📋 Table of Contents
Introduction
Why Claude is the Best AI for Developers
Claude by Anthropic consistently outperforms other AI models on complex coding tasks. Its 200K token context window means you can paste an entire codebase and ask Claude to reason across all of it simultaneously — something GPT-4o struggles with at 128K tokens.
But the real differentiator is instruction following. Claude doesn't just give you code — it reasons through problems step by step, explains its decisions, and catches edge cases most developers miss. This is why top engineering teams at Stripe, Notion, and dozens of YC startups have adopted Claude as their primary coding assistant.
If you want to go deeper on AI tools for development, read our guide on Best AI Tools for Website Development and our Groq AI for Startups post for ultra-fast inference options.
| Feature | Claude Sonnet 4 | GPT-4o | Gemini 1.5 Pro |
|---|---|---|---|
| Context Window | 200K tokens | 128K tokens | 1M tokens |
| Code Quality | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Instruction Following | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ |
| Reasoning Depth | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Best For | Complex coding | General tasks | Long documents |
| Free Tier | Yes (claude.ai) | Yes (limited) | Yes (limited) |
💡 How to use these prompts: Replace every [bracket] with your specific details. The more specific you are, the better Claude's response. Always include your language, framework version, and what you already tried.
01 — Code Generation
Code Generation Prompts (1–10)
These prompts turn Claude into your personal senior developer. Use them when you need production-ready code from scratch. The key is always giving Claude the full requirements upfront — input types, output format, edge cases, and testing requirements.
01 Write a Complete Function
Write a [language] function called [name] that [what it does].
Requirements:
- Input: [describe inputs with types]
- Output: [describe output with type]
- Edge cases to handle: [list edge cases]
- Performance: must handle [X] items in under [Y]ms
- Add full docstring/JSDoc comments
- Include 5 unit tests covering happy path and edge cases
- Use [specific library] if available
02 REST API Endpoint
Create a production-ready [FastAPI/Express/Django] REST API endpoint for [feature].
Specs:
- Method: [GET/POST/PUT/DELETE]
- Route: /api/v1/[resource]
- Auth: [JWT/API key/none]
- Request body: { [fields with types] }
- Success response: { [fields] }
- Error responses: 400, 401, 404, 500
Requirements:
- Input validation with descriptive error messages
- Rate limiting: [X] requests per minute
- Logging for debugging
- Add inline comments explaining business logic
03 React Component with Full Features
Build a React functional component: [ComponentName]
Props (TypeScript interface):
- [propName]: [type] - [description]
- [propName]: [type] - [description]
Features needed:
- Loading state with skeleton UI
- Error state with retry button
- Empty state with helpful message
- Mobile responsive (Tailwind CSS)
- Accessible (ARIA labels, keyboard nav)
- Memoized with useMemo/useCallback where appropriate
Export as default. Include usage example in a comment.
04 Database Schema Design
Design a PostgreSQL database schema for [app type: e.g. SaaS, e-commerce, blog].
Core features:
- [feature 1: e.g. user authentication]
- [feature 2: e.g. subscription billing]
- [feature 3: e.g. content management]
Requirements:
- UUID primary keys
- Soft deletes (deleted_at)
- created_at, updated_at timestamps on every table
- Row-level security (RLS) policies
- Foreign key constraints with ON DELETE behavior
- Indexes for common query patterns
Write: CREATE TABLE statements, indexes, RLS policies.
Explain your design decisions and any tradeoffs.
05 Algorithm with Analysis
Implement [algorithm name] in [language].
Step by step:
1. Explain the algorithm in plain English (2-3 sentences)
2. Write pseudocode first
3. Write the actual implementation with comments
4. State time complexity: O(?) and why
5. State space complexity: O(?) and why
6. Show 3 input/output examples
7. Describe when to use vs avoid this algorithm
06 Docker + Docker Compose
Write production-ready Docker config for: [stack e.g. FastAPI + PostgreSQL + Redis + Nginx]
Requirements:
- Multi-stage Dockerfile (builder + runtime)
- Non-root user for security
- .dockerignore to minimize image size
- docker-compose.yml with:
- Named volumes for data persistence
- Health checks for each service
- Environment variables via .env.example
- Resource limits (CPU/memory)
- Restart policies
- Commands to build, run, and check logs
07 GitHub Actions CI/CD Pipeline
Create a complete GitHub Actions CI/CD pipeline for [language/framework].
