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    Who should I follow to learn about AI agents?

    Updated October 21, 2026

    Key takeaway

    Andrew Ng and Harrison Chase are the people ChatGPT, Gemini and Google AI Mode recommend most for learning AI agents, and Andrew Ng is named in every answer set. Copilot recommends a different group led by Ilya Sutskever and Demis Hassabis. ChatGPT, Gemini and Google AI Mode credit Andrew Ng for agentic workflow patterns such as reflection, tool use, planning and multi agent collaboration, and Harrison Chase for LangChain and LangGraph agent architecture.

    Mostly agree

    Andrew Ng is the best person to follow for agentic workflows

    Harrison Chase is a key voice for building agents

    Where they differ

    Builders or big names

      Verdict

      Four engines, ChatGPT, Gemini, Google AI Mode and Copilot, name Harrison Chase and Andrew Ng among the people to follow, with Gemini and Google AI Mode putting Andrew Ng first. Copilot alone opens with Ilya Sutskever and Demis Hassabis.

      What engines actually searched

      The sub-queries each engine actually searched before answering.

      Cited, but not mentioned

      7 sites cite this answer without naming anyone

      Full responses

      5 of 5 engines that answered. Full stored text as captured, with dashes shown as hyphens. Nothing is summarised.

      ChatGPT5,029 characters · October 12, 2026

      If you want to learn AI agents, I’d follow a mix of people who build agents, researchers who explain how they work, and practitioners who share real-world lessons - not just people posting AI news.

      My recommendation is to start with a small list of 6–8 high-signal accounts, then learn by building alongside them.

      1. The best people to follow

      1. Andrej Karpathy

      Best for foundations

      X: @karpathy · YouTube

      Excellent for understanding LLMs, how they reason, and how to think about building AI systems. Start here if you want to understand what happens under the hood.

      1. Harrison Chase

      X: @hwchase17 · LangChain

      One of the people to watch for agent architectures, tool use, orchestration, and production workflows. Particularly useful if you want to build agents in Python.

      1. Andrew Ng

      X: @AndrewYNg · DeepLearning.AI

      Great for practical AI engineering, agentic workflows, and understanding where agents are useful in business. A good choice for beginners and non-researchers.

      1. Simon Willison

      Blog: simonwillison.net · X

      Follow him for hands-on experiments, practical code, tool calling, and security issues such as prompt injection. Particularly good at separating useful techniques from hype.

      1. Anthropic

      X: @AnthropicAI · Engineering blog

      A strong source for agent design patterns, tool use, context engineering, and lessons from building agents that work reliably. Read its engineering articles, not just product announcements.

      1. OpenAI

      X: @OpenAI · Agents developer guide

      Follow for agent SDKs, tool integration, multi-agent orchestration, tracing, evaluations, and safety guardrails. Its official documentation is especially useful when you want to implement something.

      1. Jim Fan

      X: @DrJimFan

      Worth following for research and experiments involving autonomous agents, tool use, robotics, and agents that interact with digital or physical environments.

      1. Hugging Face

      X: @huggingface · Agents tutorials

      Follow for open-source agent frameworks, model experimentation, and tutorials that help you understand how agents are implemented beyond proprietary platforms.

      2. The best resources to learn from them

      Following people is useful, but these resources will help you turn what you learn into skills.

      Start here: Building Effective Agents

      Beginner to intermediate · Free

      Read Anthropic’s guide to learn the difference between workflows and autonomous agents, and when each approach makes sense. Building Effective AI Agents \ Anthropic

      Build your first agent

      Hands-on coding

      Follow the OpenAI Agents SDK tutorials to learn tool calling, agent handoffs, tracing, and guardrails. Agents

      Learn agent orchestration

      Intermediate · Python

      Explore the LangChain and LangGraph learning guides for memory, multi-agent workflows, and agents that use external tools. Learn

      3. Who should you follow based on your goal?

      If you want to…Prioritize
      Understand AI from the ground upAndrej Karpathy, Andrew Ng
      Build AI agents with codeHarrison Chase, OpenAI
      Build reliable production agentsAnthropic, Harrison Chase
      Explore open-source agentsHugging Face
      Keep up with research and emerging capabilitiesJim Fan, Andrej Karpathy
      Automate business tasks and workflowsAndrew Ng, Anthropic

      4. My suggested learning routine

      Spend 30 minutes a day:

      • 10 minutes: Read posts from two or three people on your list.
      • 10 minutes: Study one technical concept, such as tool calling, memory, retrieval, or multi-agent orchestration.
      • 10 minutes: Build or improve a small agent.

      Start with a simple research agent that searches for information, summarizes its findings, and provides source links. Then add memory, evaluation, and human approval before allowing it to take actions.

      The most important principle: learn the fundamentals before chasing every new agent framework. Anthropic’s engineering guidance specifically recommends starting with the simplest design that works and adding complexity only when it provides a real benefit. Building Effective AI Agents \ Anthropic

      Let me tailor the list to you

      Gemini logo Gemini3,318 characters · October 12, 2026

      To learn about AI Agents - ranging from underlying architectures to practical implementation - following the right researchers, engineers, and educators on platforms like X (Twitter), LinkedIn, Substack, and YouTube can accelerate your learning curve significantly.

