Chainfeeds Summary:
As early as October, Virtuals proposed the concept of tokenizing AI agents, but at the time most people were not paying attention. To obtain similar excess returns, one must act early, before others discover it. Fundamentally, the key to agent success lies in its uniqueness and practicality. This article reviews several popular narratives and use cases.
Source:
https://x.com/Defi0xJeff/status/1873272066834841699
Author:
0xJeff
Perspectives:
0xJeff: 1. Tracing and Delivering Alpha: There is a huge demand for agents that provide signals and insights for trading. For example: aixbt is the gold standard for alpha-focused agents. 2. Investment DAOs: Hedge fund-style DAOs, run by human or AI agents, investing their capital. For example: the daos.world ecosystem on Base, VaderAI, WAI Combinator, sekoia_virtuals and aixcb on Virtuals, the daos.fun ecosystem on Solana. 3. On-chain Trading: On-chain trading is a narrative that resonates deeply with the community, as we love to see someone's effort in turning $1,000 into $1 million. It's not just about the money, but the excitement of watching someone go through the grind and succeed. Iterating trading agents will leverage this energy, focusing on portfolio growth and showcasing their frameworks and strategies in real-time. For example: Gekko AI: self-improving trading agent on Virtuals, leveraging Axal's infrastructure to deliver results; Big Tony: built on Cod3x, focused on autonomous execution; Project Plutus: combining real-time analysis with automated DCA execution. I expect on-chain trading agents to be a focus in Q1/Q2 2025. 4. Utility-Focused Development Tools: As the ecosystem evolves, the demand for development tools becomes crucial. Examples: SOLENG: monitoring pull requests, conducting preliminary audits, and serving as AI judges for hackathons; H4CK Terminal: white hat agent for bounties and vulnerability checks; CertaiK: conducting agent security audits. 5. Privacy and Confidentiality (TEE): Pioneered by Marvin Tong and Phala Network on Solana, Trusted Execution Environments (TEE) support fully autonomous agents. For example: "Unruggable ICO" agent aiPool; SPORE: TEE agent with inheritable genetic traits; Neural network experiments like DeepWorm.
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