Exploring software engineering, RAG, generative AI, LLM systems and recommendation systems-one problem, experiment and engineering note at a time.
What is AI Genius?
AI Genius is my personal technical space for learning, building and documenting the engineering behind intelligent systems.
Strengthening the foundations of software engineering, algorithms, system design and AI/ML.
Turning concepts into implementations, experiments and eventually production-oriented systems.
Documenting what I learn, the problems I solve and the engineering decisions behind them.
Current Focus
I'm expanding my software engineering foundations while deepening my work in generative AI and RAG, with a growing interest in LLM and recommendation systems.
Algorithms & Data Structures
Object-Oriented Design
Testing & Clean Code
Generative AI
RAG & Retrieval
LLM Systems
ML Evaluation
Recommendation Systems
Ranking & Personalization
Scalability
Reliability
Learning Lab
A growing collection of structured Learning Paths that turns study into working intuition.
Engineering Notes
Technical notes on software engineering, AI/ML, system design and the problems I'm working through. Published on AI Genius and distributed through Substack.
Working through requirements, capacity estimation, short-code generation, caching, database scaling, and the reliability trade-offs involved in designing a URL shortener that handles hundreds of billions of mappings.
Read noteNewsletter
Subscribe through Substack when you want new notes delivered to you.
Who is behind AI Genius?
Software Engineer and ML Engineer working on reliable generative AI and retrieval systems.
Work with me
I'm interested in engineering roles where I can build reliable RAG and generative AI products and grow further into LLM infrastructure, retrieval, ranking and recommendation systems.