Wondering how ORO points work? Every time you share high-signal data, whether it’s through a connected account or a completed quest → you earn points. 🔸 Core activities = linking accounts completing missions 🔸 Amplifiers = consistency, engagement, and community participation These points reflect the value your data creates, and will determine your future ORO token rewards. Contribute with purpose. Get rewarded accordingly 🫡

BlackRock’s Aladdin runs on multi-agent AI, autonomous systems that parse market sentiment, adjust risk, and coordinate trades. Not just automation. Intelligence at scale. This is how institutional finance is running ops in 2025 🧵👇

Architectures are converging. Compute is commoditizing. The next moat for frontier AI isn’t scale — it’s provenance: knowing where every bit of training data came from, with guarantees. Regulators will demand it. Users will expect it. Labs will compete on it. ORO is the programmable provenance layer for AI data, purpose-built for the next phase.

The shift is already underway: LLMs are being repurposed as strategic automation tools across sectors. It’s parsing SEC filings, modeling private valuations, and drafting investment memos inside firms like BlackRock, KKR, and even the U.S. Air Force. These aren’t chatbots. They’re persistent AI agents embedded into enterprise workflows. They work across documents, learn from feedback, and improve with every task like hyper-efficient interns that never sleep. But here’s the catch: These agents are only as smart as the data they’re built on. That’s why high-signal, structured, permissioned data is becoming the real competitive edge. ORO helps supply it, with quests that collect real user reasoning, decisions, and thought traces. Not scraped content. Not synthetic noise. The future of work depends on systems that can think with context and not just execute tasks, but understand goals, adapt to feedback, and improve over time. And context starts with people.

The old consent model doesn’t work for AI. Click a box, agree to fine print… that might’ve worked for static data. But not for recursive training where your data keeps being used, again and again. You can’t revoke it. You can’t trace it. You can’t prove it was ever yours. Consent needs to be recorded, enforced, and verifiable - not buried in a Terms of Service. Real consent means traceability, not trust.

In most AI systems, user contributions vanish into the system with no trace. No receipts. No recognition. No link between input and outcome. ORO is changing that with onchain attribution. 🔸 Your actions are logged 🔸 Your contributions are credited 🔸 Your rewards are verifiable Every action is recorded as a cryptographic proof onchain - not the data itself, but a secure record of your contribution that enables fair rewards and recognition 🤝