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Rullst Blueprints Roadmap πŸ—ΊοΈ

β€œA practical collection of reviewed Rullst application starters”

This document maps the expansion plan for the Rullst Starter Blueprints ecosystem. The goal is to provide reviewable application starting points with explicit production checklists and capability boundaries.


πŸš€ Blueprints Design Philosophy

Every blueprint added to the CLI must meet three fundamental principles:

  1. Clear first experience: Responsive, accessible interfaces whose browser assets and CSP are explicit.
  2. Native Rust/Rullst Features: Demonstrate measured resource use, typed concurrency and explicit server/realtime boundaries.
  3. Production-minded defaults: Generate .env.example, database configuration, and a conservative .gitignore; deployment readiness remains an application-level review.

πŸ—ΊοΈ Proposed blueprints (ordered from easiest to hardest)

Except for ERP, these rows describe design targets and are not selectable CLI blueprints. A proposal becomes implemented only when its generated project and negative boundaries pass the release gates.

IDBlueprint NameTechnical Focus in RullstCommercial Differentiator
4πŸ’Ό ERP Pocket (Inventory)Embedded SQLite + rullst::nexus (Auto-CMS) + Single BinarySmall/medium-business inventory starter; crash recovery and backup remain application work.
5πŸ“‹ Member/Club ManagementValidation + Nexus + reviewed receipt adapterProposed member and billing domain starter.
7πŸ€– AI Agent & RAG Boilerplaterullst-ai + opt-in document parsing/embedding adaptersProposed RAG starter; uploaded content remains untrusted.
8πŸͺ™ AI Credit-Based SaaSSSE + transactional usage ledger + payment adapterProposed AI SaaS starter with server-owned credit reservation.
9πŸ₯ Scheduling & ClinicsHTMX calendar + scheduler + database conflict policyProposed scheduling starter with database-specific contention tests.
10πŸšͺ Biometric Access ControlWebSocket foundation + real-time concierge panelPlanned access-control starter; device trust and latency need deployment-specific validation.
11πŸ“ˆ Affiliate CheckoutSSR + commission-split domain model + landing pagePlanned sales starter; performance and Lighthouse scores must be measured per application.
12🏒 B2B Multi-Tenant PlatformTenant context + RBAC + rullst-mailPlanned B2B starter; isolation must be proven across every storage and messaging boundary.
13πŸ’¬ Discord-Like Realtime ChatServer-driven UI + authenticated WebSocketsProposed chat starter; distributed presence and load evidence are required.
14πŸ›΅ Delivery / Food AppBackground queue + explicit order state machineProposed delivery starter with idempotent jobs and notification adapters.

πŸ” Highlighted Architectural Details

πŸͺ™ 8. AI Credit-Based SaaS (The Token-Burner)

  • Architecture goal: a server-owned chat flow with bounded SSE streaming, cancellation and provider error handling.
  • Data Security goal: use a database transaction and provider-specific lock semantics to reserve credit before an LLM request. This workflow is not yet a generated, cross-database guarantee.
  • Monetization goal: integrate a reviewed usage ledger with a supported payment adapter; billing portals remain provider/application work.

🏒 12. B2B Multi-Tenant Platform (The Corporate Boilerplate)

  • Isolation goal: derive a validated TenantContext at the HTTP boundary and carry it explicitly through database, cache, queue and realtime operations. Rullst does not inject a tenant predicate into every arbitrary SQL statement.
  • Permissions goal: typed roles (Admin, Member, Billing) enforced in middleware and again at sensitive service boundaries.
  • Invitations goal: hashed, single-use, expiring invitation tokens delivered through a configured mail adapter.

πŸ’¬ 13. Discord-Like Realtime Chat

  • Client goal: use server-rendered messages and an explicit WebSocket client without making bundle size a proxy for correctness.
  • Scale gate: publish connection count, message mix, backpressure behavior, CPU/RSS, hardware and distributed topology before attaching capacity numbers.

πŸ₯ 9. Scheduling & Clinics (The Scheduler)

  • Conflict-prevention goal: enforce a database constraint plus a transaction strategy tested on every declared backend; isolation level alone is not a universal double-booking proof.
  • Reminder goal: use bounded, idempotent scheduler jobs and a configured mail adapter. Multi-instance leadership and durable retry must be explicit.

πŸ€– 7. AI Agent & RAG Boilerplate (AI-Native)

  • Structure goal: quarantine and scan bounded uploads, parse supported formats in an isolated adapter, generate embeddings and store an authorized index.
  • Provider goal: expose an explicit provider selection and capability check. Changing an environment variable does not make data policy, schema or model behavior interchangeable.