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Source channel @githubtrending · Post #15248 · Oct 25

#java#awesome#backend#computer_science#distributed_systems#high_level_design#hld#interview#interview_questions#scalability#system_design You can learn important system design concepts for free, covering topics like scalability, availability, CAP theorem, caching, databases, APIs, microservices, and distributed systems. This resource offers clear explanations, interview preparation guides, and practical design problems from easy to hard, helping you understand how to build reliable, scalable software systems. It also provides links to courses, books, newsletters, and videos to deepen your knowledge. Using these materials can improve your skills for system design interviews and real-world software architecture, making you more confident and effective in designing complex systems. https://github.com/ashishps1/awesome-system-design-resources

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@githubtrending · Post #15523 · 02/25/2026, 12:30 PM

#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow