Request effective code reviews—specify focus areas, provide context, ask for architectural feedback, reference Laravel conventions
Create effective debugging prompts—include error messages, stack traces, expected vs actual behavior, logs, and attempted solutions
Provide comprehensive context in prompts—files, errors, Laravel version, dependencies, and monorepo details—for accurate AI responses
Refine AI-generated code through specific feedback—point out errors, identify gaps, show desired changes, reference style guides
Use Laravel-specific vocabulary—Eloquent patterns, Form Requests, API resources, jobs/queues—to get idiomatic framework code
Structure prompts for clarity—separate concerns, prioritize requests, specify acceptance criteria, and break work into testable increments
Define clear constraints—performance, security, testing, architecture, dependencies—so AI generates code that meets your project standards
Provide concrete examples—existing code patterns, style samples, input/output pairs—to guide AI toward your project's conventions