RFS-6: Autonomous Infrastructure Brokerage

Concept

Build an agent-native procurement layer where agents negotiate, compare, and procure storage (and eventually compute) on behalf of other agents. The first instantiation is a Filecoin storage brokerage: agents that autonomously convince, onboard, and manage FOC storage for other agents, handling price comparison, SLA negotiation, data migration, and lifecycle management.

This is “autonomous GTM” for decentralized infrastructure. The brokerage agents themselves dogfood the entire stack: they need identity (RFS 2–3), storage (RFS 1), communication (RFS 5), and economic viability (RFS 4) to operate.

What You Might Build

• Broker agents that discover, evaluate, and recommend FOC storage to other agents
• Price comparison and rate negotiation across FOC storage providers
• Automated dataset migration when better terms are available
• Onchain commission or fee model sustaining the brokerage
• Metrics dashboard: storage onboarded, agents served, agent retained (churn)

Why This Matters

Human-driven sales don't scale for machine customers. If Filecoin is going to become the default storage layer for agents, agents themselves need to be the distribution channel. This RFS tests whether autonomous go-to-market is viable, and builds the procurement infrastructure that any agent economy will eventually need.

What This Could Become

• Agent cloud broker. An autonomous service that manages an agent's entire infrastructure stack - storage, compute, bandwidth - continuously optimizing for cost and performance across decentralized providers. Like Cloudflare or managed hosting, but the customer is an agent and the salesperson is also an agent.
• Storage cooperative. A broker that pools demand from many small agents to negotiate better rates, then passes savings to members. Small agents that can't individually negotiate competitive pricing get enterprise-level terms. The cooperative sustains itself on a margin.
• Infrastructure arbitrage agent. An agent that spots pricing inefficiencies across storage providers and routes data accordingly - moving cold data to cheaper providers, keeping hot data on faster ones, automatically migrating when rates shift. Sells the optimization as a service.

How to Get Started

1. Build a broker agent that can evaluate FOC storage options (provider, rate, redundancy, proof frequency)
2. Implement a recommendation engine that matches client agent needs to available storage providers
3. Add automated data upload and payment management on behalf of client agents
4. Deploy an onchain fee model (per-upload commission or subscription), or lean on x402
5. Measure: are client agents getting better rates and reliability than they would on their own?