Pipeline stages:
1. Lint (ESLint/Flake8/etc)
2. Type check (TypeScript/mypy)
3. Unit tests with coverage report
4. Integration tests
5. Build Docker image
6. Push to registry ([ECR/GCR/DockerHub])
7. Deploy to [staging/production] on [platform]
Extra:
- Cache dependencies for speed
- Run only affected tests on PR
- Auto-create GitHub release on tag push
- Slack notification on failure with commit link
08 Web Scraper with Anti-Detection
Write a Python web scraper to extract [data type] from [website type].
Requirements:
- Use Playwright for JS-heavy sites or requests+BS4 for static
- Rotate user agents
- Respect robots.txt
- Rate limiting: random delay 1-3 seconds between requests
- Handle pagination automatically (detect next page)
- Retry on failure (3 attempts with exponential backoff)
- Save to: CSV + JSON + SQLite
- Resumable: skip already-scraped URLs
- Log progress with rich/tqdm progress bar
09 CLI Tool
Build a Python CLI tool using Typer (or Click) that [what it does].
Commands:
- [command]: [description] — args: [list]
- [command]: [description] — args: [list]
Features:
- Colorized output using Rich
- Progress bars for long operations
- Config file support (~/.config/[tool]/config.yaml)
- --verbose flag for debug output
- --output [json|csv|table] format flag
- Proper exit codes (0=success, 1=error)
- Comprehensive --help text
- Shell completion (bash/zsh)
10 Regex Pattern Builder
Build a regex pattern to [validate/extract/replace] [what].
Provide:
1. The regex pattern
2. Named capture groups where relevant
3. Break down each part of the regex with comments
4. Python implementation using re module
5. JavaScript implementation
6. Test with 5 valid matches and 5 non-matches
7. Known limitations or edge cases this pattern misses
02 — Debugging
Debugging Prompts (11–20)
Debugging with Claude is dramatically faster than Stack Overflow. The key is providing the full error trace, the relevant code, what you expected, and what you got. Claude will not just fix the bug — it will explain the root cause so you don't repeat it.
For a broader look at AI-assisted development workflows, check our post on AI Automation for Beginners.
11 Fix This Error
I'm getting this error:
[paste full error message and stack trace]
My code:
[paste the relevant code]
Context:
- Language/framework: [name + version]
- OS: [Windows/Mac/Linux]
- What I expected: [describe]
- What actually happened: [describe]
- What I already tried: [list attempts]
Find the root cause, explain exactly why this error occurs,
then provide the corrected code with comments on the fix.
12 Performance Optimization
This code is too slow. Profile and optimize it:
[paste code]
Performance data:
- Current: [e.g. 8 seconds for 10,000 records]
- Target: [e.g. under 500ms]
- Data volume: [X records, Y MB]
- Bottleneck (if known): [e.g. DB queries, loops, I/O]
For each optimization:
1. What you changed
2. Why it's faster
3. The tradeoff (if any)
Show before/after complexity analysis.
13 Memory Leak Hunt
My [Node.js/Python/Go] app has a memory leak.
Code:
[paste the relevant modules]
Symptoms:
- Memory grows from [X]MB to [Y]MB over [time period]
- Happens when: [describe trigger — e.g. after 1000 requests]
- Does not happen when: [describe]
Find: the exact leak location, explain why it leaks,
provide the fix, and explain how to prevent this pattern in future.
14 Logic Bug Walkthrough
There's a logic bug in this function:
[paste function]
Test case:
- Input: [exact input value]
- Expected output: [exact expected value]
- Actual output: [exact actual value]
Walk through the code execution line by line,
identify where the logic diverges from expectation,
and fix it. Explain the fix in one sentence.
15 API Debugging
My API call is failing. Full details:
Request:
- URL: [full URL]
- Method: [GET/POST/PUT/DELETE]
- Headers: [paste relevant headers]
- Body: [paste request body]
Response:
- Status: [e.g. 401, 400, 500]
- Body: [paste response body]
- Error message: [paste]
My code: [paste]
What is wrong? Give me the fixed code and explain the cause.
16 Async/Race Condition Fix
I have an async bug in [JavaScript/Python/Go]:
[paste code]
Symptoms:
- [race condition / unhandled rejection / deadlock / callback hell]
- Happens [always/intermittently/only under load]
Explain:
1. What the async issue is
2. Why it occurs (execution order diagram if helpful)
3. The fix
4. Best practices to avoid this class of bug in future
17 SQL Query Debugging
Fix and optimize this SQL query:
[paste query]
Problem: [wrong results / timeout / error message]
Schema: [paste CREATE TABLE statements]
Expected result: [describe]
Data volume: [X rows in each table]
Database: [PostgreSQL/MySQL/SQLite] [version]
Fix the query, explain what was wrong,
and optimize for performance (add indexes if needed).
