I was a skeptic. Couldn’t trick pangram yet.

It's pretty simple.

1. Create AI generated text with 2+ models.

2. Merge the text (have a model just choose 'best' text). this step is to get "good" writing.

3. Use an open model to 'flatten' the text. Open models are not as good at writing, so the writing gets slightly worse.

4. Have a locally trained model on your writing samples rewrites with your voice.

Seems not so simple after all. How would one even go about training a local model on their own writing voice?

You can't trick it with AI generated text, but can you trick it into calling something AI generated which isn't? From what I've seen these AI detection tools are very good at detecting AI generation, they're also very good at calling anything AI generated.

Pangram boasts an extremely low false positive rate, in contrast to other AI detection tools. This has matched my limited experience.

If you have text that you can prove is not AI-generated (e.g. it is demonstrably older than about 5 years) that gets an AI flag, you could try tweeting at the Pangram founder, I've seen screenshots of him offering bounties (admittedly mostly as a dare to claims he doesn't believe).

Really? Pangram is very easy to bypass in written form.

Yes. Even as little as a "humanize and rephrast this to be more natural" prompt with high temperature on a uncommon model reduces the confidence greatly.

And does it preserve the original meaning, including various nuances? I have never been able to trick Pangram so I am very curious of the details.

AI companies might have no incentive but determined actors do, by definition. Anything Pangram could possibly do (even semantic variation detection) can be trivially bypassed by doing img2img on a custom trained local model, which is in itself done trivially in practice by many people. Same for text. This gives you false sense of reliable detection and false negatives as a result.