Test-Driven Development with AI: The First Platform That Writes Tests Before Code

Luna Base is fundamentally different from general-purpose AI coding assistants in three critical ways: Purpose-Built for Test-Driven Development: While tools like GitHub Copilot suggest code completions, Luna Base is specifically engineered for TDD workflows. Our 6 specialized Copilots (Requirements, Architecture, Code, QA, DevOps, and Orchestration) work together as an integrated system, not as isolated suggestion engines. Tests Before Code Eliminates Hallucinations: The fundamental problem with AI-generated code is hallucination—when AI creates code that looks right but behaves incorrectly. Luna Base solves this by inverting the process: we write comprehensive tests FIRST based on your requirements, then generate code that must pass those tests. If the code fails, it's automatically regenerated until all tests pass. This test-first approach acts as a validation layer that catches AI mistakes before they reach your codebase. Guaranteed 95%+ Coverage: Generic coding assistants have no concept of test coverage or quality metrics. Luna Base delivers production-ready code with mathematically verified 95%+ test coverage across unit, integration, and E2E tests. Every function, edge case, and error path is tested. You get deployable software, not just code snippets that need debugging. In essence: other tools help you write code faster. Luna Base ensures the code you ship actually works.

Yes. Luna Base provides enterprise-grade customization for testing standards and organizational policies: Custom Testing Policies: Define your own rules for what constitutes adequate testing. Set minimum coverage thresholds per module, specify which test types are required (unit, integration, E2E), mandate specific test patterns (AAA, BDD, Given-When-Then), and enforce naming conventions. For example, you can require that all API endpoints have both success and error case tests, or that all database operations include rollback testing. Organization-Wide Templates: Create reusable test templates that enforce your team's best practices. These templates can include standard setup/teardown patterns, common mock configurations, approved assertion libraries, and pre-defined test data fixtures. When a developer starts a new feature, Luna Base automatically applies relevant templates, ensuring consistency across your entire codebase. Version-Controlled Configuration: All testing policies, templates, and quality gates are stored as code in your repository. This means they're version-controlled, reviewable through pull requests, and can be different per branch or environment. You can have stricter rules for production branches and more lenient ones for development. Teams can propose policy changes through standard code review processes. Flexible Quality Gates: Configure what must pass before code can be merged: minimum coverage percentage, zero critical security vulnerabilities, performance benchmarks, accessibility standards, or custom metrics specific to your domain. Quality gates can be tiered—different requirements for different parts of your codebase. Luna Base adapts to your organization's needs, not the other way around.

Luna Base excels with complex, domain-specific codebases through intelligent architectural understanding: Requirements Copilot - Domain Complexity Mapping: The first step is understanding your business domain. The Requirements Copilot analyzes your existing codebase, documentation, and API contracts to build a semantic model of your business logic. For a healthcare application, it learns medical terminology, HIPAA requirements, and patient data workflows. For fintech, it understands transaction processing, regulatory compliance, and financial calculations. This domain knowledge informs all subsequent test generation. Architecture Copilot - Pattern Recognition: Complex codebases have architectural patterns—microservices, event-driven systems, domain-driven design, hexagonal architecture, CQRS, etc. The Architecture Copilot reverse-engineers your system design, identifies these patterns, and generates tests that respect your architectural boundaries. If you use dependency injection, tests will properly mock dependencies. If you have event sourcing, tests will verify event streams and projections. Framework and Convention Awareness: Luna Base respects your technology choices. Using a specific ORM like TypeORM or SQLAlchemy? Tests will properly set up database transactions and fixtures. Have custom logging, authentication, or middleware layers? Tests automatically configure these correctly. Your team follows specific coding conventions? Luna Base learns and replicates them in test code. The More Complex, The More Value: Counter-intuitively, Luna Base provides MORE value on complex codebases. Simple CRUD applications are straightforward to test. But systems with intricate business logic, multiple integration points, complex state management, and specialized requirements—that's where Luna Base shines. The AI can reason about edge cases, interaction patterns, and failure modes that are easy to miss in manual testing. We've successfully deployed Luna Base on codebases with 500K+ lines of code, dozens of microservices, and highly specialized domains like medical imaging, financial trading systems, and aerospace software.

Luna Base integrates seamlessly into your existing CI/CD pipeline—no disruption to your current workflow: DevOps Copilot - Pipeline Configuration Generation: The DevOps Copilot automatically generates pipeline configurations for your CI/CD platform. Whether you use GitHub Actions, GitLab CI, Jenkins, CircleCI, Azure DevOps, or Bitbucket Pipelines, Luna Base creates optimized workflows that run your generated tests. These configs include proper caching, parallel execution, test result reporting, and coverage uploads to tools like Codecov or SonarQube. Native Integration with Popular Platforms: For GitHub Actions, we provide a dedicated Luna Base action that integrates with GitHub's native test reporting and check runs. For GitLab CI, we create merge request widgets showing test coverage deltas. For Jenkins, we generate Jenkinsfiles with proper stage definitions and test result collection. Each integration is platform-native, not a generic wrapper. Flexible Execution Models: Run Luna Base tests however you prefer: as a pre-commit hook, in pull request builds, in scheduled nightly runs, or as part of your deployment pipeline. You can configure Luna Base to run only on changed files (fast feedback) or full suite regression testing. Tests are standard test files that execute with your existing test runners—Jest, Pytest, JUnit, etc. Quality Gates and Deployment Blocks: Configure Luna Base to block deployments if coverage drops below thresholds, if critical tests fail, or if security vulnerabilities are detected. These quality gates integrate with your deployment tools—Kubernetes, AWS CodeDeploy, Vercel, Netlify, etc. Failed quality gates can automatically create GitHub issues, send Slack notifications, or trigger incident response workflows. Observability and Reporting: Luna Base exports metrics to your existing observability stack. Send test results to DataDog, New Relic, or Grafana. Track coverage trends over time. Generate executive reports showing testing velocity and quality improvements. All data is available via API for custom integrations. Installation typically takes 30 minutes: add Luna Base to your CI config, connect your repository, and you're running comprehensive tests in your next build.