We asked @_seanli of @MagicNewton about the concept of a trusted agent and untrusted agent.
"I like to describe trusted agents through analogies"
"It's like a self-driving vehicle where you set a destination and parameters like speed, and the car follows through to get you from point A to point B."
"In the middle, you want a secure computer that does the task based on your parameters, and no one should be able to tamper with that"
"Everything is recorded in the verifiable part, every turn and action is recorded like in a flight black box with a notarized log where you can check if they did the correct actions afterwards." 🦣
"That's the ZK proof part, and underneath we use @SuccinctLabs and @RiscZero for the infrastructure."
NEW EP: Sean Li on Application Abstraction, Verifiable Agents, and AI’s Trust Problem
A new UX for onchain interactions is being built before our eyes.
In today's episode of Mammoth May 🦣, @ayyyeandy sits down with @_seanli of @MagicNewton to explore:
> Why 80% of DApp Interfaces Will Disappear
> How To Build AI Agents That Can't Go Rogue
> Cryptographic Proofs vs. Traditional Trust Models
> From Embedded Wallets to Verifiable Agents
> The Future of Natural Language Crypto UX
> Why Web3 Infra Ousts Web2 for AI
Full episode links below.
Timestamps:
00:00 Intro
01:13 Mantle Ad
01:54 Sean’s Music to Tech Journey
07:16 Embedded Wallets & Starting Magic
14:54 AI x Crypto Landscape
19:11 Trusting AI Agents
24:46 Agent to Agent Interactions
28:49 Omni Ad
29:17 UX Abstraction Evolution
32:51 Newton’s Value Accrual Model
37:04 Trusting Tools With Your Capital
40:25 Enforcing Agent Guardrails
44:20 AI Ethics
48:32 Newton’s Upcoming Roadmap
53:32 Privacy in AI
58:19 Future of Newton
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