how Zeru’s reputation model works — a deep dive 🧵. powered by AI. grounded in math. built for crypto. let’s explore the ML pipeline behind zScore, now live as an AVS on @eigenlayer 👇

qiro team is goated, scoring a series of W on the trot. very glad to be working with them closely on credit policies using our neural network.

ZM! Chat soon. 🎤.

Reputation is becoming infrastructure. Over 3M wallets now have a verifiable reputation score. $2.5B in economic security backs the system. As AI-generated activity rises and pseudonymity becomes the norm, trust signals are no longer optional — they’re essential for:. –

In an era where AI-generated identities and automated behavior are flooding digital systems, reputation can no longer rely on static credentials or self-claimed profiles. Zeru is building the universal reputation layer for the onchain world, one that aligns with how AI agents,

You don’t need to prove who you are. You need to prove what you do. That’s what zScore enables — a trust signal, built from your real onchain behavior. While bots fake identities, and airdrop farms multiply, zScore cuts through the noise. Here’s how:. – It analyzes what your

RT @onchainzu: off from ethcc . sending love to all the beautiful souls i met this week 🫶🏻

RT @Ashutosh_Sahoo: this is one very crucial factor for choosing to build "reputation-as-a-service" as an AVS on @eigenlayer . at @zerufina….

RT @onchainzu: bnjr! . last day in Cannes 🌞. floating through events, drinking too much coffee, and talking anyone’s ear off about reputati….

RT @Ashutosh_Sahoo: everything is screaming for a need of decentralized employment verification . one of the many use cases built by our re….

See you in 10 minutes!.

Why does Proof of Personhood matters now more than ever?. Because trust is breaking down across the onchain economy and the consequences are already here:.– Airdrops are routinely farmed by fake wallets. – NFT mints are botted, real collectors pushed aside. – Lending protocols

For those building at the intersection of AI and crypto — this episode is essential. Saushank lays out what an agent-powered financial system could look like. And how close we already are. Watch the Full podcast here:

“You’ll be able to say: I want to earn $2k in 30 days. Your agent will assess your risk, read your onchain profile, and build the optimal strategy.”. This is not hypothetical. It’s directionally where crypto UX is going.

On user experience:.• Wallet flows are broken. • Telegram bots introduce friction and security risks. • The future is mobile-native agent interfaces — ephemeral, goal-based, and conversational.

The shift is real:.“Every trade has memory, context, and evolving logic.”. We’re leaving behind static dashboards and moving into composable, self-improving agent systems. This is the start of the AI-native DeFi stack.

Key highlight: GigaBrain.A crypto-native agent terminal aggregating data, scraping social signals, and deploying trades — all coordinated by agents. Think of it as an execution layer for DeFi intelligence, without human bottlenecks.

In the episode, he covers:.• Agent-first trading architecture.• Reinforcement learning for live market signals.• Validation loops to reduce noise and overfitting.• On-chain UX principles: escrow, refunds, risk filters.

His core thesis: .AI and blockchain will find product-market fit together. Why?. Because agents require programmable money, and crypto apps require intelligent automation. Smart contracts are how we deploy agents at scale.

Saushank has built and advised across both AI and DeFi. From PitchPilot to modular crypto terminals, his focus is now on enabling intelligent agent systems that directly interface with crypto protocols.

“We're not building backtest tools. We’re replicating how hedge funds function — through agents.”. Trader agents, risk managers, validators — each one modular, learning, and composable. That’s the foundation of autonomous crypto trading.