Context Engineering: The Forgotten Architecture of LLM Systems I’ve spent $340K learning that context management is the actual product, not the model. Everyone obsesses over which model to use, h...
A practitioner's guide to understandingwhat actually works in the real world ML system.
How to Augment LLMs with Custom Data.
A practitioner's guide to understanding, detecting, and fixing model drift in real-world production systems.
My List 100 A living, evolving list of dreams, experiments, and milestones. Personal Growth & Health Build a consistent sleep cycle Reach and maintain my ideal weight Lower blood pre...
Part 4: Building a Recommendation Engine Using Embeddings (PyTorch Edition) In this part, we’ll take a hands-on deep dive into building a recommendation engine using user and item embeddings in Py...
User Embeddings Part 3: Applications and Real-World Impact In the previous parts of this series, we understood what user embeddings are, how they’re created, and how models learn to represent user...
Flowing Against the Ocean: A Reflection on Persistence There’s something profoundly exhausting about going against the tide. When the world pushes you in celebrating strength, abundance, and ease,...
In the first part, we explored the fundamentals of user embeddings and how they fuel personalized recommendations. This follow-up dives deeper into the engineering, challenges, and ethics behind re...
Introduction In the world of modern machine learning and recommendation systems, user embeddings are the quiet yet powerful drivers behind how platforms like TikTok, Netflix, Amazon, and Spotify s...