Best sites for advanced engineers

For advanced software, systems, and hardware engineers who have moved past basic syntax and intermediate tutorials, the best platforms focus on deep internal mechanics, distributed systems design, and real-world production trade-offs. Here is a curated list categorized by engineering discipline and learning goal:

1. Real-World Systems & Internal Mechanics CodeCrafters (codecrafters.io) Best For: Systems, infrastructure, and backend engineers looking to build complex tools from scratch. Why It’s Essential: Instead of solving algorithmic puzzles, you build actual infrastructure tools from the ground up—including a Redis engine, Git CLI, SQLite database, Docker runtime, or BitTorrent client in your local IDE. LWN.net (Linux Weekly News) Best For: Low-level developers, kernel engineers, and systems programmers. Why It’s Essential: Unmatched, highly detailed coverage of kernel development, memory management, Linux sub-systems, security vulnerabilities, and open-source infrastructure news.
2. System Architecture & High-Scale Engineering InfoQ (infoq.com) Best For: Software architects, principal engineers, and engineering directors. Why It’s Essential: Focuses heavily on production architecture, microservices evolution, domain-driven design, and enterprise tech strategy. It features real case studies written by practicing staff-level engineers. ByteByteGo & High Scalability (bytebytego.com / highscalability.com) Best For: Distributed systems engineering and high-throughput architecture. Why It’s Essential: Provides visual breakdowns of how platforms handle millions of requests per second, covering real production trade-offs across storage, messaging, caching, and data pipelines. Big Tech Engineering Blogs (e.g., Netflix, Cloudflare, Uber, Stripe) Best For: Learning production engineering at extreme scale. Why It’s Essential: Reading primary engineering blogs (or aggregated feeds via GitHub repos like kilimchoi/engineering-blogs) reveals how top engineering teams handle edge cases, live database migrations, multi-region failovers, and low-latency optimizations.
3. AI Research, CS Fundamentals & Papers Papers with Code (paperswithcode.com) Best For: AI/ML practitioners, researchers, and algorithm engineers. Why It’s Essential: Tracks the latest machine learning research papers alongside their official, production-ready implementation code and evaluation benchmarks. ACM Digital Library & IEEE Xplore Best For: Hardware, database, security, and protocol design engineers. Why It’s Essential: The foundational source for seminal CS research papers—covering everything from Paxos/Raft consensus protocols to modern CPU architectures and distributed storage engines. Which specific domain (e.g., distributed systems, kernel development, hardware, AI/ML) are you aiming to dive deepest into? To see how senior staff and principal engineers approach trade-offs and complexity, check out this discussion on What Top Tier Software Architects Do Differently. This talk provides practical mental models for navigating high-level architecture decisions and managing risk in large-scale systems.