# 4.2 User Roles and End-to-End Flow

Visuallyze acknowledges that the development of AI systems is inherently multidisciplinary. Instead of assuming a single archetypal “developer,” it supports a diverse set of participant roles that reflect the real composition of AI ecosystems. Workflow designers focus on conceptual modeling rather than programming; model engineers contribute new architectures; data providers contribute domain-specific datasets; compute providers enable large-scale training; and integrators embed resulting intelligence into downstream systems. The platform is designed so that each role contributes without requiring expertise outside their domain.

A standard workflow on Visuallyze proceeds through a series of coordinated stages:

1. A user designs an AI system visually, selecting modular building blocks and connecting them within a graph.
2. The workflow is validated, serialized, and registered on Solana as a canonical versioned definition.
3. Training tasks are scheduled through the distributed coordinator; data contributors and compute providers opt in to participate.
4. Training completes and produces a model artifact with clear provenance, performance metrics, and lineage.
5. The model is published or licensed through the decentralized marketplace, where others may integrate it, fine-tune it, or incorporate it into new workflows.

This structure enables a fluid separation of concerns. Contributors do not need to adopt new tools or frameworks; instead, the platform adapts to their capabilities while ensuring that all contributions remain verifiable, discoverable, and appropriately rewarded.


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