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What are Agentic Workflows ?

📹 VIDEO TITLE 📹 What are Agentic Workflows ? ✍️VIDEO DESCRIPTION ✍️ In this video, we’ll explore Andrew Ng’s groundbreaking Agentic Workflow patterns, which provide large language models (LLMs) with the ability to operate more like autonomous agents. Instead of generating static responses, these workflows empower LLMs to execute tasks in ways that mirror human problem-solving. We'll break down the four core patterns—Reflection, Tool Use, Planning, and Multi-Agent Collaboration—and explain how each one enhances LLM performance by introducing iterative, self-corrective, and goal-driven behaviors. This approach goes beyond traditional AI outputs, enabling more refined, complex, and adaptive responses across a range of tasks. One of the key insights Andrew Ng brings to agentic workflows is how they mimic human strategies for tackling complicated, multi-step tasks. For example, just as humans use reflection to assess and improve their work, LLMs using the Reflection pattern can review their outputs, identify weaknesses, and refine results over multiple iterations. With Tool Use, LLMs access external resources or specialized tools, much like how people rely on calculators, search engines, or databases to make more informed decisions. This ability to interact with external sources allows AI agents to expand beyond static responses and adapt to real-time needs. Finally, we’ll discuss how the Planning and Multi-Agent Collaboration patterns bring an element of strategic organization and teamwork to AI, helping LLMs tackle complex goals by breaking them down into manageable steps or collaborating with other agents. This workflow is akin to how teams of people divide tasks, leverage different expertise, and provide feedback to improve results. Join us for an insightful overview of these transformative patterns and learn how agentic workflows are pushing the boundaries of what LLMs can achieve. 🧑‍💻BLOG POSTS URL 🧑‍💻 Part 1 - https://www.deeplearning.ai/the-batch... Part 2: Refection https://www.deeplearning.ai/the-batch... Part 3: Tool Use - https://www.deeplearning.ai/the-batch... Part 4: Planning - https://www.deeplearning.ai/the-batch... Part 5: Multi-Agent - https://www.deeplearning.ai/the-batch... 🧑‍💻GITHUB URL 🧑‍💻 No code samples for this video 📽OTHER NEW MACHINA VIDEOS REFERENCED IN THIS VIDEO 📽 What are Agentic Workflows? -    • What are Agentic Workflows ?   Why is AI going Nuclear? -    • Why is AI going Nuclear?   What is Synthetic Data? -    • What is Synthetic Data?   What is NLP? -    • What is NLP ?   What is Open Router? -    • What is Open Router ?   What is Sentiment Analysis? -    • What is Sentiment Analysis ?   What is Mojo ? -    • What is Mojo ?   SDK(s) in Pinecone Vector DB -    • SDK(s) in Pinecone Vector DB   Pinecone Vector DB POD(s) vs Serverless -    • Pinecone Vector Database PODS vs Serverless   Meta Data Filters in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   Namespaces in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   Fetches & Queries in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   Upserts & Deletes in Pinecone Vector DB -    • Meta Data Filters in Pinecone Vector Database   What is a Pineconde Index -    • What is a Pinecone Index ?   What is the Pinecone Vector DB -    • What is a Pinecone Index ?   What is LLM LangGraph ? -    • What is LLM LangGraph?   AWS Lambda + Anthropic Claude -    • AWS Lambda + Anthropic Claude   What is Llama Index ? -    • What is LLM Llama Index ?   LangChain HelloWorld with Open GPT 3.5 -    • LangChain HelloWorld with Open GPT 3.5   Forget about LLMs What About SLMs -    • Forget about LLMs What About SLMs ?   What are LLM Presence and Frequency Penalties? -    • What are LLM Presence and Frequency Penalt...   What are LLM Hallucinations ? -    • What are LLM Hallucinations ?   Can LLMs Reason over Large Inputs ? -    • Can LLMs Effectively Reason over Large Inp...   What is the LLM’s Context Window? -    • What is the LLM's Context Window ?   What is LLM Chain of Thought Prompting? -    • What is LLM Chain of Thought Prompting?   Algorithms for Search Similarity -    • Algorithms for Search Similarity   How LLMs use Vector Databases -    • How LLMs use Vector Databases   What are LLM Embeddings ? -    • What are LLM Embeddings ?   How LLM’s are Driven by Vectors -    • How LLM’s are Driven by Vectors   What is 0, 1, and Few Shot LLM Prompting ? -    • What is 0, 1, and Few Shot LLM Prompting ?   What are the LLM’s Top-P and TopK ? -    • What are the LLM’s Top-P + Top-K ?   What is the LLM’s Temperature ? -    • What is the LLM’s Temperature ?   What is LLM Prompt Engineering ? -    • What is LLM Prompt Engineering ?   What is LLM Tokenization? -    • What is LLM Tokenization ?   What is the LangChain Framework? -    • What is the LangChain Framework?   CoPilots vs AI Agents -    • AI CoPilots versus AI Agents   What is an AI PC ? -    • What is an AI PC ?   What are AI HyperScalers? -    • What are AI HyperScalers?   🔠KEYWORDS 🔠 #LargeLanguageModel #LLM #AIWorkflows #AgenticWorkflows #LLMDrivenSystems