18 CSS Layout Debugging
My CSS layout is broken:
[paste HTML + CSS]
Problem: [describe exactly what looks wrong]
Expected: [describe what it should look like]
Browser: [Chrome/Firefox/Safari] [version]
Viewport: [mobile/desktop/both]
Framework: [Tailwind/Bootstrap/vanilla]
Fix the layout, explain the CSS property that caused it,
and suggest how to avoid this class of layout bug.
19 Failing Test Investigation
This test is failing:
Test file:
[paste test code]
Source file being tested:
[paste source code]
Test output:
[paste full test error output]
Question: Is the bug in the test or the source?
Answer with: root cause, which file needs fixing, corrected code.
20 Environment Setup Fix
My dev environment won't work. Please help me fix it:
OS: [Windows 11 / macOS 14 / Ubuntu 22.04]
Language + version: [e.g. Python 3.11, Node 20]
Framework: [e.g. Next.js 14, FastAPI 0.100]
Package manager: [pip/npm/yarn/pnpm/poetry]
Error: [paste full error output]
Steps I already tried: [list exactly what you did]
Give me numbered steps to fix this from scratch.
Explain why each step is needed.
03 — Code Review
Code Review Prompts (21–30)
Use Claude as your always-available senior code reviewer. Unlike human reviewers, Claude never gets tired, never skips edge cases, and will give you brutally honest feedback at any time. These prompts are structured to get the most actionable reviews possible.
21 Senior Engineer Code Review
Review this code like a principal engineer at a top tech company:
[paste code]
Evaluate these 6 dimensions (rate 1-10 + specific feedback):
1. Correctness — does it handle all cases?
2. Security — any vulnerabilities?
3. Performance — any bottlenecks?
4. Readability — can a junior understand it?
5. Maintainability — easy to change in 6 months?
6. Test coverage — what's missing?
End with: top 3 things to fix before this goes to production.
22 Security Audit
Security audit this code. Check for ALL of these:
[paste code]
Vulnerability checklist:
□ SQL injection
□ XSS (reflected, stored, DOM)
□ CSRF
□ Insecure direct object references
□ Authentication bypass
□ Sensitive data in logs/errors
□ Hardcoded secrets
□ Insecure dependencies
□ Missing input validation
□ Improper error handling (stack traces exposed)
For each issue found:
- Severity: Critical/High/Medium/Low
- Exact line number
- Proof of concept attack
- Secure fix
23 Refactor for Clean Code
Refactor this code applying clean code principles:
[paste code]
Apply in this order:
1. Extract magic numbers/strings to named constants
2. Break functions >20 lines into smaller functions
3. Rename unclear variables/functions
4. Apply DRY — extract duplicated logic
5. Apply SOLID principles where relevant
6. Improve error handling
Rules:
- Do NOT change functionality
- Explain every rename/extraction
- If you skip a principle, explain why
24 Pull Request Review
Review this PR like a senior GitHub reviewer:
[paste git diff or code changes]
Context:
- This PR: [what feature/fix it implements]
- Ticket: [link or description]
- Risk level: [low/medium/high]
Format your review as:
✅ LGTM — things done well
💬 SUGGESTION — optional improvements (non-blocking)
⚠️ CONCERN — should fix before merge (blocking)
❌ REJECT — must fix, explains why
End with: Approve / Request Changes / Need More Info
25 API Design Review
Review this REST API design for correctness and best practices:
[paste your endpoints, methods, request/response examples]
Check against:
- RESTful conventions (correct HTTP methods/status codes)
- URL naming (plural nouns, lowercase, hyphens)
- Versioning strategy (/v1/)
- Authentication design
- Pagination approach
- Error response format consistency
- Rate limiting headers
- HATEOAS (if applicable)
Suggest a revised API spec if improvements are needed.
26 Database Query Optimization
Optimize this database query for production scale:
[paste query]
Context:
- Database: [PostgreSQL/MySQL] [version]
- Table sizes: [table1: X rows, table2: Y rows]
- Current execution time: [X ms]
- Target: [Y ms]
- Existing indexes: [list]
Provide:
1. EXPLAIN ANALYZE output (predicted)
2. Suggested indexes with CREATE INDEX statements
3. Rewritten query if structure can be improved
4. Estimated new execution time
27 Error Handling Review
Audit the error handling in this code:
[paste code]
Find every place where:
□ Errors are silently swallowed (bare except/catch)
□ Generic exceptions are caught instead of specific ones
□ Error messages expose internal implementation details
□ Retries aren't implemented for transient failures
□ The user sees a 500 when they should see a 400
□ Errors aren't logged with enough context
Rewrite with proper error handling throughout.
28 Test Coverage Analysis
Analyze test coverage gaps for this code:
[paste source code]
Existing tests:
[paste test file or describe what's tested]
Create a coverage report listing:
1. Untested happy paths
2. Untested edge cases
3. Untested error paths
4. Missing integration tests
5. Missing performance tests
Then write the 5 highest-priority missing tests using [pytest/Jest/Vitest].
29 Complexity Deep-Dive
Analyze every function in this code for complexity:
[paste code]
For each function provide:
| Function | Time | Space | Can Improve? |
|----------|------|-------|--------------|
Then for any function you marked "Can Improve":
- Explain the current inefficiency
- Show the optimized version
- State the new complexity
30 Dependency Audit
Audit my project dependencies:
[paste package.json / requirements.txt / go.mod]
For each dependency, flag:
🔴 CRITICAL — known CVE or abandoned (no commits in 2+ years)
🟡 WARNING — better alternative exists
🟢 OK — fine as-is
Then list:
- Unused dependencies to remove
- Dependencies that overlap in functionality
- Missing dependencies for my use case: [describe app type]
Provide the updated dependency file.
04 — Documentation
Documentation Prompts (31–40)
Good documentation is the difference between a project people adopt and one they abandon. Use these prompts to generate professional docs, READMEs, changelogs, and technical specifications — all in minutes instead of hours.
31 Professional README
Write a professional README.md for this project:
Project: [name]
One-liner: [what it does in one sentence]
Stack: [language, framework, database, hosting]
Key features:
- [feature 1]
- [feature 2]
- [feature 3]
Target audience: [developers / end users / both]
Include sections:
- Badges (build, coverage, license, version)
- Demo GIF placeholder
- Quick start (≤5 commands to get running)
- Full installation guide
- Configuration options table
- API reference (if applicable)
- Contributing guide
- License
32 OpenAPI Documentation
Write complete OpenAPI 3.0 documentation for these endpoints:
[paste endpoint code or descriptions]
For each endpoint include:
- Summary and description
- All parameters with types, required flag, examples
- Request body schema with all fields
- Response schemas for: 200, 400, 401, 403, 404, 500
- At least 2 cURL examples per endpoint
- Authentication requirements
Output as valid YAML.
33 Smart Code Comments
Add professional comments to this code:
[paste code]
Comment philosophy:
- Explain WHY, not WHAT (the code shows what)
- Comment surprising decisions with a NOTE: prefix
- Mark todos as TODO: [what] — [why not done yet]
- Add FIXME: for known issues
- Full [JSDoc/Google-style Python] docstrings on all public functions
Do NOT comment obvious things like:
// increment counter
i++
34 Technical Architecture Doc
Write a technical architecture document for this system:
[describe your system in detail]
Document sections:
1. Executive Summary (non-technical, 3 sentences)
2. System Overview
3. Component Diagram (ASCII art)
4. Data Flow Diagram (ASCII art)
5. Technology Decisions (why each tech was chosen)
6. Scalability Plan (how to handle 10x traffic)
7. Known Limitations
8. Security Considerations
9. Disaster Recovery
10. Glossary
35 Step-by-Step Tutorial
Write a complete tutorial: "How to [achieve X] with [technology]"
Target reader: [beginner/intermediate/advanced] [language] developer
What they'll build: [end result]
Time to complete: [estimated minutes]
Structure:
- What You'll Build (with final code link)
- Prerequisites (exact versions)
- Part 1: [setup] — numbered steps
- Part 2: [core feature] — numbered steps
- Part 3: [advanced/production] — numbered steps
- Testing It Works
- Common Mistakes + Solutions
- Next Steps + further reading
36 Changelog Generator
Generate a CHANGELOG.md from these git commits:
[paste: git log --oneline --no-merges]
Rules:
- Group by: Added / Changed / Deprecated / Removed / Fixed / Security
- Group commits into semantic versions (infer from commit messages)
- Write for end users, not developers (translate technical commits)
- Follow Keep a Changelog (keepachangelog.com) format
- Mark breaking changes with ⚠️ BREAKING
37 Incident Postmortem
Write a blameless postmortem for this incident:
Incident summary: [what broke]
Start time: [when detected]
Resolution time: [when fixed]
Impact: [X users affected, Y% error rate, $Z revenue impact]
Root cause: [technical cause]
Contributing factors: [list]
Write sections:
- Executive Summary
- Timeline (with UTC timestamps)
- Root Cause Analysis (5 Whys)
- Contributing Factors
- What Went Well
- Action Items (owner, due date, priority)
- Lessons Learned
38 Developer Onboarding Guide
Write a developer onboarding guide for a new engineer joining the team.
