AI Prompts for Coding & Programming

Whether you're writing your first function or refactoring a legacy codebase, these prompts help you write cleaner code, squash bugs faster, and learn new languages without drowning in documentation. Tested across ChatGPT, Gemini, and Claude so you know which model codes best for each task.

Results last tested Feb 15, 2026 · Models: GPT-4o, Gemini 2.0, Claude 3.5 Sonnet, Grok 2
What you're trying to do Prompt הכי טוב ל
Understand unfamiliar code quickly Code Explainer Claude
Debug code with error analysis Bug Squasher ChatGPT
Improve code quality and structure Refactor Coach Claude
Solve algorithmic problems step by step Algorithm Solver Gemini
Integrate third-party APIs quickly API Integrator ChatGPT
Learn a new programming language fast Language Launcher Gemini

Code Explainer

Understand unfamiliar code quickly

Explain this code so I can understand and modify it.

[Paste the code block]

Language: [language if not obvious]
My skill level: [beginner / intermediate / advanced]
What I need to do with it: [modify, extend, debug, or just understand]

Provide:
1. A plain-English summary of what this code does (2-3 sentences)
2. A line-by-line or block-by-block walkthrough with annotations
3. Any design patterns or idioms being used (and why)
4. Potential bugs, edge cases, or gotchas in this code
5. How I would modify it to [describe intended change]
6. Three things I should understand about this code before touching it

הכי טוב ל: CLAUDE

Claude provides the clearest code explanations at any skill level. It adjusts its language complexity based on your stated experience and excels at identifying non-obvious patterns and potential pitfalls in the code.

Tested Feb 15, 2026

טיפים מקצועיים

Include surrounding context, not just the function you're confused about. Isolated code snippets lose meaning. Paste the imports and the calling code so AI understands the full picture.

Bug Squasher

Debug code with error analysis

Help me find and fix this bug.

Code:
[Paste the relevant code]

Error message: [paste the exact error or describe unexpected behavior]
Expected behavior: [what should happen]
Actual behavior: [what actually happens]
What I've already tried: [any debugging steps taken]
Environment: [language version, OS, framework versions]

Provide:
1. Root cause analysis: what's actually causing this error
2. The specific fix with corrected code
3. Why this fix works (explain the underlying issue)
4. How to prevent this type of bug in the future
5. Related bugs that often accompany this one (check for those too)
6. A test case to verify the fix and catch regressions

הכי טוב ל: CHATGPT

ChatGPT identifies bugs fastest and provides the most copy-paste-ready fixes. Its root cause explanations are clear, and it consistently suggests test cases that catch edge cases other models miss.

Tested Feb 15, 2026

טיפים מקצועיים

Always paste the EXACT error message, including the full stack trace. Summarizing errors in your own words removes the line numbers and context that AI needs to pinpoint the problem instantly.

Refactor Coach

Improve code quality and structure

Review and refactor this code for better quality.

[Paste the code to refactor]

Language: [language]
Framework: [if applicable]
Primary concern: [readability / performance / maintainability / all of the above]
Constraints: [backward compatibility, team style guide, performance requirements]
What this code does: [brief description]

Provide:
1. A code quality assessment: what's good and what needs work
2. The refactored code with improvements applied
3. A change-by-change explanation of every modification and its benefit
4. Performance implications of the refactoring (better, same, or trade-offs)
5. Any patterns or abstractions that would make this code more maintainable
6. A checklist to verify the refactored code behaves identically to the original

הכי טוב ל: CLAUDE

Claude produces the most thoughtful refactoring with clear reasoning for each change. It respects existing code patterns and explains trade-offs honestly rather than applying textbook refactoring blindly.

Tested Feb 15, 2026

טיפים מקצועיים

Tell AI about your team's coding style and conventions. Refactored code that doesn't match your team's patterns creates PR review friction. A great refactor that nobody accepts is a wasted refactor.

Algorithm Solver

Solve algorithmic problems step by step

Help me solve this algorithm problem.

Problem: [paste or describe the problem]
Language preference: [language you want the solution in]
Context: [interview prep / competitive programming / real project / learning]
Constraints: [time complexity requirements, space limits, input size]
What I've tried: [any approaches you've attempted]

Provide:
1. Problem breakdown: identify the type of problem and applicable techniques
2. A brute force solution first (with time/space complexity)
3. An optimized solution with explanation of the optimization strategy
4. Step-by-step dry run with a small example input
5. Edge cases to handle and test against
6. Similar problems to practice to reinforce this pattern

הכי טוב ל: GEMINI

Gemini provides the most structured algorithmic explanations with clear complexity analysis. Its dry runs with example inputs are particularly thorough, making it easier to verify the solution mentally.

Tested Feb 15, 2026

טיפים מקצועיים

Always attempt the problem yourself for at least 15 minutes before asking AI. Describe what you tried and where you got stuck. AI teaches much more effectively when building on your partial understanding rather than generating solutions from scratch.

API Integrator

Integrate third-party APIs quickly

Help me integrate with this API.

API: [name of the service/API]
What I need to do: [specific operations: fetch data, send data, authenticate, etc.]
My stack: [language, framework, existing dependencies]
Auth type: [API key / OAuth / JWT / other]
API docs: [paste relevant endpoints or link]
Error handling needs: [retry logic, rate limiting, fallback behavior]

Provide:
1. Complete working code for the integration with all imports
2. Authentication setup with secure credential handling
3. Request/response type definitions or interfaces
4. Error handling for common API failure modes (rate limits, timeouts, 4xx/5xx)
5. A retry strategy with exponential backoff
6. A simple test to verify the integration works before deploying

הכי טוב ל: CHATGPT

ChatGPT has the broadest knowledge of popular APIs and their authentication patterns. Its integration code is production-ready with proper error handling, and it knows platform-specific quirks that save debugging time.

Tested Feb 15, 2026

טיפים מקצועיים

Paste the actual API response format (even a sample) into your prompt. AI generates much more accurate type definitions and parsing logic when it sees real response shapes instead of just endpoint URLs.

Language Launcher

Learn a new programming language fast

Help me get productive in a new programming language quickly.

New language: [the language you want to learn]
Languages I already know: [your current languages]
Goal: [build a specific project / switch jobs / expand skills]
Learning style: [build projects / read docs / solve problems]
Timeline: [how quickly you need to be productive]
Specific area: [web, mobile, systems, data, ML, etc.]

Create:
1. A concept mapping guide: 'In [known language], you do X. In [new language], you do Y'
2. The 20% of syntax that covers 80% of daily coding
3. A 'first weekend' project that teaches core language features hands-on
4. Common gotchas and mistakes developers from [known language] make
5. The ecosystem guide: package manager, testing framework, linter, formatter
6. Five resources (free) ordered from 'start here' to 'go deeper'

הכי טוב ל: GEMINI

Gemini creates the best concept-mapping guides between languages and provides the most up-to-date ecosystem information. Its 'common gotchas' sections are particularly valuable for developers switching from specific languages.

Tested Feb 15, 2026

טיפים מקצועיים

Include the language you're coming FROM, not just the one you want to learn. AI tailors examples to patterns you already understand. A Python developer learning Rust needs completely different explanations than a C++ developer learning Rust.

השוואת מודלים

Based on actual testing — not assumptions. See our methodology

G

Gemini

Best for algorithm problems and learning new languages. Provides structured explanations with thorough complexity analysis. Its ecosystem knowledge is current. Less detailed in complex debugging scenarios.

Results from Gemini 2.0 Flash · Tested Feb 15, 2026
C

ChatGPT

Best for debugging and API integrations. Generates the most production-ready code with comprehensive error handling. Has the broadest knowledge of libraries and frameworks. Can over-engineer simple solutions.

Results from GPT-4o · Tested Feb 15, 2026
C

Claude

Best for code explanations and refactoring. Provides the clearest reasoning for every change and respects existing code patterns. Its code reviews catch subtle issues other models miss.

Results from Claude 3.5 Sonnet · Tested Feb 15, 2026
G

Grok

Strong at debugging and fast practical code solutions with a direct problem-solving style. Excels at concise code reviews and identifying issues quickly, though less thorough on documentation and best practices than GPT-4o.

Results from Grok 2 · Tested Feb 15, 2026

נסו ב-NailedIt

Paste any prompt above into NailedIt and compare models side-by-side.

טיפים מקצועיים

1

Always verify AI-generated code before deploying. AI models can produce code that looks correct but has subtle bugs, security vulnerabilities, or performance issues. Run the code, write tests, and understand every line before putting it into production.

2

Context is everything for good code output. Include your language version, framework, existing patterns, and constraints in every prompt. AI that generates React 17 class components when you use React 19 with hooks wastes your time. Be specific.

3

Use AI to learn, not just to copy-paste. Ask AI to explain WHY the code works, not just to write it. Understanding the reasoning builds your skills. Copying without comprehension creates technical debt you'll pay for later when the code breaks.