As it is currently written, this is less useful the more niche your interests are. I think for such users, looking at their comment history or upvoted history might be useful instead of or in addition to just sampling recent, popular articles.
In my case, none of the topics I most like to read about and discuss on HN (package management, software freedom, next-gen CLI tools, next-gen shells, philosophy, desktop Linux, functional programming, hacker history, literate programming, Emacs, bitching about common development practices, programming language design, configuration languages) managed to appear in the 30-post sample I used. The profile it wrote for me was pretty good considering that, but definitely not great.
The assessment was also mistaken about my degree of interest in "low level" technical details like binary file formats (in fact it's rather low, although it has gradually increased over time), and my degree of interest in theoretical computer science issues (in fact it's high, but all of the theoretical papers in the sample were about machine learning, which was not an area of academic focus for me).
I do really like the simplicity and customizability of this (exposing the profile as Markdown and making it editable is awesome), and the quality of the results is very good given the tiny input size. But if your primary interests are not super aligned with the mainstream on HN, you won't get a chance to demonstrate that you like them. If users could type a few terms to say what their biggest interests are before running through the samples, this could work even better for people like me.
It would also be interesting if this could work based on article contents and not just headlines. Sometimes I open something and close it immediately, or I open it undecided as to whether I will skim or read closely.