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A Twitter thread listing the top 10 system design resources, including books, blogs, and frameworks, with a link to Martin Fowler's website for further reading.
This tweet shares 5 free and open-source GitHub projects, covering practical resources for AI side hustles, programmer side businesses, passive income, etc., encouraging users to leverage the AI era to quickly improve themselves.
Lists 50 useful websites often not appearing in Google search results, covering free books, papers, image processing, security tools, coding aids, etc., helping users expand their internet usage.
Awesome Robotics is a curated GitHub list of robotics resources—simulators, libraries, papers, and more—organized by categories like simulation, ROS, ML, and perception. It's open-source under Creative Commons Attribution 4.0.
Recommendation of courses for learning AI and ML, making the process easier.
A curated GitHub list called Awesome AI Agents 2026 that organizes 340+ AI agent tools and frameworks into 20+ categories to help developers navigate the rapidly evolving agent ecosystem.
Share a curated AI evaluation (evals) resource library, including high-quality blogs, podcasts, papers, and projects, compiled by Xiangyi Li.
Alisa Liu is joining OpenAI and has publicly shared her interview preparation notes and study resources for free.
A curated list of 14 best YouTube channels for learning AI in 2026, covering fundamentals, deep learning, research, and practical applications.
Introduces the Awesome LLM Interpretability resource collection, which gathers various interpretability tools, papers, and community resources to help understand the internal workings of large language models.
A curated list of prompt engineering resources including papers, tools, courses, and communities for working with large language models, maintained by PromptSlab.
A curated list of X/Twitter accounts that explain AI concepts and teach how to build tools, agents, and frameworks, covering retrieval, testing, fine-tuning, and more.
A tweet promoting a collection of system design videos that make learning easier.
A practitioner expresses frustration with the fast-paced hype in agentic AI and seeks advice on how to keep up without burnout, asking for reliable resources and mental models.
A tweet thread lists 10 must-check GitHub repositories for AI engineers, covering hands-on AI engineering, LLMs, AI agents, ML deployment, and more.
A curated list of Twitter accounts to follow for tips and updates on AI coding tools like Claude Code, Cursor, Codex, GitHub Copilot, and open-source tools.
Recommends five high-value subreddits on Reddit covering AI, entrepreneurship, e-commerce, marketing, and productivity as a treasure trove of information.
AI Spark has fully open-sourced its knowledge base, containing 247 articles across six major modules (from beginner's guide to industry insights), continuously updated, suitable for AI learners.
A list of 10 recommended books for becoming a 10x AI engineer, covering LLMs, machine learning, deep learning, and data-intensive systems.
A curated reading list of foundational and modern resources for understanding agentic architecture, blending classic distributed systems concepts with current AI agent patterns.