ChatGPT Prompts for Developers — 50 Best Prompts 2026

1. "Write a [language] function that [specific behavior].
   Use [library]. Handle [edge case 1] and [edge case 2].
   Include type hints and docstring."
 
2. "Scaffold a [framework] REST API with endpoints for
   CRUD operations on a [entity] resource. Use [database].
   Include input validation and error responses."
 
3. "Convert this [language A] function to [language B]
   without changing behavior. Preserve all edge case handling."
 
4. "Write a Python script that reads a CSV file, filters rows
   where [column] > [value], and outputs a summary JSON.
   Handle missing values and malformed rows."
 
5. "Generate a SQL migration that adds an index on [column]
   in the [table] table. Use [database] syntax.
   Make it idempotent."

6. "I'm getting this error: [paste error + stack trace].
   Here is the code: [paste code].
   I expected [X] but got [Y]. What's the root cause?"
 
7. "This async function sometimes throws an unhandled
   promise rejection. Here is the code: [code].
   Identify the race condition and fix it."
 
8. "This SQL query is taking 8 seconds on a table with
   1 million rows: [query]. Suggest indexes and
   query rewrites to bring it under 100ms."
 
9. "My React component re-renders on every keystroke
   even though I memoized it. Here is the component: [code].
   Why is the memoization not working?"
 
10. "This function passes unit tests but fails in production
    with large inputs. Code: [code]. What edge cases
    could cause it to fail at scale?"

# Prompt template for code review
prompt = """
Review this code as a senior engineer would in a PR review.
Focus on:
1. Security vulnerabilities (injection, auth, data exposure)
2. Performance issues (N+1 queries, unnecessary loops)
3. Error handling gaps
4. Code style and readability
5. Missing tests
 
Code to review:
[paste code here]
 
Format: numbered list, severity label (critical/medium/low) per item.
"""

11. "List all security vulnerabilities in this code with
    severity ratings and specific fixes."
 
12. "What is the time and space complexity of this algorithm?
    Can you provide a version with better complexity?"
 
13. "This function has 5 responsibilities. Refactor it
    following the single responsibility principle."
 
14. "Add comprehensive error handling to this function.
    Cover network failures, invalid input, and timeout scenarios."

15. "I'm building a [type of application] expected to serve
    [N] requests/second. Should I use a monolith or
    microservices? List trade-offs specific to my scale."
 
16. "Design a database schema for a [domain] application.
    Requirements: [list requirements]. Use [database].
    Show the ERD in text form with relationships."
 
17. "Compare [option A] and [option B] for [use case].
    I care about [priorities]. Give a recommendation
    with reasoning."
 
18. "What are the failure modes in this system design?
    [describe design]. How would you add resilience?"
 
19. "How would you cache [specific data] for this endpoint?
    Traffic: [volume]. Data freshness: [requirement].
    Options: Redis, Memcached, in-memory."

# Auto-generate docstrings
prompt = """
Add a complete Google-style docstring to this function.
Include Args, Returns, Raises, and an Example section.
 
def parse_config(path: str) -> dict:
    with open(path) as f:
        return json.load(f)
"""
 
# Generate README section
prompt = """
Write a README section for this API endpoint.
Include: purpose, authentication, request format (with example JSON),
response format (with example JSON), and error codes.
 
Endpoint: POST /api/v1/users
[describe the endpoint behavior]
"""

20. "Generate inline comments for this complex algorithm.
    Explain the why, not just the what."
 
21. "Write a CHANGELOG entry for these changes: [list changes].
    Use Keep a Changelog format."
 
22. "Write an ADR (Architecture Decision Record) for
    choosing [technology]. Include context, decision,
    consequences, and alternatives considered."

23. "Write pytest unit tests for this function.
    Cover: happy path, edge cases, error conditions,
    and boundary values. Mock external dependencies."
 
24. "Identify what's not tested in this code and write
    the missing test cases."
 
25. "Write a property-based test using Hypothesis for
    this function: [function]. Focus on [property]."
 
26. "Generate test data for a form with these fields:
    [list fields with types and constraints].
    Include valid cases and 5 invalid cases per field."

27. "Explain [concept] to someone who knows [related concept]
    but not [target concept]. Use a concrete analogy."
 
28. "What are the 5 most common mistakes developers make
    when first learning [technology]? Show an example
    of each mistake and the correct approach."
 
29. "I know [language A] well. What are the most surprising
    differences when moving to [language B]? Focus on
    patterns that look valid but behave differently."
 
30. "Create a minimal working example of [pattern/concept]
    in [language]. No unnecessary boilerplate."

# Performance review prompt
prompt = """
Profile this code and identify the top 3 performance
bottlenecks. Suggest specific optimizations for each.
Estimate the expected speedup.
 
Code:
[paste code]
 
Context: This runs on [hardware], processes [N] items,
and needs to complete in under [time limit].
"""

31. "This endpoint takes 2 seconds to respond.
    Here is the query and relevant indexes: [info].
    What indexes or query changes would help most?"
 
32. "Optimize this Python loop for a list of 10 million items.
    Use NumPy/vectorization where appropriate."
 
33. "How would you reduce memory usage in this data pipeline?
    Current peak: [N] GB. Target: [M] GB."