Mistral AI secured a US patent for 'code-based tool calling' in just 118 days, drawing criticism that it is attempting to monopolize a technique already commonly used in the industry.
Imagine this: Every morning, you tell your AI assistant, “Check today’s weather and write it down in my notebook.” The AI retrieves information from a weather website and writes it into the notepad app on your smartphone. The AI has learned how to use these tools (checking weather, saving notes) on its own, as if it were writing the code itself. But what if a specific company had patented this “AI tool usage method” that everyone takes for granted?
Recently, French AI firm Mistral AI has found itself at the center of this controversy. In an exceptionally short period of just 118 days, it secured a US patent from the USPTO for “Code implemented tool calls” technology [Reference 9].
Why is this important?
It creates a risk that the AI services we use in our daily lives could suddenly be trapped by “patent infringement.” AI agents (AI that uses tools autonomously in response to human requests) are currently evolving beyond simply providing answers to “acting,” such as sending emails or modifying files [Reference 11].
Concerns are rising that Mistral AI intends to monopolize this connection point with its new patent. If this method is protected by patent, other companies could become entangled in legal disputes or face obstacles in technical development when implementing similar functions [Reference 10].
A simple analogy
Think of it this way: It is completely natural for a chef to use a knife while cooking. Now, imagine someone suddenly patents the “specific movement of grabbing a knife, slicing ingredients, and placing them on a cutting board.” From now on, other chefs might have to pay a usage fee to that person every time they use a knife, or contemplate entirely different methods to avoid legal trouble. What is happening in the AI industry right now is exactly like this.
What is the core of the technology?
Let’s look a little closer at the technical details. The core of this patent (US 12,670,045 B1) is that when an LLM (a Large Language Model, an AI that generates sentences by learning from vast data) needs to use a tool, it directly generates the tool-usage code [Reference 8, [Reference 14].
The operation happens in three main steps:
- The AI generates the code. When the AI receives the command “Write something in the notebook,” it writes the Python code to run the notebook app itself.
- It executes in a sandbox. The code created by the AI is executed in a secure virtual space, isolated from the user’s computer, to ensure it causes no harm.
- It verifies the result and returns. If values are needed during tool execution, it pauses briefly, receives external results, and delivers them back to the AI [Reference 13].
Because this method is more reliable and safer than previous approaches, it has become a standard technology widely utilized across the AI industry.
Industry and expert reactions
Many experts and developers are unable to hide their embarrassment. Concepts similar to this have been adequately addressed in various academic papers published in 2024, not to mention that companies like Cloudflare, Anthropic, and OpenAI have been using such methods [Reference 8].
Typically, it takes over two years on average to receive a utility patent in the US. However, Mistral AI managed it in just 118 days [Reference 9]. Because of this, some are harshly criticizing the move, stating, “It has become a fight over who can plant their flag first on technology that was already being used like air” [Reference 14, [Reference 15]].
Future outlook
This incident will serve as an important precedent for how AI companies choose to disclose and protect their technology in the future. While Mistral AI explains that this patent is the result of legitimate efforts toward innovation, the tech community is watching closely, fearing that this patent could become a “minefield” that blocks the free development of the AI ecosystem [Reference 1, [Reference 12].
We must now look beyond what AI can do and watch who owns and controls that technology. Will the AI assistant you use today be able to freely use tools tomorrow? The answer depends on the patent disputes and industry responses that will unfold moving forward.
References
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[Mistral Patent for “Code implemented tool calls” Hacker News](https://news.ycombinator.com/item?id=49243397) - US Patent Process in 2026: Timelines, Rejections, Strategies
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[Managing a patent USPTO](https://www.uspto.gov/patents/basics/manage) -
[Patent related notices - 2025 USPTO](https://www.uspto.gov/patents/laws/patent-related-notices/patent-related-notices-2025) -
[Search for patents USPTO](https://www.uspto.gov/patents/search) -
[Patent Public Search USPTO](https://www.uspto.gov/patents/search/patent-public-search) - UNITED STATES PATENT AND TRADEMARK OFFICE
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- Technology for AI to directly create new AI models
- A method where LLMs generate code for tool usage and execute it in a sandbox
- A new encryption algorithm to protect user personal information
- Because the patent fees are too expensive
- Because it is a universal technology already widely used in the industry
- Because it significantly slows down AI models
- It is the same as usual
- It took much longer than usual
- It was processed much faster than usual