Papers and resources that shaped my thinking as an engineer.
Attention Is All You Need
Vaswani et al.
Introduced the Transformer architecture that revolutionized NLP and became the foundation for models like GPT and BERT.
My Take: This paper changed how I think about sequence modeling. The self-attention mechanism is beautifully elegant.
Read Paper Designing Data-Intensive Applications
Martin Kleppmann
Comprehensive guide to building reliable, scalable, and maintainable data systems.
My Take: My go-to resource for understanding trade-offs in distributed systems. Every engineer should read this.
The Twelve-Factor App
Heroku
Methodology for building modern, scalable, maintainable software-as-a-service applications.
My Take: These principles have guided how I structure every production application I build.
Read Paper MapReduce: Simplified Data Processing
Dean & Ghemawat (Google)
Programming model for processing large data sets with parallel, distributed algorithm on clusters.
My Take: Understanding MapReduce helped me think about data parallelism and fault tolerance at scale.
Read Paper CAP Theorem
Eric Brewer
States that a distributed system can only guarantee two of three: Consistency, Availability, Partition tolerance.
My Take: Essential mental model for making architecture decisions in distributed systems.