AI Prompts for Developers: 15 Templates That Actually Work

Why Most Developer AI Prompts Fail

The difference between "fix this bug" and a structured prompt that includes language, error context, expected behavior, and constraints is the difference between a hallucinated answer and a working fix. These 15 prompts follow the structure that senior engineers use to get reliable results from AI.

5 Free Developer Prompts (Preview)

1. Code Review Assistant

Performs structured code review across 5 dimensions: bugs, security, performance, readability, and best practices. Each issue includes severity level, line number, and a fix with corrected code.

• Catches bugs, security issues, and performance problems
• Severity-rated findings (critical/warning/suggestion)
• Includes corrected code for each issue

2. Unit Test Generator

Creates comprehensive test suites covering happy path, edge cases, and error scenarios. Supports Jest, Pytest, JUnit, and other frameworks. Targets 90%+ branch coverage.

• Descriptive test names ("should X when Y")
• Edge cases: empty, null, boundary values
• Setup/teardown included

3. Bug Finder and Fixer

Diagnoses root causes from error messages or symptoms. Provides the fix, explains why the bug occurred, and suggests prevention strategies.

4. Database Query Optimizer

Analyzes slow SQL queries, explains the bottleneck, rewrites the query, and suggests indexes. Includes expected performance improvement estimates.

5. Security Vulnerability Scanner

Checks code against OWASP Top 10: injection, auth issues, data exposure, input validation. Each finding includes severity, attack scenario, and fix.

What's in the Full Prompt Vault

These 5 previews are from the 15 developer prompts. The full vault also includes prompts for API documentation, refactoring, error decoding, regex generation, git commit messages, README creation, migration scripts, performance profiling, and tech debt assessment.

Plus 85 more prompts across marketing, writing, data, operations, and design.