OpenAI's GPT-Realtime-2 guide sharpens voice agents
OpenAI's prompting guide shows how to build better voice applications with GPT-Realtime-2 by tuning reasoning effort, using short preambles, defining tool behavior, handling unclear audio, capturing exact entities, and preserving state across longer sessions. The emphasis is on prompt precision and recovery behavior rather than generic helpfulness, which signals that production voice UX now depends as much on orchestration as on model quality.
Hot take: this is more of a practical operating manual than a flashy model announcement, and that makes it more useful for serious builders.
- –Start with `reasoning.effort: low`; the guide frames higher effort as something to earn, not the default.
- –Preambles are treated as a product feature: useful for noticeable work, but harmful when they create fake chatter or delay.
- –The strongest advice is around control surfaces, not style: define when to act, ask, confirm, retry, or escalate.
- –Unclear audio handling is conservative by design: don’t guess, don’t infer missing words, and don’t burn hidden reasoning on noise.
- –Exact entity capture is a core voice problem here; the guide pushes one-at-a-time collection and explicit confirmation for high-precision values.
- –Long-session behavior is about structure, not brute-force context dumping: separate current state, authoritative sources, and background.
DISCOVERED
1h ago
2026-05-07
PUBLISHED
1h ago
2026-05-07
RELEVANCE
AUTHOR
OpenAIDevs