AI Application Engineering Journey: From Prompts to Production Systems
This series documents the journey of building real-world AI applications using local LLMs, prompt engineering, structured outputs, memory, RAG, tool calling, workflows, and agents. Instead of focusing on training foundation models, we explore how modern AI products are engineered, integrated, and deployed to solve real-world problems. From basic LLM interaction to production-ready AI systems, each article builds a practical understanding of the AI application layer.
Articles in this series
Tech Insights & Engineering Articles
Explore technical articles, software architecture deep dives, clean code tutorials, and computer science explorations from my journey.
Basic Interaction with LLMs — The Concepts Every AI Engineer Must Learn First
When people start learning AI Engineering, they often jump directly into topics like RAG, Agents, Vector Databases, and …
Understanding Ollama: Installing, Managing, and Running Local AI Models
One of the biggest misconceptions beginners have when learning AI engineering is thinking that an AI model is the same t…
Understanding LLMs, Ollama, and Inference
Before building AI applications, we need to understand three fundamental concepts: