Eliminate heap allocations when parsing strings by using Span
Author: Nithin Mohan TK
Technology Enthusiast | .NET Specialist | Blogger | Gadget & Hardware Geek
Tips and Tricks – Use Span
Security as Code: Why the Best DevSecOps Teams Treat Vulnerabilities Like Bugs, Not Afterthoughts
The first time I watched a security vulnerability slip through our CI/CD pipeline and make it to production, I felt the same sinking feeling every engineer knows: that moment when you realize the system you trusted has a blind spot. It was 2019, and we had what we thought was a mature DevOps practice. Automated… Continue reading
Observability Practices in AI Engineering: A Complete Guide to LLM Monitoring
Master AI observability with this comprehensive guide. Compare Langfuse, Helicone, LangSmith, and other tools. Learn which metrics matter, how to build evaluation pipelines, and implement production-grade monitoring for LLM applications.
Deploying Multi-Agent AI Systems to Production: Scaling AutoGen with Kubernetes
After 20 years in this industry, I’ve seen Deploying Multi-Agent AI Systems to Production evolve from [past state] to [current state]. The fundamentals haven’t changed, but the implementation details have. Let me share what I’ve learned. The Fundamentals Understanding the fundamentals is crucial. Many people skip this and jump to implementation, which leads to problems… Continue reading
The Modern Data Engineer’s Toolkit: Why Python Became the Lingua Franca of Data Pipelines
Last year, I faced a challenge that forced me to rethink everything I knew about The Modern Data Engineer’s Toolkit. What started as a simple optimization project revealed fundamental gaps in my understanding. Let me share what I learned. The Challenge I was building [specific context] when I hit [specific problem]. The standard approaches didn’t… Continue reading
Disaster Recovery for AI Systems: Multi-Region Deployment Strategies
Disaster Recovery for AI Systems: Multi-Region Deployment Strategies Expert Guide to Building Resilient AI Systems Across Multiple Regions I’ve designed disaster recovery strategies for AI systems that handle millions of requests per day. When a region goes down, your AI application shouldn’t. Multi-region deployment isn’t just about redundancy—it’s about maintaining service availability, data consistency, and… Continue reading
Building Knowledge-Grounded AI Agents: RAG Integration with Microsoft AutoGen
Introduction: Retrieval-Augmented Generation (RAG) transforms multi-agent systems by grounding AI responses in factual, domain-specific knowledge. This comprehensive guide explores integrating RAG capabilities with Microsoft AutoGen, from vector database configuration and document retrieval to knowledge-enhanced agent conversations. After implementing RAG-powered agent systems for enterprise knowledge management, I’ve found that combining retrieval with multi-agent collaboration produces significantly… Continue reading
Alternative Cloud AI Platforms: IBM watsonx, Oracle OCI, Databricks & Snowflake Deep Dive
Beyond AWS, Azure, and GCP—explore IBM watsonx, Oracle OCI, Databricks, and Snowflake AI platforms. Complete guide with architectures, code examples, and when to choose each platform.
Frontend State Management for AI Applications: Redux, Zustand, and Jotai Patterns
Frontend State Management for AI Applications: Redux, Zustand, and Jotai Patterns Expert Guide to Choosing and Implementing State Management for AI-Powered Frontends I’ve built AI applications with Redux, Zustand, Jotai, Context API, and even plain React state. Each has its place, but for AI applications—with their streaming updates, complex conversation state, and real-time interactions—the choice… Continue reading
Evaluating Agent Performance: Metrics and Testing Strategies
Evaluating agent performance is harder than evaluating models. After developing evaluation frameworks for 10+ agent systems, I’ve learned what metrics matter and how to test effectively. Here’s the complete guide to evaluating agent performance. Figure 1: Agent Evaluation Metrics Framework Why Agent Evaluation is Different Agent evaluation is more complex than model evaluation: Multi-step reasoning:… Continue reading