Participants

This section describes the roles played by various participants in FOMO.

1. RMA Issuers — the Operator / Builder

The Real Model Asset Issuer is the initiator and operator of a specific model deployment. They launch the model through FOMO, define its deployment configuration, and are responsible for bringing a real, usable AI model into production. As the operator, the RMA Issuer earns a share of ongoing inference revenue, aligning long-term incentives with model quality and adoption.

Who they are

• The individual or team that launches a model deployment via FOMO

• Can be an AI builder, a startup, or a company using AI internally

What they do

• Define the model + deployment configuration

• Initiate a Real Model Asset Offering (RMO)

• Operate the “franchise” for that model

What they get

• A share of real inference revenue

• Bonus $FLOCK emissions tied to actual usage

2. Supporters — the Bootstrap Capital

Supporters participate during the model’s launch phase, providing early capital to bootstrap deployment, liquidity, and incentives. They take on initial risk in exchange for early exposure to the model’s economic upside. Their role enables models to reach production quickly while aligning early belief with long-term usage-driven value.

Who they are

• Community members who participate in RMOs

• Early believers in a model’s utility

What they do

• Provide upfront capital in exchange for MT

• Help fund hosting, liquidity, and incentives

What they get

• Early access to a model-backed asset before deployment

• Exposure to usage-driven upside through future buybacks and supply contraction

3. Users — the Power Users

Users are the consumers of AI inference who actively rely on the model in real applications. By staking the model token, they unlock discounted inference costs and receive protocol rewards, while their usage directly drives token buybacks. In FOMO, users are not just customers — they are economically aligned stakeholders in the models they depend on.

Who they are

• Developers, companies, or agents that actively use a model’s API

• Often the same people who supported the model launch

What they do

• Buy Model Tokens (MT) during the RMO or on the market

• Stake MT to unlock discounted inference

• Consume inference in real applications

What they get

• Lower inference costs

• $FLOCK emissions routed to actively used models

• Exposure to MT scarcity via usage-driven buybacks

4. The Protocol (FLock / FOMO) — the Franchisor

The protocol provides the infrastructure, rules, and economic coordination layer for all model deployments. It enforces deterministic revenue routing, emission logic, and token mechanics based on real usage, not speculation. Like a franchisor, the protocol standardizes operations and ensures that value flows fairly between operators, users, and supporters.

Who it is

• The FLock ecosystem operating FOMO and the API platform

What it does

• Hosts and serves models as production APIs

• Enforces revenue splits, emissions logic, and buyback rules

• Routes network-level value into $FLOCK

What it gets

• A portion of inference revenue for sustainability

• Deflationary pressure on $FLOCK via protocol-level buybacks

• Network effects as more models and users join

The Mental Model

FOMO participants form a closed economic loop:

• Builders → launch real models

• Users → consume inference

• Usage → generates revenue

• Revenue → buybacks + rewards contributors

• No usage → no rewards

At its core, FOMO is designed as a self-contained economic loop where value only flows when real work is done. Models must exist before tokens exist, and tokens only gain value through actual inference usage.