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@dimitarilievxo

Dimitar Iliev

@dimitarilievxo·North Macedonia·Joined October 2025

Building AI in the cloud. Lifting iron at the gym. Living for the after hours.

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Expert insights on Azure AI architecture and implementation. Real-world solutions for building intelligent enterprise systems.

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Dimitar Iliev's blogs

Dimitar on AIdimitaronai.com31 posts

About

Expert insights on Azure AI architecture and implementation. Real-world solutions for building intelligent enterprise systems.

Available for

Nothing here yet.

Dimitar Iliev's blogs

Dimitar on AIdimitaronai.com31 posts

Articles Comments

Recently published

DIDimitar Ilievindimitaronai.com·4d ago · 3 min read

System Design and Behavioral Intelligence - Book Review

Most system design books stop at diagrams and trade-offs. Most behavioral interview guides stop at STAR stories. This one argues — convincingly — that the two are inseparable, because interviewers (an

DIDimitar Ilievindimitaronai.com·Aug 14 · 3 min read

The Generative AI Career Masterplan - Book Review

The Generative AI Career Masterplan: A Systems-Thinking Guide to an AI-Driven Career There's no shortage of books promising to help you "future-proof" your career against AI. Most either drown you in

DIDimitar Ilievindimitaronai.com·Jul 19 · 3 min read

Classify and route your data using Content Understanding

Classification and splitting The analyzer concept has been expanded to include contentCategories and enableSegment, which let you classify and split the input data processed by your application. This

DIDimitar Ilievindimitaronai.com·Jul 8 · 2 min read

The Ultimate AI Guide for Linux Engineers - Book Review

If you're a Linux engineer trying to figure out where AI actually fits into your day-to-day work - not the hype, the actual workflow - this book delivers a solid, practical roadmap. It opens by ground

DIDimitar Ilievindimitaronai.com·May 25 · 2 min read

Building Agent-Powered Applications - Book Review

Building Agent-Powered Applications is the kind of book you wish existed when you first started trying to make sense of the LLM ecosystem. It opens with a grounded overview of ML and NLP fundamentals