Most multi-agent demos look impressive on stage. Then they hit production and fall apart. Here's the...
Most multi-agent demos look impressive on stage. Then they hit production and fall apart.
Here's the pattern: agents that "worked" in a Jupyter notebook start conflicting, retrying infinitely, or silently failing when other agents are involved.
The root cause isn't the LLM. It's the orchestration layer.
What Actually Breaks
No structured handoffs — Agents pass messages as raw strings. Context gets lost. Intent gets misread.
Error compounding, stale state, and context rot break multi-agent LLM pipelines. Learn the failure modes and design patterns that…
Most production AI agents don't fail because the model is bad. They fail because the infrastructure...
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The demo is impressive. ✅ The demo works in your environment, with your data, with you watching....
Have you ever seen an AI demo where five agents talk to each other, assign tasks, debate plans, write...
