Early Adopters
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Hello friends! I wanted to spread the word that Stacktora.com is in full-swing with a few early adopters and we have recently onboarded our first paying customer! For myself, the founder and a builder, I am ecstatic that someone out there said, with money, that Stacktora is a tool that builders will use.
I invite you to come check us out. We made the platform to be used for free — but features like Push-to-GitHub and adding team members to workspaces is available on a paid Pro plan.
Visit us at Stacktora.com
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Stack Definition Engine
stacktora.json widens from “recipe for the initial generate” into the single source of truth for the whole project over its life: runtime, datastores, CI, references to where real secrets live (never the secrets themselves), deployment targets, and team coding standards. Edit the recipe, regenerate everything, forever — and, per Part II, see the diff before it touches anything already running.
2. AI Context Layer
AI coding agents — Claude Code, Codex, and whatever comes next — read stacktora.json directly instead of inferring a project's setup by scanning files and guessing. Fewer wrong assumptions, cheaper and more accurate prompts, and it works for any agent, not just tooling Stacktora builds itself. As Part I lays out, this is no longer a bet on where the industry might go — it's the exact ground Vercel and Supabase are actively fighting over this quarter.
3. Recipe Marketplace
Installable, opinionated starting recipes — an official Stripe SaaS starter, a healthcare-compliant stack, a fintech baseline — shared or sold by companies, consultancies, and the community. This is the same instinct behind the Terraform Registry (and OpenTofu's own registry, now 3,900+ providers and 23,600+ modules) or Vercel's integrations marketplace: real network effects come from other people building on top of your format, not just from what you build yourself.
4. Enterprise standardization
A company.stacktora.json that enforces an organization's standards across every developer, every repo, every new hire — and every AI agent touching the codebase. Internal platform teams already build this by hand, badly, at every company that reaches a certain size. Stacktora could ship it as a product instead of leaving every company to reinvent it.
5. Becoming a standard
The long game. If CI systems, cloud platforms, and AI tools can all read the same recipe format, stacktora.json stops being “a file our tool happens to generate” and starts being infrastructure — the way Git, Docker, and Terraform's own HCL became infrastructure. This only becomes real once pillars one through four exist and enough actual projects use the format — and, per the Terraform/OpenTofu story above, only if the format itself stays credibly open while that happens.