mtrx

I use herdr daily. One thing I’ve always missed from all of these solutions, though, is the ability to actually make code changes..none of them seem to offer that properly. Am I the only one? Is the goal to abandon code entirely?

IMO, saying "Pangram thinks Echo’s writing is human more often than frontier models." is only a testament to how unreliable AI detectors are.

Unfortunately, for people trying to bypass those detectors, that metric probably matters quite a bit. I've seen students firsthand checking their AI-generated documents over and over again until they got them just right to pass.

A better, albeit not perfect, approach is to look at the writing process itself. For essays, a few tools let you examine and replay Google Docs revision history. I built one of them, Turingo (www.turingo.net), which tracks suspicious pastes throughout the revision history. This approach is not without problems, such as autotypers, which I'm hopefully going to address soon, but it beats a detector's guess.

Lately, I've been thinking about having a similar proof-of-process for other content as well (blog posts, code, etc). If anyone is working on such a thing, or knows any interesting projects, please let me know!

I was at EduLearn (a major edtech conference) this year and talked to many professors exactly about this. A lot of them are pulling work back into the classroom, but keep running into the same problems:

- some skills only develop through the actual writing (similar to how you can't learn to code just by watching YouTube videos)

- in-class assignments are not always scalable (and students end up using AI anyway)

- students aren't motivated enough to participate actively

I think looking at the writing process is a more realistic approach, so I built Turingo (https://www.turingo.net). It replays how a Google Doc was written, highlights unusual edits (large pastes) and tracks how that text changed afterwards. Surprisingly, several professors reported that students often underestimate how much LLM-generated text is left in their final drafts, so just seeing the replay changes the conversation.

It's not meant to be a verdict machine like the existing AI detectors (another big problem in education), more of a starting point for the kind of conversations the author's TAs are having. In fact, we're also beta testing a feature that suggests a few questions for the professor to ask based on the replay.

And yes, it's not perfect and autotypers do exist, but they're dumber than you'd expect and nowhere close to mimicking a real human (I hope to address that soon).