Yunno, most agent frameworks work linearly:

1 agent → 1 task → 1 output.

Useful, but limited.
You can’t solve complex, multi-step problems when every agent works in isolation.

•••

-- 📌 What ROMA Adds

@SentientAGI's ROMA (Recursive Open Meta-Agent) solves this with recursion:

• Parent agent receives a query.

• ROMA breaks it down and routes sub-tasks to specialized sub-agents.

• Sub-agents iterate in a feedback loop, refining results.

• ROMA merges everything back into a coherent final output.

Think of it like project management for AI: a manager (parent agent) coordinating multiple specialists (sub-agents).

-- 📌 Why Recursion Is The Multiplier

Linear scaling is additive:

• 5 agents = 5 outputs.

Recursive scaling is multiplicative:

• 5 agents, each coordinating 5 more = 25 potential outputs.

• Add a feedback loop, and those outputs improve with each iteration.

This is nonlinear scaling. Each artifact compounds the system’s intelligence.

-- 📌 Competitive Landscape

Ritual: strong at on-chain inference. But no recursive orchestration.

1. Ritual: strong at on-chain inference → pipes for models.

2. Olas: focuses on agent ownership + incentives. Less about coordination.

3. Sentient (ROMA): recursive orchestration + emissions model → a market where the best-coordinated agents win.

This is the Kubernetes analogy: orchestration as the standard that all agents eventually build on.

-- 📌 Why Is ROMA Vital

For devs: Agents plugged into ROMA don’t just run tasks, they collaborate.

For users: Instead of one model’s answer, you get a synthesized consensus from multiple agents.

This is why ROMA is critical: it turns Sentient from “just another agent framework” into an orchestration economy where recursion = scale.