8 Powerful Tricks to Master Claude Code and Supercharge Your AI Coding Workflow

Claude Code is widely regarded as one of the most powerful AI coding tools available today. However, many users aren’t leveraging its full potential. In this blog post, we’ll dive into eight essential tricks that can transform how you use Claude Code, enabling you to build software faster, with better quality, and fewer errors. These insights are drawn from the creator of an AI app generating $300,000 a year, so you know they’re battle-tested.

Introduction

If you’re new to Claude Code, it’s worth downloading and trying it out alongside this guide. Claude Code excels at helping developers write code through AI-assisted prompts, but to truly harness its power, you need to use it strategically. Let’s explore the eight tricks that will make you a Claude Code expert.

Trick 1: Use a Custom claude.md Rules File to Guide AI Behavior

One game-changing tip is creating a claude.md file in your project root. This file contains rules that Claude Code reads with every prompt. The creator recommends a set of seven specific rules that make Claude break down every coding task into tiny, manageable subtasks.

Why this matters:
- Breaking tasks down step-by-step reduces bugs.
- Claude creates a folder documenting all tasks, allowing you to review its thought process.
- With this approach, the user hasn't experienced a single bug in months.

Action:
Pause and download the recommended rules from the video description and add them to your own claude.md file immediately.

Trick 2: Master Plan Mode for Flawless Execution

Plan Mode is Claude Code’s secret weapon for ensuring you get exactly what you want.

How to use Plan Mode:
- Press Shift + Tab twice to enter Plan Mode.
- Describe in detail the feature or code you want.
- Claude will generate a detailed plan instead of jumping straight to coding.

Key tips:
- Overuse Plan Mode — use it for every micro-step to avoid errors.
- Use the Opus model for planning (/mod opus) and Sonnet for executing the plan (/mod sonnet).
- This approach improves planning quality and reduces costs (important if you’re on a limited subscription).

Trick 3: Use GitHub as Your Checkpoint System

Unlike some AI coding tools, Claude Code doesn’t have built-in checkpoints to rewind your code. The workaround is to commit your code to GitHub frequently—ideally after every successful coding step.

Benefits:
- Easily revert to previous commits if Claude makes a mistake.
- Maintains a reliable history of your project’s evolution.

Action:
Start integrating GitHub into your workflow now. If you’re unsure how, Claude Code can generate the necessary commands and help you set it up.

Trick 4: Incorporate Images to Inspire UI and Fix Bugs

Claude Code can process images, which is a powerful feature often overlooked.

Use cases for images:
- Inspiration: Screenshot UI elements from apps you like (e.g., to-do list designs) and paste them into Claude Code. Then prompt Claude to build similar UI components.
- Bug Fixing: Screenshot errors or UI glitches and provide them to Claude with instructions to fix or improve.

Tip for Mac users: Use Command + Shift + 4 to take selective screenshots to drag into Claude Code.

Trick 5: Use /clear to Reset Context and Save Money

Overloading Claude Code with hours of context increases hallucinations (errors) and wastes tokens, which can be costly.

When to use /clear:
- After Claude completes a sizable task or set of subtasks.
- Frequently, to keep context fresh and relevant.

Benefits:
- Reduces hallucinations and mistakes.
- Saves you money by lowering token usage.

Trick 6: Run Security Checks on Every Feature

Security is often overlooked but critical, especially if you're releasing apps publicly.

How to ensure secure code:
- After every feature is built, run a security check prompt asking Claude to verify best practices.
- Ensure no sensitive data (API keys, passwords) is exposed on the front end.
- Check for vulnerabilities that attackers could exploit.

Reminder: Many novice developers face hacking issues due to insecure code. Make security checks a mandatory step in your workflow.

Trick 7: Learn from Claude by Asking It to Explain Code

Even if you’re new to coding, understanding what Claude builds is essential.

How to do this:
After security checks, prompt Claude to explain the code in detail as if teaching a new engineer.

Why it helps:
- Improves your understanding of your app’s data flow and functionality.
- Enables you to write better prompts, leading to better code from Claude.
- Accelerates your learning curve dramatically.

Trick 8: Use Claude Code’s Downtime for Idea Generation Instead of Doomscrolling

Claude Code can take time—sometimes 15-30 minutes—to complete tasks. The natural temptation is to waste this waiting time on distractions like social media.

Better approach:
- Use a dedicated chat with Claude for brainstorming, reflecting on business ideas, or planning next steps while the AI works.
- This technique boosts productivity and mental well-being.

Result:
The creator’s productivity reportedly increased by 4000% after adopting this habit, and they generated dozens of new app ideas.

Conclusion

By incorporating these eight tricks into your Claude Code workflow, you’ll build apps faster, write cleaner and more secure code, and maintain better mental focus. Don’t forget to grab the prompts and rules mentioned above—they’re key to unlocking Claude Code’s full potential.

Which of these tips resonated most with you? Let us know in the comments! And if you want more AI coding insights, subscribe and turn on notifications for future videos.

