Month: October 2024

Understanding Modern IT Methodologies: A Comprehensive Comparison

Posted on by Nithin Mohan TK 6 min read

After two decades of building and operating enterprise systems, I’ve watched the IT operations landscape transform dramatically. What started as siloed development and operations teams has evolved into a rich ecosystem of methodologies, each addressing specific organizational challenges. In this comprehensive guide, I’ll share my perspective on four dominant approaches: DevOps, DevSecOps, Site Reliability Engineering […]

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LLM Evaluation: Metrics, Benchmarks, and A/B Testing

Posted on by Nithin Mohan TK 12 min read

Introduction: Evaluating LLM outputs is challenging because there’s often no single “correct” answer. Traditional metrics like BLEU and ROUGE fall short for open-ended generation. This guide covers modern evaluation approaches: automated metrics for specific tasks, LLM-as-judge for quality assessment, human evaluation frameworks, A/B testing in production, and building comprehensive evaluation pipelines. These techniques help you […]

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LLM Cost Optimization: Reducing API Spend Without Sacrificing Quality (Part 1 of 2)

Posted on by Nithin Mohan TK 12 min read

Introduction: LLM API costs can spiral quickly—a chatbot handling 10,000 daily users at $0.01 per conversation costs $3,000 monthly. Production systems need cost optimization without sacrificing quality. This guide covers practical strategies: semantic caching to avoid redundant calls, model routing to use cheaper models when possible, prompt compression to reduce token counts, and monitoring to […]

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

Posted on by Nithin Mohan TK 14 min read

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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.NET AI Performance Optimization: Reducing Latency and Costs

Posted on by Nithin Mohan TK 7 min read

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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