Everything as Code: How We Manage Our Company in One Monorepo

Why It Matters

A unified repository turns AI tools into real‑time validators and accelerators, giving companies a competitive edge in speed and consistency. It shows how monorepos can power AI‑native development at scale.

Key Takeaways

• One repo holds code, docs, marketing, and extensions
• Single JSON config syncs pricing across all layers
• AI validates backend, frontend, docs changes in one step
• CI pipelines trigger only for changed directories, speeding builds
• Repo size stays under 1 GB, clone under 20 seconds

Pulse Analysis

The rise of monorepos has moved beyond large tech giants to startups seeking tighter feedback loops. Kasava’s "everything‑as‑code" strategy treats documentation, marketing copy, and even email templates as first‑class code, allowing a single Git push to propagate changes across product and brand. This eliminates the classic "source of truth" drift that plagues organizations with separate CMSs and codebases, and it gives AI assistants immediate access to the exact artifacts they need to verify or generate, dramatically cutting review cycles.

From an engineering perspective, Kasava sidesteps many monorepo pitfalls by keeping each sub‑project isolated with its own npm install and dedicated CI workflows. Selective GitHub Actions trigger only when relevant paths change, so build times remain fast despite a 5,470‑file TypeScript codebase. Shared linting, formatting, and TypeScript configs enforce consistency, while lightweight tools like Turbopack and Wrangler keep local development snappy. Even potential scaling issues—repository size and binary assets—are mitigated through shallow clones and external storage for large files.

The broader implication is clear: as AI tools become integral to software creation, the value of a single source of truth skyrockets. Companies that consolidate code, content, and configuration can let models like Claude reason across product layers, auto‑update docs, and ensure marketing claims match implementation. While monorepos demand disciplined governance and may not suit every organization, Kasava’s experience demonstrates a viable blueprint for AI‑native development that balances speed, reliability, and maintainability.