Why AI framework standards should move toward "chainification"?
TechFlow Selected TechFlow Selected
Why AI framework standards should move toward "chainification"?
For AI agents to achieve more reliable autonomous decision-making and interoperable collaboration, they will inevitably trend toward "chaining."
Navigating Web3 tides with focused insightsWritten by: Haotian
Many people still don't understand why I keep advocating that AI framework standard projects should move toward "chainification"? Perhaps during the previous bull and bear cycles, chain infrastructure carried too much expectation. Now that we've finally entered the era of AI Agent applications, many feel apprehensive about blockchains. Yet, for AI Agents to achieve reliable autonomous decision-making and seamless collaboration, they will inevitably trend toward "chainification."
Currently popular frameworks like ELIZA, ARC, and Swarms are largely still in the "concept phase." At this stage, they cannot be falsified and thus reset to zero, nor can they be proven and explode in value. They remain in an early infancy where valuations are unmeasurable. This is the first hurdle for assets launched on GitHub—only when these conceptual frameworks demonstrate feasible real-world implementation can they gain consistent market recognition.
Looking closely at frameworks such as ELIZA, ARC, and Swarms—whether focused on maximizing single-agent performance or enabling multi-agent interaction—at their core, they all require establishing traceable logic and rules for AGI model API calls.
After all, data resides off-chain, reasoning processes are hard to verify, execution lacks transparency, and outcomes are uncertain.
In the short term, TEE (Trusted Execution Environment) offers a low-cost, highly feasible off-chain trustless solution that can accelerate the integration of AGI capabilities into AI Agent autonomous decision-making. But in the long run, we’ll also need an "on-chain consensus" mechanism to enhance reliability.
For example, ELIZA aims to build an AI Agent-based private key custody solution using @PhalaNetwork’s TEE secure remote attestation capability, ensuring that the execution code within the AI-Pool isn’t tampered with before signing via private keys. However, this is only the first small step of applying TEE to AI Agents.
If we could place complex predefined execution logic into Agent Contracts and have validators on the Phala chain jointly participate in verification, then a full chain-secured consensus system governing TEE execution details would be established. At that point, AI Agents will drive demand for TEE, and TEE will fuel blockchain empowerment—a positive flywheel effect begins to spin.
The logic makes perfect sense: TEE ensures private keys remain invisible, but how exactly are those keys invoked? Under what predefined rules? How are risk controls and emergency responses triggered? In the short term, open-source code repositories can provide transparency. But longer term, won’t we ultimately rely on a decentralized validation consensus to continuously verify and confirm these actions in real time?
Therefore, "chainification" not only accelerates AI Agent frameworks toward practical, real-world deployment but also unlocks entirely new incremental opportunities for Crypto infrastructure.
The direction is now clear. For most people, identifying and going bullish on the earliest "chainified" AI Agent frameworks—and the established chains that first support AI Agents—is where the alpha lies in this emerging AI Agent trend.
Join TechFlow official community to stay tuned
Telegram:https://t.me/TechFlowDaily
X (Twitter):https://x.com/TechFlowPost
X (Twitter) EN:https://x.com/BlockFlow_News
Haotian | CryptoInsight
