Tools: Stop Asking AI to Write Your Backend Code

What Terraform figured out ## What we're doing wrong today ## The better way: a DSL ## Why this matters ## Basalt: an early answer to this problem ## The bigger picture Every time you ask an AI to generate a backend, something slightly annoying happens: it writes 200 lines of TypeScript, picks its own folder structure, names things its own way, and somewhere in the middle it hallucinates an import that doesn't exist. You then spend 20 minutes fixing what should've taken 2. The thing is, this isn't really the AI's fault. You asked it to do too much. Think about how Terraform works. When you want to provision infrastructure, you don't ask an AI to write raw AWS API calls. That's complex, verbose, and easy to get wrong. Instead, you describe what you want: And Terraform handles the rest. The AI only needs to learn a small, constrained language. The hard work is handled by the system. The same idea applies to backend generation. We've just been too slow to notice. The current AI-for-backend workflow looks like this: User → "Build me a REST API for users with JWT and Supabase" → AI → 200 lines of code → you fix the mess The AI is generating the implementation. That's the wrong layer. It burns tokens on boilerplate. It makes architectural decisions it shouldn't. And every project ends up slightly different because the AI is improvising every single time. What if instead, the AI's only job was to write something like this? And your system generates the actual TypeScript, the router, the database client, the handlers — everything. The AI doesn't write code. The AI speaks your language, and your language generates code. Consistency. Every project generated from the same DSL looks the same. Same folder structure, same naming conventions, same patterns. No more "why did it do it this way this time?". Token efficiency. 10 lines of DSL vs 200 lines of TypeScript. The AI's job just got 20x cheaper. Predictability. The AI can't hallucinate an import that doesn't exist in your DSL. The language is closed and constrained. If the AI writes valid DSL, the output is valid code. Period. You own the generator. Want to switch from Express to Hono? Update the generator once. Every project benefits automatically. This is exactly what we're building with Basalt. Basalt is an open source CLI written in Go. You give it a .bs file describing your backend — tables, endpoints, auth — and it generates all the TypeScript you need, ready to run. That said — Basalt is just getting started. We're at v0.1.0 and the generator is still pretty basic: Express + TypeScript + Supabase, same template structure for every project. It doesn't do magic yet. But the foundation is there, it works, and the direction is clear. Upcoming versions will bring more frameworks, more databases, custom templates, and eventually a basalt ai command that takes plain English and generates the .bs for you. → github.com/DiegoDev2/Basalt We're at an interesting moment with AI and code generation. The first instinct was "just let the AI write everything." But the more mature approach is starting to emerge: design constrained languages that AI can speak fluently, then build systems that compile those languages into real artifacts. Terraform did this for infrastructure. Prisma did this for database schemas. OpenAPI did this for API contracts. Backend generation is next — and the pieces are already there. We just need to stop handing the AI a blank canvas and start giving it a grammar. What do you think? Is this a pattern you'd use? Drop a comment — would love to hear how others are thinking about this. Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? 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Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse CODE_BLOCK: resource "aws_s3_bucket" "my_bucket" { bucket = "my-app-storage" acl = "private" } Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: resource "aws_s3_bucket" "my_bucket" { bucket = "my-app-storage" acl = "private" } CODE_BLOCK: resource "aws_s3_bucket" "my_bucket" { bucket = "my-app-storage" acl = "private" } CODE_BLOCK: config { db: supabase auth: jwt } table "users" { id: uuid @primary email: string @unique name: string created_at: timestamp @default(now) } resource "users" { table: users endpoints { GET /users POST /users GET /users/:id PUT /users/:id DELETE /users/:id } } Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: config { db: supabase auth: jwt } table "users" { id: uuid @primary email: string @unique name: string created_at: timestamp @default(now) } resource "users" { table: users endpoints { GET /users POST /users GET /users/:id PUT /users/:id DELETE /users/:id } } CODE_BLOCK: config { db: supabase auth: jwt } table "users" { id: uuid @primary email: string @unique name: string created_at: timestamp @default(now) } resource "users" { table: users endpoints { GET /users POST /users GET /users/:id PUT /users/:id DELETE /users/:id } } CODE_BLOCK: Ask any AI to read the Basalt spec and write your main.bs → basalt generate → cd generated && npm install && npm run dev Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: Ask any AI to read the Basalt spec and write your main.bs → basalt generate → cd generated && npm install && npm run dev CODE_BLOCK: Ask any AI to read the Basalt spec and write your main.bs → basalt generate → cd generated && npm install && npm run dev