Project: [name and brief description]
Stack: [list technologies]
Repo structure: [describe key folders]
Team size: [X engineers]
Deployment: [how code gets to production]
Cover:
Day 1: Machine setup (exact commands for Mac + Linux)
Day 2: Run the app locally + make first commit
Day 3: Architecture walkthrough
Week 1: First real task checklist
Ongoing: Code review process, git workflow, deployment, who to ask for what
39 Product Requirements Document
Write a Product Requirements Document (PRD) for this feature:
Feature name: [name]
User story: As a [user type], I want to [action] so that [benefit]
Sections:
- Problem Statement
- Goals & Non-Goals
- User Stories (5-10, with acceptance criteria)
- Technical Requirements
- UX Requirements (wireframe descriptions)
- API Changes (if any)
- Database Changes (if any)
- Security Considerations
- Analytics Events to Track
- Launch Plan (rollout %)
- Success Metrics
40 Non-Technical Status Update
Write a status update email for a non-technical manager/stakeholder:
Situation: [technical description of what happened]
Impact on users: [what users experienced]
Current status: [fixed/investigating/monitoring]
Root cause: [1 sentence, no jargon]
What we did: [what the fix was, no technical details]
Prevention: [what we're doing to prevent recurrence]
Tone: professional, confident, no blame, no jargon.
Length: under 200 words.
05 — Architecture
Architecture & System Design Prompts (41–50)
These are the most powerful prompts in this list. Use them when designing new systems, preparing for system design interviews, or getting a second opinion on major technical decisions. For more on AI-powered architecture tools, see our post on Groq Cloud for High-Speed AI Inference.
41 Full System Design
Design a production-ready system for [use case, e.g. URL shortener / ride-sharing / notification service].
Scale requirements:
- Daily active users: [X]
- Requests per second: [peak Y, average Z]
- Data storage: [estimated GB/TB]
- Read/write ratio: [X:1]
- Latency SLA: [Xms p99]
Design:
1. High-level architecture diagram (ASCII)
2. Database choice + schema (justify)
3. Caching layer (what, where, TTL)
4. Load balancing strategy
5. Horizontal scaling approach
6. Failure modes + mitigations
7. Estimated infrastructure cost/month
42 Technology Decision
Help me choose between [Option A] vs [Option B] for [use case].
My context:
- Team size: [X engineers, skill level: junior/mid/senior]
- Traffic: [X req/day, growing Y% monthly]
- Budget: [$X/month infra]
- Timeline: [X weeks to launch]
- Must-have features: [list]
- Nice-to-have: [list]
Compare on: performance, learning curve, ecosystem, cost at scale, hiring availability, long-term viability.
Give a clear final recommendation with your top 3 reasons.
43 Caching Architecture
Design a complete caching strategy for this application:
[describe app, data models, access patterns]
Current problem: [slow queries / high DB load / high latency]
Budget for Redis: [$X/month — so max Y GB]
Design:
1. What to cache (and what NOT to cache)
2. Cache levels: L1 (in-memory) → L2 (Redis) → L3 (CDN)
3. Cache key naming convention
4. Invalidation strategy for each cache type
5. TTL values per data type
6. Cache warming strategy
7. Monitoring: what metrics to watch
Include Python/Node.js implementation snippets.
44 Microservices Migration
Plan a monolith → microservices migration for this app:
[describe current monolith: tech stack, modules, DB schema]
Current pain points: [list: deployments, scaling, team conflicts]
Team structure: [X teams of Y developers each]
Timeline available: [X months]
Risk tolerance: [low/medium/high]
Provide:
1. Which service to extract first (and why — Strangler Fig pattern)
2. Migration phases with milestones
3. How to handle shared database (gradual separation)
4. API contract approach between services
5. What to NOT migrate (keep in monolith)
6. Rollback plan for each phase
45 Authentication System Design
Design a complete authentication and authorization system:
App type: [B2C SaaS / B2B SaaS / API / mobile app]
User types: [list roles: admin, user, viewer, etc.]
