InLevel Up CodingbyGülden Bilgütay·Sep 11When Collaborative Filtering Has Nothing to Collaborate On: A SageMaker Fallback PatternCollaborative filtering has an attractive promise:
Prathamesh Sable·Aug 14Building a Flexible Recommendation Engine with Graph DB (Neo4j)How to build one recommendation system that can work with different types of items instead of creating a new algorithm every time.
Sanjeev·Jun 28Stoxify — recommending you stocksAs usual my hunger for creating any new projects does not start with my passion towards the subject, but rather feeling the presence of…
shashank upadhyay·Jun 26From perfect demos to disappointing deployments: hidden reason recommendation system fail in fieldMost recommendation systems optimize for preference, not timing. And how calendar-aware AI fixes the gap.
Jayasagar·Mar 1The 3-Layer Pipeline — When Data Lies and Truth Lives in the GapsBuilding recommendation systems that trust all signals — and know when to trust which
Jayasagar·Feb 24CLAUDE.md at 36,000 CharactersWhat I learned about scaling AI context across 75 sessions and 27,500 lines of production code
Dr. Kiruthiga·Feb 23Are Recommendation Engines Shrinking Your Mind?What if hyper-personalization is slowly limiting how deeply and widely you think?
PersonaClick Blog·Feb 3How Product Recommendation Systems EvolvedProduct Recommendation Engines as Interpreters
Ragy Ashraf·Dec 29, 2025Spotify’s New AI DJ: Architecture and Technical OverviewDec 29, 2025 By Ragy Ashraf | Software Engineering Student, SAIT | https://ragy.me
