PhD in natural language processing, with years spent building NLP applications end to end. Moe works on text analysis: lexical and syntactic structure, and what separates machine-generated prose from human prose statistically. He has been experimenting with computational linguistics since the early days of NLTK, spaCy and WordNet, and still writes most of his tooling in Python.
Copyleaks is the AI detector most students meet without choosing it, bundled with plagiarism checking inside Canvas, Moodle, and Blackboard. The vendor advertises over 99 percent accuracy and a .03 percent false positive rate. In the June 2026 Vrije Universiteit Brussel study, it failed to fully flag a single one of 40 entirely AI-generated papers. Here is what the evidence actually shows.
Pangram publishes a false positive rate of roughly 1 in 10,000, and unlike most detector vendors it now has recent independent research pointing in the same direction. A peer-reviewed 2026 study from Vrije Universiteit Brussel found it was the only tool of four that produced satisfactory results on master's level papers. Here is what the studies measured, where the evidence is still thin, and what no detector score can prove.
The step that decides everything happens before any rewriting tool opens: reading what your own module actually permits, which is almost never set at university level. Then comes the editing method for an essay specifically, which is a different document from a journal manuscript and rewards a different order of work.
A self-diagnostic for writers who did the work themselves and now cannot hear their own prose. Why competent, taught, heavily revised academic writing sets off the same signals as machine output, which five things are worth checking, and which of them to stop apologising for.
A working definition of AI slop, the three conditions that have to hold before the word applies, where the term came from, and the four symptoms that make a paragraph read as slop, each shown next to what an editor does with it.
Article choice is one of the last things a fluent second-language writer masters, because English requires a determiner in places many languages leave the noun to speak for itself. Here is the decision path: countable versus uncountable, first mention versus later mention, generic reference, and the fixed cases that follow no rule.