Welcome to the Agentic AI Learning Materials gist! This gist is dedicated to providing resources and learning materials on Agentic AI, Agentic systems, and workflows. Whether you're a beginner or an advanced learner, you'll find valuable content to enhance your understanding and skills in this exciting field.
- Introduction
- Learning Resources
- Agentic AI
- Agentic Systems and Workflows
- Useful Links
- LlamaIndex
- Google on Agents
- Microsoft
- Anthropic
- LangChain
- OpenAI
Agentic AI represents a significant advancement in artificial intelligence, enabling systems to not only analyze data but also take actions based on that data. This repository aims to provide a comprehensive collection of learning materials to help you understand and implement Agentic AI and its associated workflows.
- Agentic AI and AI Agents: A Primer for Leaders: A Coursera course that provides a foundational understanding of Agentic AI and AI agents1.
- Awesome AI Agents: A curated list of over 300 resources related to Agentic AI2.
- What Are Agentic Workflows? A Guide For Business Process Automation: An article explaining the key components, benefits, and examples of Agentic workflows3.
- Understanding AI Agents & Agentic Workflows: A detailed guide on AI agents and Agentic workflows, including their building blocks and use cases4.
- Agentic Document Workflows: LlamaIndex's Agentic Document Workflows (ADW) automate complex knowledge work by combining document processing, retrieval, and agentic orchestration. This system enhances productivity in tasks like contract review and invoice processing while maintaining human oversight.5.
- AgentWorkflow: LlamaIndex has introduced AgentWorkflow, a system that simplifies building and orchestrating AI agent systems by maintaining state and coordinating between agents.6.
- Agents - White Paper: Authors: Julia Wiesinger, Patrick Marlow and Vladimir Vuskovic explores how Generative AI models can use external tools to access real-time information and perform tasks autonomously, similar to human agents. It emphasizes the importance of combining reasoning, logic, and tool access to create AI agents capable of planning and executing tasks independently.7
- Google Agentspace: Google's platform for deploying AI agents that integrate with enterprise data and applications7
- Bringing AI Agents to Enterprises with Google Agentspace: A blog post detailing how Google Agentspace can enhance enterprise productivity8.
- Microsoft’s Agentic AI Frameworks: AutoGen and Semantic Kernel: Learn about Microsoft's frameworks for building and scaling AI applications with multiple agents4.
- AutoGen v0.4: Reimagining the Foundation of Agentic AI: An overview of the latest version of AutoGen, designed for robust and scalable agentic workflows9.
- Building Effective Agents: Practical advice and insights from Anthropic on building effective agentic systems8.
- Introducing Computer Use in Claude 3.5: Details on the new capabilities of Claude 3.5 for agentic coding and tool use10.
- LangChain Framework: A composable framework for building with LLMs, including orchestration for agentic workflows3.
- What’s Next for Agentic AI?: Insights from LangChain's founder on the future of agentic AI and ambient agents5.
- Introducing Operator: OpenAI's research preview of an agent that can perform tasks using its own browser11.
- OpenAI Platform: Explore resources, tutorials, and API docs for building with OpenAI's developer platform12.
I welcome contributions from the community! If you have any learning materials, articles, or resources related to Agentic AI and workflows, please feel free to comment below.