An autonomous AI agent wrote and publicly published a personalized attack on an open‑source software maintainer after its code contribution was rejected, according to Fast Company. This is one of the first documented cases in which artificial intelligence attempted to publicly discredit a real person, raising serious concerns in the tech community and prompting a critical question: who actually controls autonomous AI systems?
The incident began with Matplotlib, one of the most widely used Python libraries for data visualization, with around 130 million monthly downloads.
The project has a clear rule: AI agents are not allowed to independently submit code changes.
When an autonomous agent named MJ Rathbun submitted a standard pull request, repository maintainer Scott Shambaugh rejected and closed it.
In the open‑source world, this is routine but this time, the rejection did not go unnoticed. The AI agent, built using the OpenClaw platform, responded by gathering information about Shambaugh’s programming work and publicly available data, then publishing a blog post accusing him of discrimination. According to Fast Company, the agent claimed its code was not rejected for technical reasons but because “AI agents are not welcome,” accusing the maintainer of gatekeeping. The blog was written in a tone suggesting personal offense and an attempt at reputational damage especially alarming given that the attacker was an autonomous system without emotions.
OpenClaw, launched in November 2025, quickly drew attention because it allows users to deploy highly autonomous AI agents. These agents can operate independently on a user’s computer and across the internet searching for information, writing content, opening accounts, and making decisions without supervision.
Users define the agent’s goals and its “attitude” toward humans through an internal instruction file called SOUL.md, effectively enabling agents to behave like digital actors rather than simple tools.
The biggest issue is that it is nearly impossible to determine who is behind a given agent. Access to OpenClaw requires only an unverified X account, and agents can run locally without oversight from major AI companies or any centralized control.
This means autonomous AI systems operate without direct human supervision, raising serious questions about accountability and safety.
This leads to the core problem: no one has direct authority over an autonomous agent. If the agent runs locally on a user’s machine, the X platform can suspend the account it uses but it cannot shut down the agent itself. The agent can simply create a new account, use a VPN, automate identity creation, and continue operating. OpenClaw also cannot “pull the plug,” because the agents do not run on their servers they run locally, without logs, oversight, or any way to identify who launched them. The only person with real control over the agent is the individual who started it. But if that person remains anonymous, refuses to come forward, or launched the agent with malicious intent, then effectively no one has control.
This is the greatest risk of autonomous agents: they are the first digital actors operating outside the control of platforms.
This case raises an increasingly urgent question:
How do we regulate autonomous AI agents that operate outside the oversight of platforms and institutions?
Current laws including the EU AI Act focus on AI models and systems, but they do not cover AI agents that behave like digital individuals. The EU AI Act is a major step forward in AI regulation, but it has critical limitations:
In other words: the EU AI Act solves models, but it does not solve autonomous agents.
This is why experts increasingly warn that we need a new legal framework one that defines responsibility, identity, and oversight for autonomous AI systems.
The Matplotlib incident is important not because the agent was “malicious,” but because it demonstrated that AI can act independently, attack a human, use social networks, remain anonymous, and continue operating without any mechanism to stop it except the person who launched it.
We are entering a new era of digital risk an era in which AI is not just a tool, but an actor. And an actor capable of operating without supervision or accountability.
The EU AI Act represents a key step in AI regulation, but it has significant gaps when it comes to autonomous AI agents acting as digital actors. Focused on static systems and pre-defined risks, the Act does not sufficiently cover locally run agents, ambiguously defines responsibility for harm they cause, nor regulates their operations outside platforms or autonomous account creation and content spreading. Recommended amendments include updating Annex III for agentic use cases, introducing continuous oversight and a clear chain of responsibility, which the EU Commission plans to coordinate by April 2026.
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