LLM Observability: Cost Tracking and Quality Monitoring (Part 2 of 2)

Introduction: You can’t improve what you can’t measure. LLM applications are notoriously difficult to debug—prompts are opaque, responses are non-deterministic, and failures often manifest as subtle quality degradation rather than crashes. Observability gives you visibility into every LLM call: what prompts were sent, what responses came back, how long it took, how much it cost, […]

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Hybrid Search Implementation: Combining Vector and Keyword Retrieval

Introduction: Hybrid search combines the best of both worlds: the semantic understanding of vector search with the precision of keyword matching. Pure vector search excels at finding conceptually similar content but can miss exact matches; pure keyword search finds exact terms but misses semantic relationships. Hybrid search fuses these approaches, using vector similarity for semantic […]

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.NET AI Performance Optimization: Reducing Latency and Costs

Last year, I inherited a .NET AI application that was struggling. Response times averaged 2.3 seconds, costs were spiraling, and users were complaining. After three months of optimization, we cut latency by 87% and reduced costs by 72%. Here’s what I learned about optimizing .NET AI applications for production. Figure 1: .NET AI Performance Optimization […]

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GitHub Copilot Chat Transforms Developer Productivity: AI-Assisted Development Patterns for Enterprise Teams

Introduction: GitHub Copilot Chat, released in late 2023, represents a paradigm shift in AI-assisted development by bringing conversational AI directly into the IDE. Unlike the original Copilot’s inline suggestions, Copilot Chat enables developers to ask questions, request explanations, generate tests, and refactor code through natural language dialogue. After integrating Copilot Chat into my daily workflow […]

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