A Production-Ready Monorepo for AI-Native Full-Stack Development
Source: Dev.to
Overview
Andrej Karpathy recently wrote: “If you properly connect the things that emerged over the past year, they could easily become 10× more powerful.”
Ashok, Tesla’s CTO, also said: “Everyone is a CEO now.”
Both statements are true. Spinning up a service with a few clicks has become easy, but building software that humans and AI can review together—and that remains maintainable over time—is still hard. To truly leverage these tools, you need a solid foundation first.
I’m open‑sourcing the foundation I built while developing AI‑driven services as an AI SWE. Compared to starting from scratch, it should save you roughly two weeks.
Tech Stack
- Web: Next.js 16, React 19, TailwindCSS v4
- API: FastAPI, async SQLAlchemy, PostgreSQL
- Mobile: Flutter 3.38, Riverpod
- Infra: Terraform, GCP (Cloud Run, Cloud SQL)
- CI/CD: GitHub Actions + Workload Identity Federation (keyless)
- Observability: OpenTelemetry
Why This Matters
The quality of AI‑generated code varies widely by model. A well‑designed template provides clear patterns for AI to follow, while strict linting and CI act as guardrails.
Key Features
- mise‑based monorepo: unified toolchains for Node, Python, and Flutter
- Single‑source i18n: shared across web and mobile
- Automatic API client generation: Orval (web),
swagger_parser(mobile) - Rust‑based toolchain: Biome, uv, Turbopack
- Production patterns and troubleshooting that rarely make it into docs, encoded directly in the codebase
If you see room for improvement, feel free to open an issue.
GitHub: