# Some recent applications of AI > Source: > Published: 2026-08-25 10:51:00+00:00 [Trevor McKendrick asked](https://ckarchive.com/b/xmuph6hp4en3kurnppvnqc20gw8kranhd6g7) for favorite recent applications of AI. Here are some of mine: - I have a large corpus in which I want to find the most frequently occurring facts. I've built a system that (i) attempts to extract the facts from items in the corpus, (ii) generates their embeddings, and (iii) runs a clustering algorithm over the result to estimate which of the extracted facts should count as the same. - I'm keeping all important school-related documents in a Claude project. It is [reliable enough](https://www.natemeyvis.com/civic-applications-of-generative-ai/) at extracting and interpreting practical information that I can ask it to, e.g., update my personal calendar with all the relevant dates. - Speaking of "now good enough at juggling nontrivial real-world information," I'm finding it not only amusing but actually worthwhile to ask an email- and calendar-connected LLM something like "please find all the information related to my trip to *X* next week and make sure everything seems on track." - I'm now reliant on using the [Zippyflash](https://www.zippyflash.com/) API via LLM for (i) allowing me to do some of my flashcard reviews with pen and paper (by asking it to generate PDFs of paper-friendly due cards and then asking it to grade my work, confirming any nontrivial right-wrong decisions with me), (ii) allowing me to customize my study sessions in *ad hoc* ways that would be very hard to anticipate in advance, and (iii) allowing me to reschedule low-priority cards in smart ways when I run up a backlog. Some patterns, here and in my other recent AI usage: - There's a shape of task that prompts a "OK, I need to gather a bunch of mostly-unstructured real-world data and check stuff" reaction. (The school- and trip-information cases are like this.) AI has graduated from "can see the data and be sort of useful" to "can reliably handle these tasks, though I double-check the important stuff." This is a huge step up. [Cheaper, faster models](https://www.natemeyvis.com/try-the-very-fast-models/) are good enough that I don't feel much friction when I find a question that might be addressable with AI. (The fact-extraction example is one of several like this.) There's a big difference, for me at least, between spending three hours and $50 on something and spending 30 minutes (of active time) and $5 on it. - I also find myself deferring some interesting, low-urgency projects in anticipation of their being much cheaper a few months from now. This involves both prioritization and also some guesswork about which kinds of tasks AI will improve at the most. - I *don't* find it much better, compared to a few months ago, with questions like "what books should be on my list but aren't?" and other high-judgment lifestyle questions. As AI gets vastly better at the basic triage and annoying, lower-judgment data management that I imagine a personal assistant might do, it's nowhere near replacing the highest-judgment aspects of a PA's job. (N.B.: I have no first-hand experience of personal assistants.)