Debugging Claude Multi-Agent Systems: Loops & Bad Tool Calls
Catch infinite loops, wrong tool calls, and hallucinated arguments in Claude multi-agent systems with the right tracing and guardrails.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Catch infinite loops, wrong tool calls, and hallucinated arguments in Claude multi-agent systems with the right tracing and guardrails.
What to put in a Claude agent's context and what to leave out — a practical guide to prompt and context design for reliable multi-agent systems.
Wire MCP servers into Claude multi-agent systems the right way: scoped auth, tight schemas, actionable errors, and idempotency that survives retries.
Reusable patterns for multi-agent systems on Claude: role-scoped prompts, return contracts, tool schemas, context budgeting, and clean state passing.
Step-by-step guide to building a working multi-agent system with Claude — decomposition, subagent dispatch, return contracts, validation, and synthesis.
How multi-agent systems fit together on Claude: orchestrators, isolated subagent contexts, message passing, and where the token cost actually goes.
How agentic AI systems transform business intelligence by autonomously querying databases, generating visualizations, and delivering insights without manual intervention.
Learn how AI tutoring agents adapt to individual student learning styles, pace, and knowledge gaps to deliver personalized education at scale across the US, India, Europe, and Asia-Pacific edtech markets.
Learn how engineering teams are integrating AI into their code review workflows to catch bugs earlier, reduce review cycle time, and measurably improve code quality in production.