AI product system
An AI-native product, analytics, and systems orchestration platform for designing architecture, generating specs, coordinating realtime collaboration, and running background AI workflows.
Collaborative AI Architecture Workspace
Ghost AI is presented as a modern build-in-public product system: realtime collaboration, AI-assisted systems design, interactive canvas orchestration, background workflow execution, and production deployment through Vercel.
Current Ghost AI workspace: shared project rooms, architecture canvas, component palette, saved state, Liveblocks collaboration, and an AI Architect panel for system design prompts.
Tech stack
The project reads well for technical recruiters because it shows modern product engineering, AI integration, realtime state, durable data, and deployment operations.
AI Architect workspace
Ghost AI is designed to help teams describe a system, generate or refine architecture, review dependencies, and keep implementation context visible across product and engineering.
Teams can map services, databases, APIs, workflows, and dependencies in one visual workspace instead of scattering system decisions across chats and docs.
The AI Architect panel helps turn product intent into architecture options, suggested components, implementation notes, and reviewable system flows.
Engineers get a clearer view of ownership, integration points, data movement, deployment assumptions, and risks before implementation begins.
Product and business stakeholders can see how requirements become technical structure, making handoffs, scope discussions, and tradeoff reviews easier.
Architecture and workflow
Ghost AI connects architecture mapping, realtime collaboration, background AI workflows, database-backed state, and production delivery.
React Flow workspace for mapping systems, data movement, AI services, product flows, and orchestration logic.
Liveblocks-powered presence, shared activity, and collaborative feeds keep system design work visible to the team.
Trigger.dev supports long-running background AI workflows for product/spec generation and multi-step system tasks.
Prisma and PostgreSQL give the workspace durable project context, schema-backed state, and production-ready data foundations.
System evidence
This keeps the portfolio premium and technical without turning the page into a code dump.
Ghost AI system notes
1Ghost AI is positioned as an AI-native product, analytics, and systems orchestration platform.23- Frontend: Next.js, TypeScript, and a React Flow architecture canvas4- Collaboration: Liveblocks presence, feeds, and realtime shared workspace patterns5- AI layer: OpenRouter LLM integration for assisted systems design and product/spec generation6- Workflow layer: Trigger.dev background jobs for long-running AI orchestration7- Data layer: Prisma with PostgreSQL for persisted workspace and system context8- Delivery layer: Vercel deployment, environment management, and production debuggingChallenges solved
Ghost AI adds a future-facing product build to the portfolio while staying grounded in architecture, collaboration, and production engineering.
Frames AI-assisted systems design as a structured workspace where product intent, data flows, and technical components stay connected.
Uses shared presence and feeds so product, analytics, and engineering contributors can work from the same operating surface.
Moves AI generation and orchestration into background workflows instead of blocking the core product experience.
Shows environment management, Vercel deployment, dependency configuration, and production debugging as part of the product story.