      Here are the top people and organizations to follow, broken down by focus area:

      1. Research & Foundational Thought Leaders

      • Andrew Ng (DeepLearning.AI): One of the best educators in AI. He frequently shares insights, short courses (such as agentic workflows and multi-agent systems with CrewAI), and breakdowns on why agents are the next frontier.

      • Harrison Chase (LangChain): As the creator of LangChain and LangGraph, Harrison is deeply embedded in agent architectures, state management, and multi-agent workflows. His feed is a goldmine for practical agent engineering.

      • Yann LeCun & Andrej Karpathy: While Karpathy focuses broadly on AI and education (and has done great deep-dives into autonomous systems and LLMs), following leading research minds helps you understand the theoretical limits and capabilities of agentic behaviors.

      2. Framework Builders & Open-Source Experts

      • Joao Moura (CrewAI): Creator of CrewAI. His content focuses heavily on multi-agent collaboration, task delegation, and enterprise agent deployments. Mastering AI Agents: The 10 Best Free Courses, Tutorials ... - Medium

      • Jerry Liu (LlamaIndex): Great for insights into agentic RAG (Retrieval-Augmented Generation), data integration, and workflows that allow agents to interact reliably with private data stores.

      • The Hugging Face Team (e.g., Clément Delangue, Ɐlexandre Wild): Essential for keeping up with open-source models, tool-use agents, and their dedicated agent courses.

      3. Practical Builders & Creators

      • Rowan Cheung (The Rundown AI): Excellent for daily high-level news, trending agent tools, and practical use-cases sweeping the industry.

      • Dan Shipper & The Every Team: Great for practical, human-centric essays on using AI agents for real-world productivity and workflow automation.

      Alternative Free Resources to Supplement Your Learning

      If you want to move beyond social media feeds and dive into structured learning, consider these top-tier resources:

      • DeepLearning.AI Short Courses: Free, code-forward modules built specifically around agent design patterns and multi-agent frameworks.

      • Hugging Face Agents Course: A comprehensive community-driven curriculum covering code agents and transformers.

      • Microsoft's "AI Agents for Beginners": A fantastic 10-lesson video course taking you from concept to code. AI Agents for Beginners - Microsoft Learn

      Are you looking to learn about AI agents from a high-level strategic/business perspective, or do you want to dive straight into coding and building them yourself?

      Google AI Mode2,329 characters · October 12, 2026

      To dive deep into the world of AI Agents - ranging from multi-agent frameworks to enterprise automation - following the right builders, researchers, and educators will keep you on the cutting edge.

      Here are the top voices and where to find their insights:

      • ** Harrison Chase** : As the co-founder and CEO of LangChain, his work and public updates focus heavily on agent orchestration, tool use, memory management, and enterprise app architecture.

      • João Moura : The creator of CrewAI, he is a primary voice to follow for multi-agent systems, role-playing autonomous agents, and collaborative team-based AI setups.

      • ** Sam Witteveen** : A favorite among developers, his YouTube channel and social feeds provide hands-on, highly technical deep dives into agent frameworks, advanced reasoning loops, and coding implementations. Who to follow to stay most-informed re AI / the Singularity?

      • ** Lilian Weng** : A researcher at OpenAI whose technical blog posts (such as her foundational breakdown on autonomous agent architecture) remain standard reading for anyone trying to understand the core mechanics of LLM-powered agents.

      • ** Andrej Karpathy** : A prominent AI researcher whose commentary on foundational shifts, systems engineering, and modern agentic development ("vibe coding") offers a big-picture view of where autonomous systems are heading. Artem Rodichev's Post - LinkedIn

      If you want to narrow this down, let me know:

      • Are you looking for hands-on coding tutorials or high-level business/strategy insights?
      • What framework (if any) are you currently exploring (LangChain, CrewAI, AutoGen, etc.)?

      I can tailor these recommendations or point you toward specific starter projects.

      Perplexity455 characters · October 21, 2026

      Start with Andrew Ng for clear explanations of agent design patterns - planning, tool use, reflection, and multi-agent workflows. Follow Harrison Chase to learn how to build and orchestrate agents with LangChain and LangGraph, and Simon Willison for practical experiments and lessons from real-world use.(citegist.com)

      Copilot logo Copilot3,906 characters · October 12, 2026

      If you want to dive into AI agents , it’s best to follow a mix of researchers, open‑source builders, educators, and consultants who are actively shaping the field. Here are some of the most influential voices right now:

      🔬 Researchers & Lab Leaders

      📚 Educators & Accessible Voices

      ⚙️ Open‑Source Builders (Agent Frameworks)

      🧭 Consultants & Practitioners

      👉 If your main interest is hands‑on building of AI agents , I’d recommend following Harrison Chase (LangChain) and Jerry Liu (LlamaIndex). 👉 If you want big‑picture strategy and safety , keep up with Ilya Sutskever and Demis Hassabis. 👉 For accessible learning and practical adoption , Andrew Ng and Cassie Kozyrkov are excellent starting points.

      Would you like me to curate a list of their best platforms to follow (Twitter, LinkedIn, newsletters, podcasts), so you can plug directly into their updates?