llm-observability

Tag

Cards List
#llm-observability

How do you all actually get from a failed eval to a prompt fix that holds in prod?

Reddit r/AI_Agents · 2026-07-20

A discussion comparing LLM evaluation and observability tools (LangSmith, Weave, Phoenix, Braintrust, Galileo, Opik) for fixing prompt failures and introducing an open-source platform that integrates the full eval-to-fix loop on a single trace.

0 favorites 0 likes
#llm-observability

@ArizePhoenix: Phoenix's agent PXI can propose annotation categories, annotate traces en mass, and even suggest fixes based on pattern…

X AI KOLs Timeline · 2026-07-13 Cached

Introduces how to use Phoenix's Pixie assistant to automatically classify error spans, batch annotate, and generate system prompt repair suggestions based on failure patterns.

0 favorites 0 likes
#llm-observability

@rohanpaul_ai: Thier Github with 4.2k stars https://github.com/latitude-dev/latitude-llm…

X AI KOLs Following · 2026-06-23 Cached

Latitude is an open-source AI Agent Monitoring tool that provides issue detection, traces, and evals for LLM-based agents, similar to Sentry for AI.

0 favorites 0 likes
#llm-observability

@LangChain: When the EU AI Act goes into effect, compliance will become an ongoing measurement obligation. With LangSmith, you can …

X AI KOLs Following · 2026-06-23 Cached

LangChain's LangSmith enables developers to use tracing as compliance evidence for the EU AI Act, with customizable evaluators for bias, hallucination, toxicity, accuracy, and adversarial inputs.

0 favorites 0 likes
#llm-observability

langfuse/langfuse

GitHub Trending (daily) · 2026-04-22 Cached

Langfuse open-sources its LLM engineering platform to offer self-hosted tracing, analytics, and evaluation tools for production AI applications.

0 favorites 0 likes
← Back to home

Submit Feedback