ErrorLens: LLM Debugging & Insight Platform
Developers building LLM‑powered apps struggle with vague, anthropomorphic error terms like 'hallucinations', making it hard to pinpoint root causes and optimize performance. ErrorLens delivers a machine‑centric error taxonomy, real‑time diagnostics, and actionable insights that shift the focus from code to data and integration bottlenecks, enabling faster, more reliable deployments.
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Raw PostsComment on: The bottleneck was never the code
The difference is in the kind of errors machines make compared to ones that humans make.It’s frustrating we’re using anthropomorphic concepts like hallucinations when describing LLM behaviors when the fundamental units o