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If you’re an instructor for the O’Reilly live training platform, you’ve got to be prepared for the unexpected. As a developer I think we all can understand the situation when a demo (you know, the one that you’ve tested a thousand times on your machine) easily decides on its own to go wrong while being demonstrated to a live audience. We’ve all been there. And of course, the biggest variable in the equation is the live Q&A portion of any course, because we actively encourage course participants to ask any question that’s on their mind.

Shortly after Anthropic announced that they were going to include AI watermarking in all text-based outputs from their latest models, I was flooded with questions during a Q&A session in a completely unrelated course about Claude Agents. Nearly everyone who posted a question in the Q&A box wanted to know more about how AI watermarking worked, and how it would affect them.

In light of that interest, I am taking this opportunity to help explain what watermarking means for you.

What did Anthropic officially announce?

I don’t want to put words in anyone’s mouth, so I’ll just quote Anthropic verbatim from its announcement in August 2026:

Future Claude models will generate text that contains a watermark. This is a way of determining the likelihood that Claude was involved in writing the text, and we, along with several other major AI providers, are implementing this change to comply with the EU AI Act.

Here’s another quote from the same announcement:

Watermarking won’t be specific to Claude. As of August 2, the EU requires AI providers serving its market to mark AI-generated content. Other major model developers have signed the same Code of Practice and will be implementing their own watermarks.

The list of Claude models (at the time of this writing) that include AI text watermarks in all generated outputs are:

• Claude Mythos 5.1
• Claude Fable 5.1
• Claude Fable 5
• Claude Opus 5.5
• Claude Opus 5
• Claude Opus 4.8
• Claude Sonnet 5.5
• Claude Sonnet 5
• Claude Haiku 5.5

It won’t matter if you use Claude Desktop, Claude Code, or the API, because all of Claude’s outputs will contain the AI watermark. As a result, any code, email, blog, article, newsletter, or white paper that you write using Claude will contain a watermark, and anyone who has an AI watermark detector can easily determine if that content was AI generated.

What’s the difference between cryptography and steganography?

Now let’s talk about two related terms that apply to what we’re dealing with when it comes to the AI watermarks: cryptography and steganography. Cryptography is something you encounter every day when you visit a website that uses HTTPS instead of HTTP. Your web browser automatically handles the encrypting and the decrypting for you, but what it simply does is make the content of anything that you send or receive unintelligible unless you have the key to decrypt the message. As a result, you can (for example) securely type in your credit card to sign up for an O’Reilly subscription, because we (like every other major website on the internet) use HTTPS on our website to ensure that no outsider can obtain your credit card information. Therefore, if an unscrupulous person intercepts something you send over an HTTPS connection, the contents will be encrypted and meaningless.

Steganography is completely different, and it’s what the Claude AI watermarking technology uses. Steganography is about hiding something in the right place for someone who knows where to look for it. Steganography is not cryptography, because everything about the message is in plain sight. However, you have to look deeper at the message itself to find the contents that have been hidden or obscured. The most common example would be any paper currency of a large denomination (like the $100 dollar bill). If you hold the bill up to a light, then you’ll see a “security thread” as well as a watermark of Benjamin Franklin’s face.

So, technically, how does the AI watermark actually work?

The Claude AI watermark uses a type of steganography based upon SynthID-Text, an open source project by Google DeepMind. SynthID-Text is a form of steganography because the signal (the information that you are looking for) hides inside the word choices of an ordinary-looking paragraph. Consequently, you can copy/paste the AI-generated code in your favorite code editor, or put an AI-generated paragraph into a Word document, an email, or a Slack message, and the AI watermark comes along for the ride.

According to Anthropic, the watermark changes only the source of randomness that the model uses when it picks among near-equivalent words, so nothing is added to the text. There are no hidden characters placed inside the AI generated text, and no extra tokens are consumed. Also, the watermark carries no information about you. This means simply that the AI watermark detector can determine if text is AI-generated, but it cannot determine whose Claude account was used to generate the text.

