I sat down with Michael Sena to explore how we’ll start trusting AI agents with real‑world responsibilities — from crypto trading to enterprise workflows. We talk about his Web3 roots, the genesis of the concept behind skill markets, and how his project is creating transparency and performance benchmarks in a rapidly evolving AI ecosystem. If you’ve ever wondered how to evaluate an agent, give one control of money, or build one yourself — this episode gives you a front‑row seat.

Key Learnings

• [00:01:00 ] Michael’s journey: from discovering Bitcoin in 2011 to diving into Web3 identity protocols and ultimately shifting to AI skill‑markets.

• [00:04:00 ] What the company does: a “decentralised skill market” where AI agents are tested, ranked, and evaluated on real‑world skills.

• [00:06:00 ] The central problem: how do you trust an AI you hand your crypto portfolio to, or a business process you delegate?

• [00:10:00 ] Why benchmarks often fall short: static tests, academic settings, and hype don’t always align with real‑world performance.

• [00:12:00 ] The role of agents vs. foundation models: many new AIs will specialise, and evaluation will need to keep up.

• [00:17:00 ] Why blockchain? For coordination, capital‑signalling, transparency and enabling open skill‑markets with economic incentives.

• [00:24:00 ] Most traction today: crypto‑trading agents, but enterprise and internal tooling evaluations are growing fast.

• [00:35:00 ] Roadmap highlights: token launch, permissionless market creation, verifiable AI execution via partnerships, and more.

• [00:39:00 ] How you can get involved: as a builder, curator, or user — open to anyone with interest and energy.
  

Connect

https://x.com/recallnet

https://recall.network/

https://discord.com/invite/recallnet

https://www.linkedin.com/company/recalllabs/ 

https://www.linkedin.com/in/msena/

https://x.com/dataliquidity 

Disclaimer

Nothing mentioned in this podcast is investment advice and please do your own research. 

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