After two decades of building enterprise systems, I’ve witnessed numerous technology waves—from SOA to microservices, from on-premises to cloud-native. But nothing has matched the velocity and transformative potential of generative AI. The challenge isn’t whether to adopt it; it’s how to do so without creating technical debt that will haunt your organization for years. The […]
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
Vector Databases: Why They Matter in the Age of Generative AI
After two decades of architecting enterprise systems and spending the past year deeply immersed in Generative AI implementations, I can state with confidence that vector databases have become the cornerstone of modern AI infrastructure. If you’re building anything involving Large Language Models, semantic search, or Retrieval-Augmented Generation (RAG), understanding vector databases isn’t optional—it’s essential. This […]
Read more →Tips and Tricks – Cache Dependencies in GitHub Actions
Speed up CI builds by caching package manager dependencies between runs.
Read more →Tips and Tricks – Optimize Re-renders with React.memo and useMemo
Prevent unnecessary component re-renders by memoizing components and computed values.
Read more →Tips and Tricks – Debounce Search Inputs for Better Performance
Prevent excessive API calls by debouncing user input in search fields.
Read more →LLM Cost Optimization: Reducing API Spend Without Sacrificing Quality
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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