Requirements:
□ Email/password
□ Social login (Google, GitHub)
□ Magic link
□ SMS 2FA / TOTP
□ SSO (SAML / OIDC)
□ API keys for developers
□ Role-based access control (RBAC)
Design: token strategy (JWT vs opaque), session management,
refresh token rotation, RBAC implementation, security headers.
Include implementation code for [your framework].
46 Data Pipeline Design
Design a data pipeline for [use case]:
Sources: [list data sources + formats]
Volume: [X events/day, Y GB/day]
Latency requirement: [real-time <1s / near-real-time <1min / batch daily]
Destination: [data warehouse, ML model, dashboard]
Budget: [$X/month]
Design:
- Ingestion layer (Kafka/Kinesis/Pub-Sub vs batch)
- Processing (Flink/Spark/dbt vs simple ETL)
- Storage (data lake + warehouse)
- Orchestration (Airflow/Prefect/Dagster)
- Monitoring + alerting
- Estimated cost at scale
47 Cloud Cost Optimization
Analyze and reduce my cloud infrastructure costs:
Current setup:
[paste: EC2/GCE/Azure VM sizes, RDS specs, storage, data transfer]
Monthly bill: [$X]
Traffic pattern: [constant / business hours / spiky]
Goal: reduce by 40%+ without degrading performance
Analyze:
1. Right-sizing opportunities
2. Reserved vs spot vs on-demand tradeoffs
3. Storage tier optimization
4. Data transfer cost reduction
5. Architectural changes (serverless, managed services)
6. Projected savings per change with effort estimate
48 Code Migration Planner
Plan and execute this code migration:
From: [old technology/version]
To: [new technology/version]
Code to migrate: [paste or describe]
Provide:
1. Migration risk assessment (low/medium/high + why)
2. Breaking changes to handle
3. Migrated code with side-by-side comparison
4. Test strategy to verify correctness
5. Rollback plan
6. Phased rollout recommendation
49 System Design Interview Prep
Give me a realistic system design interview for [company level: FAANG/startup/mid-size].
My background: [X years experience, current role]
Target role: [Senior/Staff/Principal Engineer]
Run the interview:
1. Give me the problem statement (be realistic to actual interviews)
2. Let me answer (I'll type my response)
3. Ask follow-up questions like a real interviewer
4. Then give me detailed feedback:
- What I got right
- What I missed
- What a top candidate would have added
- Overall score: pass/borderline/fail
50 ⚡ The Ultimate Master Prompt
You are a principal software engineer with 15 years of experience at top tech companies. You are known for:
- Asking clarifying questions before jumping to solutions
- Thinking about edge cases most engineers miss
- Explaining tradeoffs instead of just giving answers
- Teaching juniors while solving problems
My situation:
- I am building: [describe your project in detail]
- My stack: [list all technologies and versions]
- My team: [size, experience level]
- The challenge: [describe problem in detail]
- What I've already tried: [list all attempts]
- My constraints: [time, budget, technical debt]
Step 1: Ask me your top 3 clarifying questions.
Step 2 (after I answer): Give your recommendation with code.
Step 3: Tell me the top 3 things that could go wrong and how to prevent them.
Pro Tips
How to Get 10x Better Results from Claude
💡 Tip 1 — Be Specific: "Fix my code" gets average results. "Fix the NullPointerException on line 42 in UserService.java that occurs when userId is null during session timeout" gets excellent results.
💡 Tip 2 — Give Context: Always include your language, framework version, OS, and what you already tried. Claude's answer quality is directly proportional to context quality.
💡 Tip 3 — Use Follow-ups: Claude has a 200K token memory within a conversation. After getting working code, ask "now add error handling" or "now write tests for this" without repeating the code.
💡 Tip 4 — Request Formats: Say "respond with a markdown table" or "give me numbered steps" or "respond only in JSON" to get structured output you can use immediately.
⚠️ Warning: Never paste real API keys, passwords, or personally identifiable information into Claude. Use placeholder values like [YOUR_API_KEY] in prompts.
What These Prompts Will Do For You
- Save 2-4 hours per day on repetitive coding tasks
- Catch bugs before production with thorough code review prompts
- Write documentation in minutes instead of hours
- Make better architecture decisions with Claude as your senior advisor
- Ace system design interviews by practicing with Prompt 49
Want to go further? Read our complete guide on AI Automation for Beginners and learn how to combine Claude with Groq for blazing-fast AI workflows in our Groq for Startups post.