Harness the power of Claude Code like a pro and elevate your AI-assisted development today!

📚 Video Chapters (9 chapters):

• Intro - 00:00
• Competition begins - 01:36
• The prompt - 02:47
• V1 - 05:38
• V2 - 07:04
• V3 - 09:59
• V4 - 12:10
• Final Version - 17:40
• Scoring - 19:55

📹 Video Information:

Title: Gemini CLI vs Claude Code: Which is the Best AI Coding Tool Ever?
Channel: Alex Finn
Duration: 23:52
Views: 22,736

Overview

This video presents a detailed, head-to-head comparison of two AI coding tools: Google's Gemini CLI and Anthropic's Claude Code. The creator builds an identical, complex stock tracking app with each tool, evaluating them across multiple criteria—speed, accuracy, "taste" (design/UX), and ease of use—while guiding viewers through each version's development. Each chapter builds on the previous, progressively revealing the strengths and weaknesses of both tools, ultimately providing viewers with actionable recommendations based on the real-world performance and user experience of each AI assistant.

Chapter-by-Chapter Deep Dive

Intro (00:00)

Core Concepts & Main Points:
- Introduction of Gemini CLI as Google's direct competitor to Claude Code.
- The main purpose: Determine which AI coding tool is superior by building the same app side-by-side with each.
- Notable difference: Gemini CLI offers the first 1,000 requests per day for free; Claude Code can cost up to $200/month for serious use.

Key Insights:
- Cost is a significant differentiator, but performance and user experience will be the true deciding factors.

Actionable Advice:
- Viewers are encouraged to follow along and build their own app as the video progresses.

Connection to Overall Theme:
- Sets the stage for a practical, feature-focused competition between two leading AI coding tools.

Competition begins (01:36)

Core Concepts & Main Points:
- The competition structure: Each AI runs in its own instance of the Cursor IDE, building the same stock tracking app.
- The apps will be evaluated on speed, accuracy, taste, and ease of use.
- Installation steps are briefly mentioned, with commands available in the video description.

Key Insights:
- The challenge is intentionally complex, moving beyond basic app examples to truly test the AIs.

Actionable Advice:
- Viewers can set up both tools using the provided commands to build alongside the creator.

Connection to Overall Theme:
- Establishes fairness and rigor in the head-to-head comparison, making findings relevant for serious developers.

The prompt (02:47)

Core Concepts & Main Points:
- The prompt, generated by Claude, specifies a stock tracking app with a chart, AI company summary, sentiment analysis, and a watch list.
- Both AIs receive the exact same prompt to ensure comparability.

Key Insights:
- Prompt quality is vital: a detailed, well-thought-out prompt leads to better, more autonomous AI performance.
- Initial behaviors: Claude Code builds a step-by-step to-do list; Gemini CLI provides an up-front plan and uses Next.js, which is more modern than Claude’s HTML/CSS approach.

Actionable Advice:
- Use detailed prompts for better AI output and reduced need for oversight.
- Consider the underlying technologies (e.g., Next.js vs. simple HTML) when building apps for future extensibility.

Connection to Overall Theme:
- Emphasizes the importance of prompt engineering and initial app scaffolding in AI-powered development.

V1 (05:38)

Core Concepts & Main Points:
- First working versions (V1) from both AIs are evaluated.
- Claude Code’s V1 is clean but uses mock data; Gemini CLI’s V1 uses real data for stock prices.

Key Insights:
- Gemini's speed and real-data integration are impressive, but its UI is less polished.
- Claude Code excels in user experience and design ("taste"), but lags on real data integration.

Actionable Advice:
- Check if your AI-generated app is using real or mock data before moving ahead.
- Prioritize both functionality and design for a usable product.

Connection to Overall Theme:
- Begins to highlight the trade-offs between immediate functionality and refined user experience.

V2 (07:04)

Core Concepts & Main Points:
- Both AIs advance: Gemini sticks closely to the prompt, while Claude Code autonomously adds extra features.
- Claude maintains and updates a to-do list; Gemini does not.
- Prompt quality is again emphasized.

Key Insights:
- Claude is creative and proactive but can go "off script."
- Gemini is more literal and focused.
- A superior initial prompt saves time and reduces errors.

Actionable Advice:
- Let your LLM generate the initial prompt for your project.
- Use to-do lists or stepwise approaches for better project management with AI tools.
- Approve steps rather than micromanaging, provided your prompt is strong.

Connection to Overall Theme:
- Contrasts the personalities and approaches of the two AI tools, reinforcing the importance of prompt engineering and project management style.

V3 (09:59)

Core Concepts & Main Points:
- Both apps expand features: Claude Code adds an alert button and company news, but with mock data; Gemini refines charts and watch lists.
- Gemini is more accurate in basic functionality but lacks detailed sentiment explanations.

Key Insights:
- Claude Code tends to add features not requested, which can be a double-edged sword.
- Gemini’s output is more utilitarian—plain but functional.

