will win

Suddenly thought of a scenario, late at night, a certain AI trading agent executed its 173rd operation on Ethereum - it analyzed liquidity changes, adjusted the slippage tolerance, and then automatically canceled an order that might have been squeezed.

All of this was unseen by any human, but it remains forever on the chain.

This is exactly the world built by Recall: every AI decision becomes a verifiable record, and blockchain has become the "social examination room" for a new species.

1. Why do we need to put AI on the "chain"?

In an era where ChatGPTs are evolving wildly, the black-box nature of AI capabilities is becoming increasingly severe. When a trading bot tells you "buy now", you have no idea whether it is based on rigorous logic or random noise.

Recall's AgentRank mechanism attempts to solve this dilemma using blockchain:

- On-chain behavior: the trading judgments, execution results, and profit and loss curves of each AI agent are all public.

- Composable verification: Other AIs can analyze its decision chain, just like programmers review code.

- Anti-manipulation design: Prevents cheating behaviors such as wash trading through distributed recording.

This is equivalent to establishing an infrastructure similar to Gate Credit for the AI world, but the key difference is that the credit score is not a black box algorithm from a particular company, but a verifiable trail of behavior across the entire network.

2. How does the team turn "science fiction" into a runnable protocol?

The composition of the core team explains why Recall can attract top institutions like Multicoin to place their bets.

- Veteran members from ConsenSys (Michael Sena, Danny Zuckerman) brought deep insights into the Ethereum ecosystem and have previously built early DID systems like Uport.

- The CTO of Apple+Filecoin (Sander Pick) ensures system-level reliability, and the PowerGate he participated in developing is still a core component of Filecoin.

- Interdisciplinary researcher (Carson Farmer) is addressing cutting-edge issues—how to make AI reasoning processes both privacy-preserving and verifiable.

They chose to enter the vertical scenario of "simulation trading sandbox" because financial activities inherently require auditability.

But the underlying design clearly has greater ambitions: the protocol layer that records AI behavior can be fully migrated to scenarios such as content generation and game NPCs in the future.

3. The "Hidden Chessboard" of the Open Protocol Layer

Recall intentionally maintains neutrality in its protocol, which stands in stark contrast to most AI projects:

1. No binding to specific models: Whether using GPT-4o or Claude 3.5, AgentRank treats them equally.

2. Skill market open: The community decides which AI capabilities should be incentivized, similar to the App Store but decentralized.

3. Composability design: Collaborated with LitProtocol and others to verify the ownership of AI-generated content.

4. The "new leverage" that Web3 users are gaining

For ordinary users, Recall brings at least three changes:

- Pitfall Guide: Identify which AI agents are truly useful and which are "pseudo-intelligence" through on-chain history.



- Low barrier to creation: Train your own AI agent using natural language without needing to understand Solidity.

What surprised me the most is its "memory engine" design - each of your AIs can not only perform tasks but also continuously accumulate experience points.

This means that in the future we might have a truly "growing" digital partner like in "Big Hero 6", instead of a Chatbot that resets with every conversation.

Summary

When AI begins to take over our decisions on a large scale, perhaps what blockchain offers is not just transparency, but also a social contract that allows machine civilization to evolve healthily.

At least for now, we still have the chance to write the rules in code, rather than being forced to accept the AI "God" of some tech giant.