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Envoy AI Gateway

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  1. From demo to production: what an agent harness actually adds

    The piece frames an agent as "model + harness" and splits the harness into a development half (memory, tools and MCP, retrieval, prompt orchestration) and an operations half (observability, evals, guardrails, routing, cost control, deployment and scaling) — capabilities the model itself does not provide. It then builds the same finance agent, FinBot, two ways: a managed Amazon Bedrock AgentCore Harness configured via CreateHarness/InvokeHarness calls, with per-session Firecracker microVMs, managed memory and automatic tracing; and a self-managed LangChain agent on the reader's own Kubernetes cluster behind the open-source Agent Router (formerly Envoy AI Gateway). The trade-offs come down to where provider credentials live, who carries the operational burden, and whether you pay a vendor bill or infrastructure plus engineering time.

    InfoQ 中文 AI&大模型 · 🔥 6

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