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#ia #Agentes #Prompt

Building AI Agents

📹 Videos

  1. LLM Introduction: https://www.youtube.com/watch?v=zjkBMFhNj_g
  2. LLMs from Scratch: https://www.youtube.com/watch?v=9vM4p9NN0Ts
  3. Agentic AI Overview (Stanford): https://www.youtube.com/watch?v=kJLiOGle3Lw
  4. Building and Evaluating Agents: https://www.youtube.com/watch?v=d5EltXhbcfA
  5. Building Effective Agents: https://www.youtube.com/watch?v=D7_ipDqhtwk
  6. Building Agents with MCP: https://www.youtube.com/watch?v=kQmXtrmQ5Zg
  7. Building an Agent from Scratch: https://www.youtube.com/watch?v=xzXdLRUyjUg
  8. Philo Agents: https://www.youtube.com/playlist?list=PLacQJwuclt_sV-tfZmpT1Ov6jldHl30NR

🗂️ Repos

  1. GenAI Agents: https://github.com/nirdiamant/GenAI_Agents
  2. Microsoft's AI Agents for Beginners: https://github.com/microsoft/ai-agents-for-beginners
  3. Prompt Engineering Guide: https://lnkd.in/gJjGbxQr
  4. Hands-On Large Language Models: https://lnkd.in/dxaVF86w
  5. AI Agents for Beginners: https://github.com/microsoft/ai-agents-for-beginners
  6. GenAI Agentshttps://lnkd.in/dEt72MEy
  7. Made with ML: https://lnkd.in/d2dMACMj
  8. Hands-On AI Engineering: https://github.com/Sumanth077/Hands-On-AI-Engineering
  9. Awesome Generative AI Guide: https://lnkd.in/dJ8gxp3a
  10. Designing Machine Learning Systems: https://lnkd.in/dEx8sQJK
  11. Machine Learning for Beginners from Microsoft: https://lnkd.in/dBj3BAEY
  12. LLM Course: https://github.com/mlabonne/llm-course

🗺️ Guides

  1. Google's Agent Whitepaper: https://lnkd.in/gFvCfbSN
  2. Google's Agent Companion: https://lnkd.in/gfmCrgAH
  3. Building Effective Agents by Anthropic: https://lnkd.in/gRWKANS4.
  4. Claude Code Best Agentic Coding practices: https://lnkd.in/gs99zyCf
  5. OpenAI's Practical Guide to Building Agents: https://lnkd.in/guRfXsFK

📚Books

  1. Understanding Deep Learning: https://udlbook.github.io/udlbook/
  2. Building an LLM from Scratch: https://lnkd.in/g2YGbnWS
  3. The LLM Engineering Handbook: https://lnkd.in/gWUT2EXe
  4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://lnkd.in/dJ9wFNMD
  5. Building Applications with AI Agents - Michael Albada: https://lnkd.in/dSs8srk5
  6. AI Agents with MCP - Kyle Stratis: https://lnkd.in/dR22bEiZ
  7. AI Engineering: https://www.oreilly.com/library/view/ai-engineering/9781098166298/

📜 Papers

  1. ReAct: https://lnkd.in/gRBH3ZRq
  2. Generative Agents: https://lnkd.in/gsDCUsWm.
  3. Toolformer: https://lnkd.in/gyzrege6
  4. Chain-of-Thought Prompting: https://lnkd.in/gaK5CXzD.
  5. Tree of Thoughts: https://lnkd.in/gRJdv_iU.
  6. Reflexion: https://lnkd.in/gGFMgjUj
  7. Retrieval-Augmented Generation Survey: https://lnkd.in/gGUqkkyR.

🧑‍🏫 Courses

  1. HuggingFace's Agent Course: https://lnkd.in/gmTftTXV
  2. MCP with Anthropic: https://lnkd.in/geffcwdq
  3. Building Vector Databases with Pinecone: https://lnkd.in/gCS4sd7Y
  4. Vector Databases from Embeddings to Apps: https://lnkd.in/gm9HR6_2
  5. Agent Memory: https://lnkd.in/gNFpC542
  6. Building and Evaluating RAG apps: https://lnkd.in/g2qC9-mh
  7. Building Browser Agents: https://lnkd.in/gsMmCifQ
  8. LLMOps: https://lnkd.in/g7bHU37w
  9. Evaluating AI Agents: https://lnkd.in/gHJtwF5s
  10. Computer Use with Anthropic: https://lnkd.in/gMUWg7Fa
  11. Multi-Agent Use: https://lnkd.in/gU9DY9kj
  12. Improving LLM Accuracy: https://lnkd.in/gsE-4FvY
  13. Agent Design Patterns: https://lnkd.in/gzKvx5A4
  14. Multi Agent Systems: https://lnkd.in/gUayts9s

📩 Newsletters

  1. Gradient Ascent: https://lnkd.in/gZbZAeQW
  2. DecodingML by Paul: https://lnkd.in/gpZPgk7J
  3. Deep (Learning) Focus by Cameron: https://lnkd.in/gTUNcUVE
  4. NeoSage by Shivani: https://blog.neosage.io/
  5. Jam with AI by Shirin and Shantanu: https://lnkd.in/gQXJzuV8
  6. Data Hustle by Sai: https://lnkd.in/gZpdTTYD

Referências