SynthID-Text uses a technique called tournament sampling. At each position, the model draws several candidate tokens and runs them through essentially what is a knockout bracket. The winner of each round is decided by a pseudorandom score (g-values) that comes from hashing the previous handful of tokens together with a secret key. In a body of text with hundreds of words, the text ends up slightly favoring tokens with high g-values in a pattern that only the key holder can see, and that you would never spot by reading.

“Slightly favoring” is the key phrase here. For example, the choice between the words “big” and “large” doesn’t change the meaning of most sentences, so nudging that choice to one of the two doesn’t change your text in any way you’d notice. Google tested this on roughly 20 million Gemini responses, and the thumbs-up rate differed by 0.01% (with the watermarked model slightly ahead).

Who else is watermarking their AI-generated content?

As previously stated, Anthropic’s decision to put AI watermarking on its content is mandated by EU laws and regulations that took effect in 2026. Anthropic is not the only company that has complied with this regulation and, according to the EU Commission website, hundreds of companies have agreed to comply with the regulations that require AI watermarks.

For example, OpenAI has recently announced their support for watermarking AI-generated outputs. Here’s a quote from their announcement:

Over the coming weeks, we will add an invisible watermark to eligible ChatGPT and Codex text output in the European Union.

OpenAI’s text watermarking technology is called “textGrain,” and it’s inspired by the art of writing text on a grain of rice. Now, you may be asking yourself, “How much AI text is needed in order to place the watermark itself?” The good news is that OpenAI has published statistics from their own tests for AI text watermark detection. Their AI text watermark detector has 95% accuracy for passages that contain 400-tokens of text. This gives you an idea that only a few paragraphs of text is all that’s needed in order to embed the watermark.

However, since the EU mandate applies to AI-generated content (not just text), OpenAI has gone even further and released a website to let anyone know if their models have generated non-textual media, such as images and audio. I’ve tried the website myself and it correctly identifies a watermark within a few seconds.

The regulation dictating AI watermarks is not just an EU thing. The SB-942 California AI Transparency Act also requires watermarks on AI-generated content. These regulations, combined, not only apply to AI-generated text but also to images, audio, and video.

Google’s model outputs also contain AI-watermarks

Google complied with the EU AI Act years ago, so their models have included the SynthID Text Watermark since 2024. However, they’ve followed suit with OpenAI and released a public website, SynthID.com, to allow anyone to check if any non-text media (such as images, audio, and video) contains the SynthID AI watermark. Google’s AI watermark detector allows you to check for a watermark from multiple AI providers such as OpenAI, Nvidia, Kakao, and of course, Google themselves.

Watermarking all AI-generated content is not necessarily a bad thing

In my most recent experience, I worked as a consultant for a company that was undergoing a VC-backed funding round. After the funding was publicly announced, certain people at the company were being contacted by the “CEO,” who asked them to perform a bank transfer from their personal accounts because of some made-up situation. In reality, it was a group of scammers that used LinkedIn to find the names of employees of the company, and then posed as the CEO so that employees would send money into the scammer’s bank account. Most of us were tech-savvy enough to understand that this was an obvious ploy driven by unscrupulous people. The scammers gave themselves away because they were using email domains that were not owned by the startup, so in this case, the fraud attempt was easily detectable.

However, the technology exists today where voice cloning can be easily accomplished with only a few samples of a person’s voice. So what if a more sophisticated “spear phishing” attempt was done where the attacker decided to use AI in order to clone the CEO’s voice? And what if the fake CEO started calling people (instead of sending emails)? This could lead to a much worse situation where employees think they’re interacting with (and obeying) the CEO and feel compelled to do something that could have grave financial consequences.

What this means for you

All the major LLMs are including watermarking in their AI-generated content, and due to recent regulations, that’s not going away. Bad actors can use AI today to perform serious attacks on the public, so having an AI watermark on any AI-generated content (text, images, audio, or video) is a very useful tool to determine authenticity.

If you want to see a live demonstration on how AI watermarks can be applied and detected on your own, be sure to attend the course Understanding AI Text Watermarking, only on O’Reilly.

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