How to Build a Developer Tool with AI in a Weekend

I built and shipped a developer tool in a weekend using AI coding assistants. Not a toy — a real tool that other developers use. Here is exactly how I did it, step by step.

The Idea

The tool: a CLI that analyzes your project's dependencies and tells you which ones have AI-powered alternatives. You run ai-deps check and it outputs a list of dependencies that could be replaced or augmented with AI tools.

Simple, useful, shippable in a weekend.

Friday Evening: Scaffolding (2 hours)

Step 1: Project Setup

I started by telling Claude what I wanted to build:

I want to build a Node.js CLI tool called "ai-deps" that:
1. Reads package.json from the current directory
2. Checks each dependency against a database of AI alternatives
3. Outputs suggestions in a formatted table
4. Publishes to npm

Give me the project structure and initial setup.

Claude generated:

• package.json with proper bin configuration
• tsconfig.json for TypeScript
• src/index.ts with argument parsing (using commander)
• src/analyzer.ts for the core logic
• .github/workflows/publish.yml for automated npm publishing

Total time: 10 minutes for the initial scaffold.

Step 2: Core Logic

I used Cursor to implement the analyzer:

// In Cursor Composer:
// "Implement the dependency analyzer. It should:
// 1. Read package.json dependencies and devDependencies
// 2. Check each against the AI_ALTERNATIVES map
// 3. Return a list of suggestions with: current dep, AI alternative, reason
// 4. Handle missing package.json gracefully"

Cursor generated the complete implementation with error handling, TypeScript types, and even a reasonable default mapping of common packages to AI alternatives.

I spent 30 minutes manually curating the AI alternatives database — this is the kind of domain knowledge AI cannot generate.

Step 3: CLI Interface

Back to Cursor:

// "Add a formatted table output using the chalk and cli-table3 packages.
// Show: Dependency, AI Alternative, Category, Reason.
// Add color coding: green for direct replacements, yellow for augmentations.
// Add a --json flag for machine-readable output."

Cursor generated the CLI output formatting. The result looked professional immediately.

Friday total: 2 hours. I had a working CLI that reads dependencies and outputs suggestions.

Saturday: Features and Polish (6 hours)

Step 4: Testing

I asked Cursor to generate tests:

// "Generate Vitest tests for the analyzer module.
// Test: valid package.json, missing file, empty dependencies,
// dependencies with known alternatives, dependencies without alternatives.
// Use temp directories for file system tests."

Cursor generated 12 test cases. I adjusted 3 of them for edge cases and added 2 more for specific scenarios I cared about. Total testing time: 45 minutes.

Step 5: README

// "Generate a README.md with: project description, installation (npm),
// usage examples, output screenshot placeholder, configuration options,
// contributing guidelines, and license (MIT)."

Claude generated a comprehensive README. I edited the description to be more specific and added a real usage example. Time: 20 minutes.

Step 6: Error Handling and Edge Cases

I used Claude to think through edge cases:

Here is my CLI tool code. [paste]
What edge cases am I missing? What errors could users encounter?

Claude identified:

• Monorepo support (multiple package.json files)
• Workspace dependencies
• Lock file parsing for accurate version detection
• Network errors if I add an online database later
• Permission errors reading files

I implemented the top 3 with Cursor. Time: 2 hours.

Step 7: npm Publishing Setup

Claude generated the GitHub Actions workflow for automated publishing:

# On push to main with version tag
on:
  push:
    tags: ['v*']

jobs:
  publish:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: 20
          registry-url: https://registry.npmjs.org
      - run: npm ci
      - run: npm test
      - run: npm publish
        env:
          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}

Time: 15 minutes.

Saturday total: 6 hours. The tool is tested, documented, and ready to publish.

Sunday: Ship It (3 hours)

Step 8: Final Polish

• Added a --verbose flag for detailed output
• Added a --ignore flag to skip specific dependencies
• Cleaned up TypeScript types
• Ran the linter and fixed issues

Most of this was done with Cursor's inline editing. Time: 1.5 hours.

Step 9: Publish

npm login
git tag v1.0.0
git push --tags

GitHub Actions ran the tests and published to npm automatically. Time: 15 minutes.

Step 10: Launch

• Posted on Reddit (r/webdev, r/node)
• Tweeted about it with a screenshot
• Submitted to a few developer tool directories

Time: 1 hour.

What AI Did Well

1. Scaffolding. Project setup that would take an hour took 10 minutes.
2. Boilerplate. CLI argument parsing, table formatting, error handling — all boilerplate that AI generates perfectly.
3. Tests. 80% of test cases were generated correctly.
4. Documentation. README, contributing guide, and inline comments.
5. CI/CD. GitHub Actions workflow was correct on the first try.

What I Did Manually

1. Domain knowledge. The mapping of packages to AI alternatives required my expertise.
2. UX decisions. How the output should look, what flags to support, what information is most useful.
3. Edge case prioritization. AI identified edge cases; I decided which ones to handle.
4. Marketing. AI cannot post on Reddit for you (yet).

The Numbers

• Total development time: 11 hours over a weekend
• Lines of code: ~800 (TypeScript)
• Estimated time without AI: 25-30 hours (2-3 weekends)
• Time saved by AI: ~60%
• npm downloads (first week): 340

AI did not build the tool for me. It accelerated the parts that are mechanical — scaffolding, boilerplate, tests, docs — so I could spend my time on the parts that matter: the idea, the UX, and the domain knowledge.

That is the real power of AI coding assistants. Not replacement, but acceleration.

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