Vibe Coding with Claude: 100 Prompts That Actually Ship Products

The term "vibe coding" gets used to mean two very different things. One version is developers who use AI to write code they don't understand and ship products they can't maintain. The other version is developers who use AI to dramatically reduce the time spent on boilerplate, documentation, debugging, and repetitive patterns — so they can spend more time on the actually interesting problems.

The first version is a trap. The second version has changed how I build.

What Changes When You Prompt Well

The traditional development workflow has a lot of overhead that isn't the interesting problem. Setting up auth, writing database migrations, creating API endpoints with proper error handling, writing tests for code you already know works — these things take time but they're not the part of building that requires your specific creativity and judgment.

With good prompting, most of that overhead collapses. A well-specified prompt for a database migration produces something I can read, understand, and deploy in two minutes instead of fifteen. A prompt for a rate limiting implementation gives me a starting point that handles 80% of the edge cases I'd forget to handle on the first pass.

What's left — the actual product decisions, the architecture that's specific to my use case, the UX that makes something feel right — still requires me. The AI handles the scaffolding. I handle the design.

The Prompts That Actually Work

Generic prompts produce generic output. The prompts that produce code I actually use have four things in common:

1. They specify the exact stack. Not "write a database migration" but "write a PostgreSQL migration for adding a nullable text column called 'stripe_customer_id' to the users table, with an index since we'll be doing lookups on it." Specificity eliminates the need for back-and-forth clarification.

2. They include the edge cases upfront. "Handle the case where the user has no previous subscription, the case where the subscription is cancelled, and the case where the Stripe API call fails" in the prompt produces much better results than asking for edge cases after the fact.

3. They specify what NOT to include. "Don't add comments explaining what each line does. Don't add console.log statements for debugging. Don't use any type that isn't strictly typed." Negative constraints are often the most useful constraints.

4. They match the format to the use case. For a function I need to understand and maintain: ask for the implementation plus a one-sentence explanation of any non-obvious decisions. For boilerplate I just need to work: ask for the implementation only.

The Debugging Workflow Change

Production debugging is where AI assistance has surprised me most. When something breaks in production, the traditional workflow is: find the error, understand the error, reproduce the error, fix the error, test the fix. The understanding step is often where time disappears.

Pasting a stack trace with context into Claude and asking "explain what's actually going wrong here, not just where the error is" consistently produces faster and more accurate diagnoses than I can do cold. The model has seen enough error patterns that it recognizes things I haven't seen before. I still verify the fix — but I'm verifying rather than searching.

What It Doesn't Replace

System design. Architecture decisions that will be hard to change later. Choosing the right abstraction. Deciding what not to build. These require the judgment that comes from having built things before, made mistakes, and understood why they were mistakes. The AI can give you options, but it can't tell you which option fits your specific situation without extensive context — and sometimes not even then.

The developers who are getting the most out of AI-assisted coding are the ones who have enough experience to evaluate what the AI produces, catch its mistakes, and make the decisions it can't make. The 100 prompts in this pack are calibrated for that developer — the solo builder who wants to move faster, not someone looking to write code without understanding it.