Introduction: LLM agents extend language models beyond text generation into autonomous action. By connecting LLMs to tools—web search, code execution, APIs, databases—agents can gather information, perform calculations, and interact with external systems. This guide covers building tool-using agents from scratch: defining tools with schemas, implementing the reasoning loop, handling tool execution, managing conversation state, and […]
Read more →Author: Nithin Mohan TK
Hello Namaste! 👋🏻
I'm an accomplished Enterprise Solution Architect & Engineering Leader with 20+ years of progressive experience architecting, building, and scaling transformative enterprise solutions.
⚜️ Solution Architect / AI & Cloud 📌 Galway, Ireland
Building Chatbots with Personality: Using AI to Enhance User Experience
Over the past two decades of building enterprise software systems, I’ve watched conversational AI evolve from simple rule-based decision trees to sophisticated agents capable of nuanced, context-aware dialogue. Having architected chatbot solutions for financial services, healthcare, and e-commerce platforms, I’ve learned that the difference between a chatbot users tolerate and one they genuinely enjoy interacting […]
Read more →Prompt Template Management: Engineering Discipline for LLM Prompts
Introduction: Prompts are the interface between your application and LLMs. As applications grow, managing prompts becomes challenging—they’re scattered across code, hard to version, and difficult to test. A prompt template system brings order to this chaos. It separates prompt logic from application code, enables versioning and A/B testing, and makes prompts reusable across different contexts. […]
Read more →AI for Environmental Sustainability: Innovations and Applications
After two decades of building enterprise systems and watching technology evolve from mainframes to cloud-native architectures, I’ve witnessed few technological shifts as profound as the application of artificial intelligence to environmental challenges. What makes this intersection particularly compelling isn’t just the technical sophistication—it’s the urgency. Climate change, biodiversity loss, and resource depletion aren’t abstract problems […]
Read more →Exploring Anaconda AI Navigator: A Comprehensive Guide for Windows Users
When Anaconda released their AI Navigator tool, I was skeptical. After two decades of building data science environments from scratch, managing conda environments manually, and wrestling with dependency conflicts across dozens of projects, I wondered if yet another GUI tool could actually solve the problems that have plagued Python development for years. After six months […]
Read more →Multi-Cloud AI Strategies: Avoiding Vendor Lock-in
Multi-cloud AI strategies prevent vendor lock-in and optimize costs. After implementing multi-cloud for 20+ AI projects, I’ve learned what works. Here’s the complete guide to multi-cloud AI strategies. Figure 1: Multi-Cloud AI Architecture Why Multi-Cloud for AI Multi-cloud strategies offer significant advantages: Vendor independence: Avoid lock-in to single cloud provider Cost optimization: Use best pricing […]
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