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Instrument once against the OpenTelemetry GenAI conventions and your LLM traces become portable: the same spans flow to Langfuse, Phoenix, and Honeycomb through one Collector, with zero code changes when you switch. Here's the copy-paste setup.
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Vendor needle-recall numbers tell you nothing about where your agent breaks. This does: a small harness that inserts a known fact at varying depths and lengths, asks a non-lexical question, and shows you the exact window size where accuracy falls off a cliff.
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The Wire
The July release adds message-injection middleware — host code or a tool can drop a message into a live run and have it picked up on the next model call. Skills also left experimental. Here's what actually changed and why the mid-turn hook matters for long-running agents.
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Langfuse's scheduled blob exports now write Apache Parquet, not just CSV/JSON. That removes the cast-every-column step between your traces and a warehouse — here's the exact config, a DuckDB query that runs in one line, and the cost-column gotcha to know before you rely on it.
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Both ship on the same runtime — middleware is sugar over a LangGraph graph. The decision isn't which framework; it's which layer. Here are the real hooks, the real node API, and a clean rule for choosing.
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When an agent takes a consequential action, 'trust me' isn't an answer. Here's a copy-paste pattern for a decision record that captures inputs, the rules that fired, the model's rationale, and any human override — so you can replay any decision months later and prove exactly why.
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