One command scaffolds a secure app. AI tooling included.
A dotnet new template generates a working full-stack application with security wired, and the conventions ship in a form AI coding assistants can follow.
- ·One command scaffolds a working application with security, sessions, the API, and login already wired.
- ·Generated projects carry convention files written for AI coding assistants, so the code they produce follows the platform's rules instead of plausibly breaking them.
- ·Multi-tenancy, permissions, audit, history, background work, notifications, and reporting are platform services, so there is far less application code to secure and maintain for a decade.
The first two weeks of every project are the same two weeks.
New application, same setup: authentication, session handling, API scaffolding, a login page, layout, error handling. Two weeks to a month before the first business screen, repeated per project, with drift between projects as a bonus.
AI-assisted teams have a newer version of the problem: the assistant doesn't know your platform's rules, so it generates plausible code that violates them. The gains leak away in review.
The mechanisms, not the adjectives.
Full-stack scaffolding
dotnet new rbdforge-app generates a working starter: an ASP.NET Core API with GraphQL, the security engine wired, session middleware, and login endpoints, plus a web client with authentication, session tick, auto-logout, and a home page. Minutes to first run.
Projects start at the business problem instead of the plumbing.
Conventions that AI assistants can read
Generated projects include convention files written for AI coding assistants: the platform's rules, patterns, and gotchas in machine-readable form. The assistant working in your new project already knows how the platform wants things done.
AI-assisted developers stay on the rails instead of generating plausible violations.
Schema tooling over MCP
The MCP server gives AI clients live schema introspection, search, foreign-key graphs, and a structural audit that checks conventions like sequence-backed keys and indexed foreign keys. Governed platform artifacts are created through validated, confirmation-gated tools.
The assistant reads the real data model and follows the real conventions, instead of hallucinating either.
The platform absorbs the hard parts
Multi-tenancy, permissions, audit, history, background processing, notifications, and reporting are platform services. Application code registers tables and writes business logic.
Less custom code per app means less to secure, less to review, and less to maintain for a decade.
New app, first morning.
- 1
Run dotnet new rbdforge-app with your project name. A working API and web client come out.
- 2
Point it at your database and register your first tables with their permission keys.
- 3
The API is live and governed. The admin console can already manage what you registered.
- 4
Your AI assistant reads the included conventions and the MCP schema tools, and its output matches how the platform works.
- 5
By afternoon you're writing the business feature you actually came for.
The AI angle.
MIT's finding was that bought, workflow-integrated tools succeed at roughly twice the rate of internal builds. The scaffolding plus AI-readable conventions is how you get buy-speed with build-ownership: your developers, your code, on rails the platform already proved.
Keep going.
AI done right
MCP-native access, prompt-authored rules, and a security engine every AI agent inherits.
Go deeper →Data & instant API
Register a table and it is secured, audited, and queryable. No ORM, no per-table code.
Go deeper →Operations
The platform ships with its own ops console, real-time notifications, and full change history.
Go deeper →See it on your schema, not ours.
A fixed-price assessment gets this running over your actual data.