ChatGPT Prompts for Software Developers: Code Review, Debugging, Architecture

Published: July 2026 | 10 min read

Software developers are already the heaviest users of AI tools, but most are leaving value on the table. You ask ChatGPT to fix a bug or write a function, but you rarely use it for architecture decisions, code review, test strategy, or documentation. The prompts below go beyond autocomplete — they think like a senior engineer who understands trade-offs, design patterns, and maintainability.

Code Writing & Review

1. Code Review Assistant

Role: Senior software engineer reviewing a pull request
Task: Review the following code changes for quality, correctness, and maintainability.
Language: [programming language]
Context: [What this PR does, what files changed, what feature it implements]
Review checklist:
1. Logic correctness (does it do what it claims?)
2. Edge cases (empty inputs, null values, boundary conditions, race conditions)
3. Security (injection, auth bypass, data exposure, dependency vulnerabilities)
4. Performance (O(n) complexity, N+1 queries, unnecessary allocations, memory leaks)
5. Error handling (try/catch, error messages, graceful degradation)
6. Naming and readability (do names convey intent?)
7. DRY violations (duplicated logic that should be extracted)
8. Test coverage (are the tests adequate? what cases are missing?)
9. API design (is the interface intuitive? backward compatible?)
10. Documentation (does it need comments? docstrings? README updates?)
For each issue found:
1. Severity (Blocker / Major / Minor / Suggestion)
2. File and line reference
3. Issue description
4. Suggested fix (code snippet)
Format: Structured review ready to paste as PR comments.
Constraint: Do not nitpick style if the team has a linter. Focus on issues a linter cannot catch.

2. Function Implementation Generator

Role: Senior [language] developer
Task: Implement a function that [description of what it should do].
Language: [programming language]
Framework: [if applicable]
Inputs: [describe parameters, types, validation rules]
Outputs: [describe return value, error cases]
Constraints:
- Performance: [time/space complexity requirements]
- Dependencies: [what libraries/modules are available]
- Style: [team conventions — naming, error handling pattern, logging]
Requirements:
- Input validation (fail fast with clear errors)
- Error handling (custom exceptions, not generic catches)
- Logging (at appropriate log levels)
- Unit-testable design (dependency injection, pure functions where possible)
- Edge cases: [list specific edge cases to handle]
Output: Complete function with docstring, type hints, and 5+ test cases.
Include: Brief explanation of design decisions and trade-offs.

3. Refactoring Plan

Role: Software architecture refactoring specialist
Task: Create a refactoring plan for [codebase/module description].
Current state: [Describe the code — language, size, main issues, tech debt]
For each refactoring:
1. What to change (specific, not vague)
2. Why (what problem does it solve?)
3. Risk level (Low/Medium/High)
4. Approach (big bang or incremental? why?)
5. Estimated effort (hours/days)
6. Dependencies (what must happen first?)
7. Testing strategy (how do we verify we did not break anything?)
8. Rollback plan (if something goes wrong)
Refactoring priorities:
1. Extract duplicated logic
2. Simplify complex conditionals
3. Reduce coupling between modules
4. Introduce interfaces/abstractions where needed
5. Remove dead code
6. Improve naming
7. Add missing tests
Output: Prioritized refactoring backlog with a 30/60/90 day execution plan.
Format: Refactoring plan ready for tech lead approval.

Debugging & Problem Solving

4. Bug Diagnosis Assistant

Role: Senior debugger / troubleshooting specialist
Task: Help diagnose this bug.
Bug description: [What is happening vs what should happen]
Error message: [Paste exact error, stack trace]
Environment: [OS, runtime version, framework, relevant config]
Reproduction steps: [Exact steps to reproduce]
What I have tried: [List debugging steps already attempted]
Analysis:
1. What could cause this? (list 3-5 hypotheses ranked by likelihood)
2. What data would confirm/refute each hypothesis?
3. What are the next debugging steps? (specific commands, log additions, breakpoints)
4. Is this a known issue? (common pitfalls with [framework/library])
5. Could this be environment-specific? (config, env vars, network, permissions)
Output:
1. Ranked hypothesis list with evidence assessment
2. Debugging action plan (what to check, in what order)
3. Quick fix candidates (if any are identifiable)
4. Long-term fix recommendation (prevent recurrence)
Format: Debugging guide that a junior developer can follow.

