Google Gemini is surprisingly good at coding. It can generate functions, debug errors, explain complex code, write tests, and even architect entire systems. But like any AI tool, you need to know how to use it effectively.
After using Gemini for coding daily for the past year, I've developed a set of techniques that consistently produce better results. Here's everything I've learned.
What Gemini is Good At (and Not Good At)
Let's set realistic expectations:
Gemini Excels At:
- Boilerplate code: CRUD operations, API endpoints, common patterns
- Explaining code: Understanding what unfamiliar code does
- Debugging: Finding obvious bugs and suggesting fixes
- Converting formats: JSON to TypeScript types, SQL to ORM, etc.
- Writing tests: Unit tests, edge cases, test data
- Documentation: Comments, README files, API docs
- Learning: Explaining concepts, comparing approaches
Gemini Struggles With:
- Large codebases: Limited context window means it can't see your whole project
- Cutting-edge libraries: May not know the latest API changes
- Business logic: Can't understand your specific requirements without explanation
- Complex architecture: May suggest patterns that don't fit your system
Best Prompts for Coding
The quality of Gemini's code depends heavily on how you ask. Here are battle-tested prompts for common tasks:
1. Code Generation
Be specific about language, framework, and requirements:
Write a [language] function that [specific task]. Requirements: - [requirement 1] - [requirement 2] - [error handling needs] Use [specific library/framework] and follow [coding style].
Write a TypeScript function that fetches user data from an API and caches it. Requirements: - Use fetch API - Cache results for 5 minutes - Handle network errors gracefully - Return null if user not found Use async/await and add JSDoc comments.
2. Debugging
Provide the error message and relevant code:
I'm getting this error: ``` [paste error message] ``` Here's my code: ```[language] [paste relevant code] ``` What's causing this and how do I fix it?
3. Code Review
Ask for specific feedback:
Review this code for: 1. Bugs or edge cases I might have missed 2. Performance issues 3. Security vulnerabilities 4. Code style improvements ```python [paste your code] ```
4. Code Explanation
Great for understanding unfamiliar code:
Explain this code step by step. What does it do, and why is it written this way? ```javascript [paste confusing code] ```
5. Writing Tests
Write unit tests for this function using [Jest/pytest/etc]. Include tests for: - Happy path - Edge cases - Error handling - Boundary conditions ```[language] [paste function to test] ```
Prompting Do's and Don'ts
✅ Do
- Specify the language and version
- Include relevant context
- Ask for explanations
- Request error handling
- Iterate and refine
❌ Don't
- Be vague ("write me a function")
- Paste huge files without context
- Trust code without testing
- Ignore version differences
- Copy-paste without understanding
Workflow Tips for Developers
1. Keep Project-Specific Chats
Create a separate Gemini conversation for each project or feature. This builds context over time - Gemini remembers your codebase structure, patterns, and decisions from earlier in the chat.
2. Start with Architecture
Before asking Gemini to write code, discuss the approach first:
I need to build [feature]. Before writing code, what's the best approach? Consider: - My stack: [React/Node/etc] - Scale: [small/medium/large] - Existing patterns: [describe your codebase style] Give me 2-3 options with tradeoffs.
3. Iterate, Don't Regenerate
If the code isn't quite right, don't start over. Tell Gemini what to change:
"That's close, but can you add error handling for network failures?" "Good, but use async/await instead of .then()" "Can you make this more concise? The current version is too verbose."
4. Save Good Conversations
When Gemini produces great code or explanations, save them. You'll want to reference them later.
Use SaveChat for Gemini to export coding conversations to PDF. Build a personal library of solved problems.
5. Always Test the Output
Gemini writes plausible-looking code that might have subtle bugs. Always:
- Run the code before using it
- Check edge cases manually
- Verify with real data
- Read and understand what it wrote
Example: Building a Feature with Gemini
Here's a real workflow example:
Task: Build a rate limiter for an Express API
Step 1: Ask for architecture options
I need to add rate limiting to my Express.js API. What are my options? Consider: - Running on multiple servers (need distributed solution) - Different limits for different endpoints - Should work with Redis
Step 2: Choose approach and get implementation
Let's go with option 2 (sliding window with Redis). Write the middleware. Requirements: - TypeScript - Configurable per-route limits - Return proper 429 responses with retry-after header - Include tests
Step 3: Iterate on details
Good, but add: 1. IP-based limiting for unauthenticated requests 2. User-ID-based limiting for authenticated requests 3. Logging when limits are hit
Step 4: Ask for edge cases
What edge cases should I test for? Are there any security issues with this implementation?
This iterative approach produces much better results than asking for everything at once.
Organize Your Coding Chats
Keep coding conversations organized by project with Toolbox for Gemini. Export solutions to PDF for your personal reference library.
Install Toolbox for Gemini - Free4.7★ rating • 5,000+ users
Common Mistakes to Avoid
- Not providing context: Gemini doesn't know your project. Explain your stack, patterns, and constraints.
- Trusting blindly: Always read and understand the code before using it.
- Giving up too early: If the first response isn't right, iterate. The second or third attempt is often much better.
- Ignoring the explanation: Gemini often explains why it made certain choices. Read those explanations - they help you learn.
- Using outdated prompts: Gemini improves constantly. Techniques from 6 months ago might not be optimal anymore.
Summary
Gemini is a powerful coding assistant when used correctly. The key principles:
- Be specific in your prompts
- Provide context about your project
- Iterate rather than regenerate
- Always test the output
- Stay organized with project-specific chats
Start with the prompt templates in this guide, adapt them to your needs, and build your own library of effective prompts over time.
Not affiliated with or endorsed by Google LLC. This guide is based on personal experience with Gemini for coding tasks. Updated January 2026.