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AGENTIC AI — MODULE 2: Reflection Design Pattern — EPISODE 11: Chart Generation Workflow

What happens when an AI agent's first attempt isn't good enough? Instead of just accepting a messy chart or buggy code, you can build a workflow that allows the agent to reflect on its own work and improve it.

In this video, Andrew Ng provides a hands-on demonstration of the Reflection design pattern. Watch as an agent is tasked with visualizing coffee sales data. You'll see how it first generates a confusing stacked bar chart, then uses a multimodal LLM to critique the visual output and rewrite the code, resulting in a much clearer and more effective visualization.

CHAPTERS:
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00:00 - Introduction to the Chart Generation Workflow
00:15 - The Task: Visualizing Coffee Sales Data
00:34 - Chart Generation Agentic Workflow
00:49 - Step 1: Writing the First Draft of Python Code
00:55 - Step 2: Executing the Code & Analyzing the Flawed Output
01:12 - Step 3: Reflection with External Feedback (Critiquing the Image)
01:44 - The Improved V2 Code and Final Chart
02:05 - Using Different LLMs for Generation vs. Reflection
02:50 - Key Takeaway: The Power of External Feedback

RESOURCES & LINKS:
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