Actionable Advice:
- If you want creative enhancements, Claude might be better; for strict adherence, Gemini is preferable.
- Test for requested features and clarity (e.g., explanations for sentiment analysis).

Connection to Overall Theme:
- Further explores the balance between creativity and strictness in AI outputs.

V4 (12:10)

Core Concepts & Main Points:
- Claude Code catches up on functionality and continues to add creative, unprompted features.
- Gemini runs into its first error; Claude Code remains error-free.

Key Insights:
- Reliability is a key differentiator: Claude Code is stable; Gemini can be fragile.
- Debugging workflow: Copy errors directly from the console and feed them back to the AI for troubleshooting.

Actionable Advice:
- When encountering errors, use a simple feedback loop: paste the error into the AI and ask for a fix.
- Value stable, "ironed out" tools for production work.

Connection to Overall Theme:
- Demonstrates the practical realities of AI coding: error handling and the importance of stability for developer productivity.

Final Version (17:40)

Core Concepts & Main Points:
- Final feature check: Claude Code’s app has technical indicators, news feed, and a polished UI/UX.
- Gemini CLI is stuck in an error loop and becomes unusable.

Key Insights:
- Claude Code’s app is visually appealing, intuitive, and "human-centric."
- Gemini CLI, despite initial speed and intelligence, ultimately falters due to bugs and lack of polish.

Actionable Advice:
- For a production-ready, user-friendly app, prioritize tools that consistently deliver polished, stable results.
- Be ready to input API keys or make minor tweaks for advanced features.

Connection to Overall Theme:
- The journey highlights the difference between building something that “works” and building something users want to use.

Scoring (19:55)

Core Concepts & Main Points:
- Final ratings by category: speed, accuracy, taste, ease of use.
- Claude Code: 7 (speed), 9 (accuracy), 10 (taste), 7 (ease) = 33/40
- Gemini CLI: 8 (speed), 6 (accuracy), 5 (taste), 8 (ease) = 27/40

Key Insights:
- Claude Code is superior in accuracy and taste (usability/design).
- Gemini CLI is faster and a bit easier at first, but error-prone and less appealing.

Actionable Advice:
- If budget is tight, use Gemini CLI to build and launch your first app for free, then upgrade to Claude Code if/when possible.
- Monetize early efforts and reinvest in better tools.

Connection to Overall Theme:
- The competition underscores the value of both tools, but positions Claude Code as the best all-around choice, especially for those who prioritize quality and reliability.

Cross-Chapter Synthesis

Recurring Themes & Building Concepts

• Prompt Engineering: From “The prompt” (02:47) through “V2” (07:04), the importance of crafting a detailed, thoughtful prompt is repeatedly emphasized. Good prompts enable both AIs to work more autonomously and efficiently.
• Trade-offs: Early chapters (“V1” and “V2”) reveal Claude's superior taste/design but slower speed and reliance on mock data, while Gemini excels in initial speed and real data integration but lacks polish. These trade-offs are explored and iterated upon in subsequent versions.
• Reliability vs. Creativity: Claude Code is shown to be more creative, adding features beyond the prompt (sometimes useful, sometimes superfluous), and extremely reliable (rarely producing errors). Gemini is literal, focused, and fast, but less reliable as complexity increases.
• Debugging & Error Handling: Starting in “V4” (12:10), Gemini’s errors illustrate the importance of robust error handling and the value of stable tools. The recommended debugging approach is to iteratively paste errors back into the AI for fixes.

Progressive Learning Journey

• The video begins by introducing the contenders and establishing a fair, rigorous test environment.
• Each chapter adds complexity to the app, exposing deeper strengths and weaknesses of the AI tools.
• Viewers learn not only which tool is better but also how to prompt, manage, and debug AI-powered coding workflows.
• The final scoring and recommendations synthesize these lessons, giving practical guidance for both beginners and experienced AI developers.

Most Important Points by Chapter

• Intro: Cost and new competition in the AI coding space.
• The prompt: Detailed prompts fuel better AI coding outcomes.
• V1/V2: Early strengths: Gemini for speed and data, Claude for UX and to-do management.
• V3/V4: Reliability and error management become crucial as complexity grows.
• Final Version/Scoring: Claude Code is the overall winner for polished, stable, user-friendly apps, with actionable next steps for budget-conscious users.

Actionable Strategies by Chapter

Warnings/Pitfalls:
- Claude Code: Expensive for high usage ($200/month for serious use).
- Gemini CLI: Prone to errors and can become unusable in more complex apps; debugging can become a "rabbit hole," especially for beginners.
- Prompting: Sloppy or overly vague prompts lead to more manual correction and oversight.

Resources/Next Steps:
- Install commands for both tools are in the video description.
- Link to a video on app monetization for those using Gemini CLI and wanting to upgrade.
- Weekly live streams where the creator builds apps live for additional learning.

This chapter-structured summary provides a clear roadmap for understanding the strengths, weaknesses, and practical realities of Gemini CLI and Claude Code in AI-driven app development, with actionable insights at each step.