Arize Phoenix released evaluation support for Pytest and Vitest/Jest, allowing developers to write LLM evaluations as ordinary tests. The integration records LLM traces and metrics like cost and laten…
InfoQ opened enrollment for its AI Security & Privacy Engineering Program, a five-week online cohort for senior engineers in regulated industries, starting August 26 and October 14. The program, facil…
SigNoz, Langfuse, and Arize Phoenix lead the top LLM observability tools in 2026, offering capabilities such as full-stack monitoring, agent workflow debugging, and drift detection. The tools converge…
A developer running reliability for a small team shipping LLM features compared six Langfuse alternatives—Helicone, Arize Phoenix, LangSmith, Braintrust, Laminar, and Future AGI traceAI—focusing on bo…
A developer built an open-source PII firewall for LLMs after accidentally sending a customer's credit card number to OpenAI during a benchmark test. The tool, called LLM Governance Engine, intercepts …
A developer evaluated six LLM observability tools—Langfuse, Helicone, Arize Phoenix, LangSmith, Braintrust, and Laminar—for their ability to monitor the audio layer in voice agents, not just LLM calls…
A company shipped an AI chat feature to production but found the model was a black box, unable to answer basic operational questions about why answers were good or bad. The team added an observability…
Arize AI cofounder and CPO Aparna Dhinakaran demonstrated a method for improving AI agents by building a better harness around the model, using traces and evals to debug failures. In a live demo with …
At the AI Conf 2026 in Moscow, the industry has fully shifted away from traditional machine learning toward agents, RAG, and voice systems, with agent orchestration emerging as the new infrastructure …
Arize Phoenix is evolving from an observability tool designed for human-in-the-loop workflows into a context platform for both humans and AI agents. The shift comes as coding agents increasingly write…