All-in-One AI Agents Cheat Sheet ! AI Agents are the future of automation - capable of planning, reasoning, taking actions, and even working with other agents to complete complex tasks. Here’s a quick breakdown of everything you need to know to get started: 1. Core Capabilities AI Agents can plan, make decisions, use tools via APIs, remember context, and reflect on past actions - all with minimal human input. 2. Types of AI Agents From role-based agents (like researcher or coder) to multi-agent systems, there’s a structure for every use case. 3. Popular Design Patterns ReAct, AutoGPT, CAMEL, Toolformer, Reflexion - these patterns help agents reason, collaborate, and adapt effectively. 4. Foundational Concepts to Learn Understand prompts, task decomposition, CoT reasoning, feedback loops, and agent loops to build powerful agent workflows. 5. Top Tools & Frameworks Platforms like LangChain, AutoGen, CrewAI, LangGraph, and AgentOps power everything from multi-agent systems to workflow orchestration. 6. Memory & Knowledge Management From Redis and PostgreSQL for state storage to FAISS and Chroma for vector search - memory is what makes agents intelligent. 7. Real-World Use Cases Think customer service bots, content summarizers, developer copilots, and autonomous research agents - these use cases are already live. 8. Best Practices to Follow Start small, add memory modules gradually, keep your tool stack light, and always test + iterate to improve performance. 📌 Save this post as your go-to cheat sheet if you’re building or learning AI Agents in 2025 ! Follow Vaibhav Aggarwal For More Such Information ! | 31 comments on LinkedIn