Beyond Rule-Based Systems: Building a Resilience Layer for Reliable Production LLMs
Static rules can’t keep up with evolving threats and unpredictable AI behavior.
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Key Takeaways
for AI Leaders & Technical Teams
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Why rule-based filters fail against evolving LLM threats like hallucinations, prompt attacks, and cost spikes.
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How a resilience layer delivers real-time monitoring, anomaly detection, and automated recovery, ensuring every AI output is reliable and compliant.
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Real-world examples of legal, financial, and reputational fallout from missed AI failures.
How lightweight detection models catch subtle hallucinations and policy violations at runtime.