Multi-Agent

Hermes Agent v0.18: When a Self-Improving Agent Gets MoA

Nous Research’s open-source agent Hermes Agent shipped v0.18.0 on July 1, 2026. The release notes call it “The Judgment Release.” Reading this as a routine feature update misses the point. The official docs describe Hermes Agent as “the self-improving AI agent,” and the project is built around a loop that accumulates memory and skills the more it gets used. This post covers how that loop was refined in v0.18, and what role Mixture of Agents (MoA), now a first-class model choice in the same release, plays inside it.

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TradingAgents: Reading the Paper and Code Behind an LLM Trading Desk

Up front: this is not investment advice, and nothing here recommends buying or selling anything. It is a read of how you organize LLM agents into a single decision, looked at from the research and the code. Trading is just the domain the design happens to target.

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Mixture of Agents: How Layering Open-Source LLMs Beat GPT-4 Omni

Instead of scaling a single model up, you can stack multiple models in layers and have each one refine the previous layer’s output. Together AI’s research team formalized that approach in June 2024 as Mixture of Agents (MoA) in arXiv:2406.04692. Using only open-source models, their MoA configuration scored 65.1% on AlpacaEval 2.0, versus 57.5% for GPT-4 Omni.

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