5. Performance Profiling Plan

Role: Performance optimization specialist
Task: Create a performance profiling plan for [application/endpoint].
Symptom: [Slow response time, high CPU, memory growth, database bottleneck]
Current metrics: [Response time p50/p95/p99, throughput, resource usage]
Profiling plan:
1. What to measure (specific metrics, instrumentation points)
2. Tools to use (language-specific profilers, APM, load testing tools)
3. Test scenarios (what load to simulate, what endpoints to test)
4. Baseline capture (before any changes, for comparison)
5. Bottleneck identification methodology (flame graph, trace analysis, query analysis)
6. Optimization candidates (what might be slow and why)
7. Validation approach (re-measure after changes, ensure no regression)
Output:
1. Profiling plan document
2. Tool setup instructions
3. Test scenario definitions
4. Expected bottlenecks and optimization ideas
Format: Performance investigation plan ready for execution.

Architecture & Design

6. Architecture Decision Record (ADR)

Role: Software architect documenting a decision
Task: Write an Architecture Decision Record for [decision topic].
Decision: [What technology/pattern/approach was chosen and why]
ADR structure:
1. Title (short, descriptive)
2. Status (Proposed / Accepted / Deprecated / Superseded)
3. Context (what problem are we solving? what constraints exist?)
4. Decision (what we decided — specifically)
5. Alternatives Considered (2-3 other options with pros/cons)
6. Consequences (positive, negative, neutral)
7. Compliance (how do we verify the decision is followed?)
8. Notes (links to relevant docs, discussions, benchmarks)
Format: ADR document following the Michael Nygard template.
Constraint: Be honest about trade-offs — every decision has negative consequences. Document them.

7. System Design Document

Role: Senior system designer
Task: Create a system design for [feature/product description].
Requirements:
- Functional: [what the system must do]
- Non-functional: [performance, scalability, availability, security]
- Constraints: [budget, timeline, team size, existing infrastructure]
Design sections:
1. Context diagram (system boundary, external dependencies)
2. Component architecture (services, modules, data flows)
3. Data model (entities, relationships, storage choices)
4. API design (endpoints, request/response, auth, rate limiting)
5. Technology choices (languages, frameworks, databases, queues)
6. Scalability strategy (horizontal/vertical, caching, sharding, CDN)
7. Reliability strategy (redundancy, failover, circuit breakers, retries)
8. Security strategy (auth, encryption, secrets, network)
9. Observability (logging, metrics, tracing, alerting)
10. Deployment (CI/CD, environments, rollback)
Output: System design document with diagrams described in text, ready for review.
Include: Trade-off discussion — why this design over alternatives?

8. API Design Review

Role: API design specialist
Task: Review this API design for [feature/service].
API: [Describe endpoints, methods, request/response schemas, auth]
Review criteria:
1. RESTful compliance (or GraphQL/whatever paradigm applies)
2. Naming consistency (resource names, field names, conventions)
3. Versioning strategy (how are breaking changes handled?)
4. Error handling (consistent error format, meaningful codes, helpful messages)
5. Pagination (for list endpoints — cursor vs offset, limits)
6. Filtering and sorting (query params, operators, default sort)
7. Rate limiting (per user? per IP? what limits?)
8. Authentication/authorization (token type, scopes, refresh)
9. Idempotency (for POST/PUT — idempotency keys?)
10. Backward compatibility (will existing clients break?)
For each issue:
1. Severity (Critical / Important / Suggestion)
2. Issue description
3. Recommended change (with example)
Format: API review document with specific, actionable feedback.

Testing & Documentation

9. Unit Test Generator

Role: Test-driven development specialist
Task: Write comprehensive unit tests for [function/module name].
Code to test: [Paste the function or describe its interface]
Test framework: [Jest/PyTest/JUnit/etc.]
Test categories:
1. Happy path (normal inputs, expected outputs)
2. Edge cases (empty, single, max, boundary values)
3. Error cases (invalid input, missing data, exceptions)
4. Null/undefined handling
5. Type coercion (if dynamically typed)
6. Concurrency (if applicable — race conditions, ordering)
7. Performance (timeout tests for slow operations)
8. Integration touchpoints (mocks/stubs needed)
For each test:
1. Test name (descriptive: should_X_when_Y)
2. Arrange (setup data, mocks)
3. Act (call the function)
4. Assert (verify result + verify mocks called)
5. Cleanup (if needed)
Generate 15-20 tests with good coverage.
Constraint: Tests should be independent, fast, and deterministic — no flaky tests.

10. Technical Documentation Generator

Role: Technical writer with software engineering background
Task: Create [documentation type] for [project/feature].
Documentation type: [README / API docs / architecture doc / runbook / onboarding guide]
Audience: [Who will read this — developers, ops, new hires, external users]
Include:
1. Overview (what this is, why it exists, how it fits in the system)
2. Prerequisites (what you need before using/contributing)
3. Quick Start (get running in 5 minutes)
4. Configuration (all config options with defaults and descriptions)
5. Architecture overview (main components, data flow, key design decisions)
6. Development guide (how to set up, test, build, deploy)
7. API reference (if applicable — endpoints, params, examples)
8. Troubleshooting (common issues and solutions)
9. FAQ (anticipated questions)
10. Contributing (coding standards, PR process, review criteria)
Format: Markdown documentation ready for the repo.
Constraint: No walls of text — use code examples, diagrams (text-based), and tables.

11. Database Schema Design

Role: Database design specialist
Task: Design a database schema for [application/feature description].
Requirements: [Entities, relationships, queries needed, expected volume]
Database: [PostgreSQL / MySQL / MongoDB / etc.]
For each table/collection:
1. Name (snake_case, plural for tables)
2. Columns/fields (name, type, constraints, default)
3. Primary key (uuid vs serial vs composite?)
4. Foreign keys (references, on delete/update behavior)
5. Indexes (which columns? b-tree? GIN? composite? partial?)
6. Constraints (unique, check, not null)
7. Audit fields (created_at, updated_at, created_by, deleted_at)
Query patterns to support:
1. [Describe the main queries and their frequency]
2. [Which queries need to be fast? What is the access pattern?]
Output:
1. DDL/schema definition (ready to run)
2. ERD description (entities and relationships)
3. Index strategy (which indexes, why, expected impact)
4. Migration plan (if modifying existing schema)
5. Data integrity considerations
Format: Schema design with DDL, ready for review.

12. Pull Request Description Generator

Role: Senior developer writing a PR description
Task: Create a comprehensive PR description for [change description].
Changes: [What files changed, what was added/modified/removed]
PR sections:
1. Summary (2-3 sentences: what this PR does and why)
2. Type of Change (feature / bugfix / refactor / docs / test / chore)
3. Related Issues (ticket #, JIRA link, GitHub issue)
4. Changes Made (bullet list of specific changes)
5. Testing (what tests were added/modified, how to verify)
6. Screenshots/Demo (if UI changes — describe what to look at)
7. Breaking Changes (any? what will break? migration needed?)
8. Checklist:
   - [ ] Code follows style guide
   - [ ] Self-reviewed the code
   - [ ] Added tests for new functionality
   - [ ] All tests pass locally
   - [ ] Documentation updated
   - [ ] No new linting warnings
   - [ ] Dependent changes are merged
9. Deployment Notes (any special steps? feature flags? migrations?)
Format: Ready-to-use PR description that makes review faster.

Best Practices

For more developer content, see our ChatGPT prompts for DevOps engineers and AI prompts for cybersecurity analysts.