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10 AI Coding Tips That Actually Work (And How to Keep It Simple)

Burke Holland shared 10 practical strategies for using AI coding tools effectively, emphasizing simplicity and safety. The tips include using Visual Studio Code, enabling YOLO mode for seamless execution, isolating agents via remote SSH, prototyping upfront, and leveraging multi-model reviews. The advice aims to help developers avoid overcomplication and improve production results.

read2 min views1 publishedJun 20, 2026

Feeling overwhelmed by the constant flood of new AI features, MCP servers, and agentic platforms? In a world full of tech noise, it's easy to get exhausted trying to keep up.

I just watched an incredible video by Burke Holland where he strips away the hype and shares 10 highly practical, concrete strategies to make AI coding tools actually work for your daily workflow. If you want to stop overcomplicating your setup and start getting better production results, here is the ultimate breakdown.

Huge shoutout and credit to Burke Holland for these insights:

1) Use Visual Studio Code to maximize your environment with powerful themes, extensions, and inline terminal chats.

2) Always turn on YOLO / "allow all" mode so your AI agent can execute commands seamlessly without breaking your flow with constant permission prompts.

3) Never run agents on your own machine, choosing instead to isolate them via remote SSH or dev containers so YOLO mode is completely safe.

4) Prototype and mock everything upfront to map out UI design languages and logic before implementing code.

5) Always plan and grill by leveraging interactive planning modes to answer critical edge-case questions before generating file.

6) Rubber duck your plans across different AI model families (like combining Claude and GPT) to cross-verify solutions and expose blind spots.

7) Utilize autopilot and sub-agents to delegate parallel tasks and route smaller, faster models where appropriate.

8) Use built-in browser tools to visually review live previews and directly prompt structural or stylistic adjustments.

9) Run iterative multi-model reviews on autopilot to catch hidden bugs and refine code quality until reaching a clear point of diminishing returns.

10) Learn from your session history using tools like Chronicle to analyze your prompting habits and continually optimize how you interact with the agent.

If you are looking to dive deeper into perfecting your workflow, mastering these concepts, and scaling your development habits, I highly recommend checking out this book:

👉 [Book Recommendation on AI & Developer Productivity](https://link.amazon/B07U1tdB3)
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