Field notes on agentic AI, RAG, and shipping ML to production. I also write regularly on Medium.
Published in Towards AIA practical walkthrough of prompt engineering fundamentals — the anatomy of a good prompt (role, task, context, constraints), good-vs-bad prompt examples side by side, real-world use cases across industries, and Python code for building prompt templates and calling an LLM API.
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Demos showcase the happy path, but production is everything beyond it — hallucinations, tool failures, infinite loops, and context explosion. A look at why reliability, not autonomy, is what separates agents that ship from agents that stay demos.
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A backend engineer's field notes on applying Retrieval-Augmented Generation to FAQ search in vacation rentals — turning scattered property details, house rules, and policies into fast, accurate answers for guests.
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We predict a house's sale price from features like size and number of rooms — treating those attributes as input and price as the output of a machine learning model.
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