Everything we’ve published — page 13.
How to detect credential theft in AI agent harness traces
In May 2026, a malicious version of a popular VS Code extension spent 18 minutes in the marketplace…
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Phoenix at 10,000 stars on GitHub: How an open source AI observability project grew by following its community
Phoenix crossed 10,000 GitHub stars. Here is how the open-source AI observability project grew from a Jupyter notebook…
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Building the AI factory for self-improving agents: What’s new in Arize AX
Arize AX is adding managed agents, full-agent experimentation, expanded multimodal support, and Harness-as-a-Judge to help teams observe, evaluate,…
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Microsoft’s open trust stack runs on OpenInference
Microsoft's open trust stack for AI agents puts ASSERT and Agent Control Specification on top of OpenInference, connecting…
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The end of fine-tuning: Why evals, context, and traces matter more
Fine-tuning isn't dead, but the way most teams iterate on AI products has split in two. A tiny…
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AI benchmarks are breaking. Trace analysis is what comes next.
Models got smart enough to cheat their benchmarks, and outcome-only scores stopped measuring what we thought they measured.…
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Prompt Playground
A prompt playground offers a UI to experiment with prompt templates, input variables, LLM models and LLM parameters.…
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How the Hermes agent harness implements an open source architecture
Hermes from NousResearch is a strong open-source agent harness. This post examines how its runtime loop, context management,…
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The best eval harness for production AI and agents: A comparison
A practical comparison of production AI evaluation harnesses, including what to look for across instrumentation, evaluators, online evals,…
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How to build a better agent harness with traces and evals
Agents are easy to prototype and hard to improve. A repeatable loop of traces, evals, failed-span inspection, and…
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From production traces to better AI agents: Automating the LLMOps feedback loop
Production AI traces are the raw material for better evals, prompts, datasets, and fine-tuned models. This post shows…
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LangSmith alternatives for AI observability and LLM evaluation
Compare the top LangSmith alternatives for AI observability and evaluation, focusing on tools that support framework-agnostic tracing, production…
Read the guideDon’t ship vibes.
Arize gives AI teams observability and evals to understand and improve agent performance.
