Introduction: LLM APIs fail in ways traditional APIs don’t—rate limits, content filters, malformed outputs, timeouts on long generations, and model-specific quirks. Building resilient LLM applications requires comprehensive error handling: retry logic with exponential backoff, fallback strategies when primary models fail, circuit breakers to prevent cascade failures, and graceful degradation for user-facing applications. This guide covers […]
Read more →Month: May 2024
Data Storytelling: How to Communicate Insights Effectively
The Presentation That Changed Everything Early in my career, I spent three weeks building what I thought was a brilliant analytics dashboard. It had every metric imaginable, interactive filters, drill-down capabilities, and real-time data feeds. When I presented it to the executive team, I watched their eyes glaze over within the first five minutes. The […]
Read more →LLM Rate Limiting and Throttling: Building Resilient AI Applications
Introduction: LLM APIs have strict rate limits—requests per minute, tokens per minute, and concurrent request caps. Hit these limits and your application grinds to a halt with 429 errors. Worse, aggressive retry logic can trigger longer cooldowns. Proper rate limiting isn’t just about staying under limits; it’s about maximizing throughput while gracefully handling bursts, prioritizing […]
Read more →Generative AI Services in AWS
The moment I first deployed a production generative AI application on AWS, I realized we had crossed a threshold that would fundamentally change how enterprises build intelligent systems. After spending two decades architecting solutions across every major cloud platform, I can say with confidence that AWS has assembled the most comprehensive generative AI ecosystem available […]
Read more →LLM Observability: Monitoring AI Applications in Production
Last month, our LLM application started giving wrong answers. Not occasionally—systematically. The problem? We had no visibility. No logs, no metrics, no way to understand what was happening. That incident cost us a major client and taught me that observability isn’t optional for LLM applications—it’s survival. ” alt=”LLM Observability Architecture” style=”max-width: 100%; height: auto; border-radius: […]
Read more →Generative AI in Healthcare: Revolutionizing Patient Care
The first time I witnessed a generative AI system accurately synthesize a patient’s complex medical history into actionable clinical insights, I understood we were entering a new era of healthcare delivery. After two decades of architecting enterprise systems across industries, I can say that healthcare presents both the greatest challenges and the most profound opportunities […]
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