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Practical articles on building reliable AI systems - from LLMs, RAG and agents to evaluation, reliability, security, cost and production operations.
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Discover how AI agents are moving beyond chatbots to plan tasks, use tools, and complete real-world workflows. Explore practical banking applications, from payment investigations to fraud detection, and learn why security, reliability, and human judgment remain essential for trustworthy AI automation.
Learn what Retrieval-Augmented Generation (RAG) is, why it is needed, and how retrieval helps large language models answer questions using relevant external knowledge.
From smarter models to production failures: what the latest AI releases reveal about reliability, cost, security, and the engineering challenges benchmarks cannot measure.
An introduction to Agentic AI as a new paradigm for building AI systems that can pursue goals, make decisions, interact with their environment, and act with varying degrees of autonomy.
An introduction to AI engineering, how it differs from traditional software engineering, and what it takes to build production-ready AI systems.
How 15+ years in enterprise banking evolved into building production-ready AI systems using Machine Learning, Generative AI, LLMs, RAG, and Agentic AI.
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