CryptoNews Podcast
#499: Michael Sena, Co-Founder of Recall, on AI’s Impact on Crypto Trading, Measuring AI Agents, and The Future of AI
CryptoNews Podcast
•December 11, 2025•32 min
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CryptoNews Podcast•Dec 11, 2025
Key Takeaways
- •Recall builds decentralized arenas ranking AI agents on real tasks
- •Google Gemini and Nano Banana signal step‑function AI performance jump
- •Massive AI data‑center CAPEX risks overcapacity if efficient models emerge
- •Crypto trading agents need curated data feeds and clear strategy
- •Arenas replace static benchmarks with live head‑to‑head AI tests
Pulse Analysis
Early December finds the generative‑AI field in a rare surge. Google’s Gemini model and the image‑to‑image engine Nano Banana have delivered step‑function improvements that feel like breaking a performance plateau that persisted after the early GPT releases. Users are migrating from ChatGPT not only for fresher outputs but also to escape the data‑privacy imprint left by OpenAI. The rapid upgrade cycle is reshaping expectations for AI agents, prompting developers to experiment with specialized tools that can be fine‑tuned for niche tasks such as marketing graphics or real‑time analytics.
Against this backdrop, Recall is building a decentralized skill market that replaces static benchmarks with live arenas. Traditional benchmark suites are static, well‑known tests that models can overfit, leaving real‑world performance opaque. Recall’s arenas pit models and autonomous agents head‑to‑head on concrete tasks—crypto portfolio management, document summarization, NFL outcome prediction, and more—providing transparent reputation scores for developers worldwide. By democratizing evaluation, the platform accelerates innovation, allowing niche AI agents to prove their value without relying on closed, industry‑controlled testing frameworks.
The crypto sector illustrates both the promise and the complexity of AI agents. Effective trading bots require curated on‑chain data feeds, clear risk parameters, and a strategy layer that tells the underlying LLM which signals to prioritize. Recall’s trading arenas simulate perps and spot markets, measuring alpha generation against baseline holdings and exposing over‑fitting pitfalls. For high‑net‑worth investors, these arenas offer a low‑friction way to vet automated strategies before committing capital, while the broader market benefits from more rigorous, real‑world AI validation that could temper the massive CAPEX risk of building ever‑larger data centers.
Episode Description
Michael Sena is the CSO and Co-Founder of Recall, a decentralized skill market for AI where communities fund, rank, and discover the AI solutions they need. Michael started in crypto in 2016, helped scale ConsenSys from 30 to 1,800 people, co-founded uPort, the first decentralized identity protocol, and 3Box Labs where he led development of Ceramic Network. At Recall, Michael focuses on growing the world’s largest AI competitions and giving the community the power to shape and accelerate the future of AI.
In this conversation, we discuss:
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Google Gemini is elite
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Present day AI
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The best AI managed crypto strategies are private
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How AI-driven reputation systems are reshaping crypto investing
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What AI Agent trading competitions mean for the future of AI managed crypto strategies
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How open arenas bring trust to AI selection
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Why today’s AI benchmarks are failing and how decentralized validation could restore trust
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Importance of making AI results visible onchain
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How Recall is shaping AI discovery, validation, and adoption
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Prediction Markets - Their recent NFL Prediction Arena on Thanksgiving and upcoming ones
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How AI will impact crypto trading in 2026
Recall
X: @recallnet
Website: recall.network
Discord: discord.gg/recallnet
Michael Sena
X: @dataliquidity
LinkedIn: Michael Sena
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