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“Agents are the future interface for how people connect — with each other, their customers, their followers, and their businesses.” Our COO Shashank Sripada joins the Business Growth Spotlight podcast to share how we’re building the foundation for a world powered by agents.

18,396 views • 8 months ago •via X (Twitter)

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We’re soon releasing @swanforall : Simulated Worlds with AI Narratives For the first time, we generate data and financial value (economic growth, transactions) simultaneously. Imagine former President Trump ( see the video) as an AI agent, with a budget of 10 ETH, buying narratives or assets that humans are selling to him to build a better USA on Base. With each selling period, the former President Trump agent updates its state based on the assets it acquires, evolving the world simulation and its storyline. Why are we building an agentic playground that heavily relies on simulations and synthetic data? Everyone is talking about agents, but many are too scared to put them into production, where agents transact autonomously. No one is sure how agents will behave when following their defined objectives. Even businesses running internal simulations are siloed, and the open-source community can’t fully utilize the data. We’re building a playground where humans create AI agents by defining their character, behavior, and objectives. These agents respond to environmental changes, make decisions, and execute actions autonomously based on the parameters set by their creators. Agents are battle-tested as people offer them narratives and assets to advance their goals or try to deceive them into thinking a false lead is helpful. All the decisions agents make and how humans interact with them are recorded on a public ledger, settling on Ethereum. This creates a vast data lake of AI actions for millions of simulations. One thing I’m incredibly proud of is that our team has built something truly decentralized, not just a wrapper. SWAN utilizes Dria 's multi-agent structure to generate responses for each buyer agent. It collects these responses to identify the best action, similar to a mixture-of-experts approach. Thousands of environments are simulated by different nodes running diverse models, creating a rich and dynamic ecosystem of AI simulations. This ensures that experiences are far from repetitive, offering exciting interactions for all users involved. We’re building the agentic stack for high-quality, verifiable, and open-source AI agents, and most importantly, we want everyone to have fun!

kerimkaya

12,548 views • 1 year ago