Overview

Automatically detect, cluster, and fix errors in your AI agent traces with Error Feed.

What it is

Error Feed is an intelligent error analysis system built into the FutureAGI platform. It automatically monitors traces from your Observe projects, identifies issues in agent execution, groups similar errors into clusters, and surfaces actionable recommendations — all without any additional configuration.

Once traces start flowing in, Error Feed picks them up according to a configurable sampling rate, scores them across four key metrics, and presents findings directly in the platform UI alongside the trace tree.

Error Feed overview

Purpose

  • Error Detection — Automatically identifies and categorizes errors in agent execution, pointing out root causes and suggesting immediate fixes.
  • Cluster Grouping — Groups similar errors from multiple traces into named clusters so you can spot recurring problems at a glance.
  • Scoring — Evaluates every analyzed trace across four metrics: Factual Grounding, Privacy & Safety, Instruction Adherence, and Optimal Plan Execution (each scored out of 5).
  • Recommendations — Provides both an immediate fix (minimal functional fix) and a long-term recommendation (robust architectural fix) per error.
  • Pattern Detection — Tracks error trends over time — increasing, decreasing, or stable — so you know which problems are getting worse.
  • Zero Config — Works automatically on any Observe project; no extra instrumentation or setup required.

Supported Integrations

Error Feed works with any integration that sends traces to an Observe project. The following are currently supported.

LLM Models: OpenAI, OpenAI Agents SDK, Vertex AI (Gemini), AWS Bedrock, Mistral AI, Anthropic, Groq, Together AI, Google ADK, Google GenAI, Portkey

Orchestration Frameworks: LlamaIndex, LlamaIndex Workflows, LangChain, LangGraph, LiteLLM, CrewAI, Haystack, Autogen, PromptFlow, Vercel, Pipecat

Other: DSPy, Guardrails AI, Hugging Face smolagents, Ollama, Instructor, MCP

Note

Error Feed requires zero configuration. Once you start sending traces to a FutureAGI Observe project, it automatically picks up traces and generates insights. Use the sampling rate to control what percentage of traces are analyzed.

Getting started with Error Feed

Using Google ADK

Walk through a full Google ADK example and see Error Feed scores and insights in action.

Taxonomy

Explore the full error taxonomy: categories, subcategories, and what each error type means.
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Questions & Discussion