Topic
CrewAI & AutoGen Multi-Agent Debugging
13 posts on crewai & autogen multi-agent debugging — part of developer tools on the n4n AI blog.
Why CrewAI crews get stuck in infinite loops
Practical guide to CrewAI infinite loop debugging: trace agent delegation, set timeouts, cap iterations, and fix prompt loops in multi-agent crews.
Tracing token usage across CrewAI agent chains
Learn how to implement tracing token usage in CrewAI agent chains with per-agent attribution using LangChain callbacks and OpenAI-compatible metering.
Logging AutoGen agent messages for debugging
Learn how to implement structured logging for AutoGen agent messages to debug multi-agent workflows, with runnable Python code and expected outputs.
How to unit test CrewAI agent tools
Learn practical steps for unit testing CrewAI agent tools with pytest, mocks, and schema validation to keep multi-agent pipelines reliable and debuggable.
How to trace AutoGen multi-agent conversations
Practical steps for tracing AutoGen multi-agent conversations: wrap the LLM client, hook messages, and export traces to JSONL or OTel with runnable Python code.
Fixing CrewAI agent output parsing errors
Practical guide to resolving CrewAI output parsing errors in multi-agent pipelines: enforce JSON schemas, build custom parsers, add retries with validation.
Debugging CrewAI task delegation errors
Practical steps to diagnose and fix CrewAI task delegation errors in multi-agent pipelines, from verbose logging to LLM fallback and isolated tests.
Debugging CrewAI agent handoff failures
Practical steps to diagnose and fix CrewAI agent handoff debugging issues: tracing context, validating outputs, and inspecting hierarchical delegation.
Debugging AutoGen group chat deadlocks
A practical, ordered path for AutoGen group chat deadlock debugging: reproduce in isolation, trace speaker selection, set round limits, and break I/O hangs.
Debugging AutoGen function calling failures
A practical, ordered path for AutoGen function calling debugging: from schema validation to agent loop tracing, logging, and fallback strategies.
Catching silent failures in CrewAI multi-agent pipelines
A practical guide to CrewAI silent failure detection: instrument agents, enforce output contracts, and build fallbacks to catch broken multi-agent pipelines.
Building observability dashboards for CrewAI crews
Learn to build a CrewAI observability dashboard with step callbacks, SQLite logging, and Streamlit to monitor multi-agent crews in production. A hands-on tutorial for engineers.
AutoGen vs CrewAI: debugging tools compared
A practitioner's head-to-head on AutoGen vs CrewAI debugging tools: capabilities, cost, latency, ergonomics, ecosystem, limits, and which to use.
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