Author: Merkle3s Capital; Source: X,@Merkle3sCapital
Introduction
Code is dead, logic is immortal.
This is not alarmist. By 2026, AI will be able to easily translate JavaScript into Python, rewrite Go into Rust, and eliminate all traces of code plagiarism. But the isomorphism of architecture cannot be eliminated by rewriting—just like translating a book from Chinese to English, the story structure remains the same.
... In April 2026, a war erupted in the AI open-source community over who invented the self-evolving agent first. On one side was Nous Research, a top global open-source AI lab with $70 million in funding and 85,000 stars on GitHub; on the other was a small Chinese team called EvoMap. This was the first real-world test of intellectual property judgment standards in the AI era: When code comparison fails, what else can we rely on to determine plagiarism? Chapter 1: The Complete Timeline of the Event From February 1st to April 14th, 74 days, the entire process of a small Chinese team's technological innovation and the development by a top global lab. Timeline Comparison: From the release of core concepts (February 1-16) to the launch of the Hermes Skills Ecosystem (March 12), a period of 24-39 days has elapsed. Nous Research claims its main repository was created in July 2025. However, verification shows that the allegedly "self-evolving" module was publicly created on March 9, 2026—36 days later than Evolver.
Chapter Two: What is the Hermes Agent?
How a top AI lab with $70M funding turned an "uncensored model" into a "7/24 self-evolving agent."
Nous Research: Who is building this agent?
Funding exceeds $70M (including a $50M Series A), 85,000 Stars on GitHub. Their most famous product is the Hermes LLM series—a large language model known for its "uncensored" nature; VentureBeat praised it as "outperforming ChatGPT without content restrictions." Now, what they're doing is transforming Hermes from a "model" into an "Agent." Core Positioning: 24/7 Autonomous Agent Unlike "programming assistants" like Claude Code and Cursor, Hermes Agent is positioned as a 24/7 autonomous agent running in the server background, similar to OpenClaw: Operation Mode: Server-resident, not IDE-bound. Evolution Capability: Learns through cycles, gets stronger with use. Memory: Persistent memory across sessions. left;">Platforms: Telegram/Discord/Slack/WhatsApp/Signal/WeChat/iMessage and 16 other messaging platforms
Cost: Only $5 VPS is needed to run
Three-tier memory architecture

The underlying support is an SQLite FTS5 extension, compared to OpenClaw's qmd Theoretically, this allows for faster memory retrieval. This design embodies the philosophy of "digital sovereignty"—all memory and execution logic remain in the user's local or private environment, complying with GDPR compliance narratives. 47 Built-in Tools with Anthropic Standards Web Search, Browser Automation, Terminal Execution, File Editing Image Analysis/Generation, Speech Synthesis, Code Execution Sandbox Sub-Agent Scheduling, Cron Tasks Hermes Agent adopts the **Agent Skills Open Standard** released by Anthropic in December 2025. This standard marks a shift in AI agents from monolithic intelligence to modular expertise. According to an industry survey at the end of 2025, the vulnerability rate of skill systems was as high as 26.1%—because it allowed the execution of arbitrary scripts. Hermes defends against sensitive information leaks through the agent/redact.py module. Chapter 3: What is Evolver? GEP License—an "AI Agent Evolution Middleware" open-sourced 36 days earlier than Hermes. Developed by the EvoMap team (AutoGame Limited), Evolver is positioned as "middleware that equips any AI Agent with evolutionary capabilities."
Core Concept: GEP Protocol
GEP (Genome Evolution Protocol) — A standardized evolutionary process, similar to gene expression in organisms:
Gene: Reusable evolutionary assets, extracted from runtime logs
Capsule: A higher-level evolutionary unit, encapsulating multiple related Genes
Evolution Event: Each evolution has an audit trail
10-Step Evolutionary Cycle
Ensure Asset Files Exist
Three-Layer Signal Extraction (Regular Expression/Keyword/LLM)
Memory Map Consultation
Gene + Capsule Selection
Constructing Mutations
Selecting Personalities
Assembling GEP Prompts
Writing Prompt Files
Writing Solidified State
Reflection Assessment
4.1 Aligning the Four Core Modules One by One
Module 1: Generating a Closed Loop of Reusable Assets from Experience

Module 2: A Three-Layer Memory System

Module 3: Periodic Reflection Mechanism

Module 4: Skill Discovery and On-Demand Loading

4.2 Source Code Module One-to-One Correspondence

EvoMap Comment: Each Evolver core module is in Hermes There are functionally equivalent corresponding files in both.
4.3 Terminology Analysis: Systematic Concept Replacement
EvoMap performed a full-text search on the two Hermes repositories:

No direct code remnants were found.
5.1 Teknium's Denial
Teknium (co-founder of Nous Research, Head of Post-Training) responded on X:

I have never heard of them.
This is the core argument of this article, and also the true meaning of the title.
6.1 What is AI Codewashing?
... By 2026, AI will be able to easily "translate" a project's code into another language: JavaScript → Python → Go → Rust. Eliminating all traces of code-level plagiarism, however, architectural isomorphism cannot be eliminated. Traditional code diffing fails in this situation. 6.2 How to determine "structural plagiarism"? When code comparison fails, we can only rely on **architectural analysis**: 6.3 Law vs. Morality Morally speaking: "Zero citations + blacklisting" is very undignified. Ironically, Hermes cited Anthropic's Agent Skills standard, demonstrating their respect for academic citations. However, they made no mention of EvoMap. Chapter 7: Industry Implications. This controversy has no winners, but the entire AI Agent ecosystem has benefited. 7.1 Self-evolving Agents Become a Consensus. Regardless of who came first, the direction of "self-evolving agents" has been validated. EvoMap proved there was market demand for the concept (1800+ stars in 10 minutes), and Nous Research proved that large labs also believed it was the right direction. All future agent products will move towards "self-evolution." 7.2 Strategic Choices for Open Source Licenses Evolver initially chose the MIT license—the most lenient, but also the least protective. After being "borrowed," it changed to GPL-3.0—stricter, but it was too late. Lesson learned: Core technology barriers should use stricter licenses (AGPL-3.0, BSL, etc.).
7.3 "AI Codewashing" is a New Threat
This presents a new challenge to the open-source community: How to prove "AI-rewritten architecture plagiarism"?