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# GPT-5.6

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  1. Cohere Labs

    Coding agent teams don't need strong models everywhere: cheap planners nearly match an all-strong team

    Teams of coding agents generally beat a single agent at rebuilding programs, but at four to seven times the cost. A controlled study across 200 ProgramBench programs finds that putting cheaper models only on exploration and planning comes within 2.7 points of an all-strong-model team that delegates every stage, at roughly a fifth of that team's cost, because discovering the original program's behavior is the real bottleneck.

    Multi-agent systemCoding AgentsProgramBenchGPT-5.6
  2. OpenAI

    Ringg's AI agents handle 7M calls a month and resolve up to 65% of customer requests

    Ringg built an enterprise agent platform centered on GPT‑5.6 family models spanning voice, chat, WhatsApp, and the web, using an orchestration layer, knowledge retrieval, and multi-model routing to complete multi-step tasks across CRMs, ticketing, payment, and scheduling systems; it now handles more than 7 million connected calls each month, resolves up to 65% of routine customer inquiries without human involvement, reports an average customer CSAT of 4.8, and cut model costs by roughly 90% after migrating suitable real-time workloads from GPT‑4.1 to GPT‑5.6.

    OpenAI
    Ringg agent platformGPT-5.6Customer service automation

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