╔══════════════════════ SYSTEM // ONLINE ══════════════════════╗
║ ID : KoNit ║
║ MODE : BUILD · BREAK · SECURE · DECENTRALIZE ║
║ FOCUS : AI AGENTS · SECURITY · WEB3 · AI × FINANCE ║
║ SIGNAL : MAJOR CONTRIBUTOR · HERMES AGENT ║
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I build and research systems at the intersection of AI agents, agent security, decentralized infrastructure, and financial protocols. My background is in Web3 and blockchain systems; my current work is increasingly focused on reliable agent infrastructure, adversarial evaluation, multi-agent systems, and AI × finance / Web3.
Major contributor to NousResearch/hermes-agent, contributing across agent infrastructure, Desktop, reliability, tooling, and cross-platform behavior.
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🚀 Hermes Agent v0.21.4 |
🚀 Hermes Agent v0.22.3 |
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🚀 Hermes Agent v0.21.6 |
🚀 Hermes Agent v0.21.5 |
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🚀 Hermes Agent v0.21.3 |
🚀 Hermes Agent v0.21.2 |
My earlier work and research centered on blockchain and decentralized systems. I continue to work across Web3 infrastructure, DeFi, smart contracts, and financial mechanisms, while moving deeper into AI-agent systems and agent security.
I am particularly interested in problems where these areas overlap: autonomous agents interacting with financial systems, secure tool-using agents, decentralized execution, and mechanism-aware AI systems.
Systems: LLM Agents · Multi-Agent Systems · Agent Security · EVM / DeFi · Smart Contracts · Distributed Systems · Wallet Infrastructure
| Area | Current direction | |
|---|---|---|
| 🤖 | AI Agents & Agent Infrastructure | Orchestration, multi-agent coordination, tool use, runtime reliability, and local/cloud agent systems |
| 🛡️ | Agent Security | Red teaming, adversarial evaluation, robustness, and safe credential / execution boundaries |
| ⛓️ | Web3 Systems | Wallets, smart contracts, DeFi/AMM systems, cross-chain infrastructure, and onchain financial applications |
| ◈ | Research | Mechanism design, game theory, and AI × decentralized / financial systems |
Automatic multi-agent red-teaming framework for evaluating AI-agent robustness.
Attacker, target, and evaluator agents operate in an iterative adversarial feedback loop, with configurable LLM backends and distributed execution through the Naptha SDK.
ATTACKER ──► TARGET ──► EVALUATOR
▲ │
└────── feedback loop ◄───┘
Open to open-source engineering, AI / agent-security research, and technically serious work at the intersection of AI, Web3, and financial systems.
BUILD // TEST // BREAK // SECURE // SHIP




