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AI coding assistants have come a long way, but they’re still not perfect. If you’ve tried them and felt disappointed, don’t worry—you’re not alone. In this video, I break down: 🚀 The key challenges AI faces in software development 💡 How to work around these limitations to maximize productivity 🛠️ My personal setup & best practices for using AI coding assistants effectively We’ll cover the latest advancements, from large language models (LLMs) to agentic coding tools like Amazon Q Developer and Cline with Claude 3.5 Sonnet v2. Learn how to structure your code, use coding assistants for unit testing, and apply prompt engineering techniques for better results. 🔗 Resources & Related Content: 📌 Adaptive Software Design Series → • Principles for Distributed Systems Design ... 📌 Follow me on LinkedIn → / derick-chen If you’re a serious builder, AI coding assistants can be a game-changer. Subscribe to @BuildWithDC for more insights on AI, software architecture, and development best practices! 👍 🔔 #AICoding #SoftwareDevelopment #AmazonQ #Claude35 #CodingAssistants #BuildWithDC More resources and guides available at https://www.BuildWithDC.co Systems Atlas (https://atlas.BuildWithDC.co) - a challenge based systems design knowledge map. AI Driven Designer (https://design.BuildWithDC.co) - AI led software architecture design tool. Chapters: 00:00 Intro – AI Coding Assistants Not Living Up to the Hype 00:43 Coding Assistant Updates Since 2023 01:14 Current Challenges with AI in Software Development 02:19 Sub-par Developer Experience with Coding Assistants 03:11 Understanding When AI Works Best 04:21 How to Structure Your Code for Better AI Help 06:08 Writing Better Prompts for Better Results 07:11 My Personal Coding Assistant Setup (Amazon Q + Cline) 07:45 Pros and Cons of Amazon Q Developer and Cline 09:05 Final Thoughts: How to Stay Ahead with AI Coding Tools