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A practitioner's honest breakdown of building an AI report-generation agent, explaining that 90% of the code exists to handle silent, confident model failures and ensure reliability in production.
This paper presents a comprehensive 33-class taxonomy of recurrent distortion patterns (heuristic parasites) in LLM outputs, along with operational definitions, recognition criteria, and a reproducible measurement protocol (PPE) for quantifying behavioral degradation across conversations.
A developer building an AI legal assistant for a German law firm details seven specific LLM citation failure modes and the prompt-engineering fixes used to meet strict legal citation standards.
Researchers apply contrastive LRP-based attribution to analyze why LLMs fail on realistic benchmarks, finding the method gives useful signals in some cases but is not universally reliable.