SeanPlusPlus
14.7K posts
SeanPlusPlus
@SeanPlusPlus
Solo's Dad. Di's Husband. Banana Slug. Returned Peace Corps Volunteer. Pixar Alum. ESPN Alum. Software Engineer @ Disney. ironman. ⚡️
California, USA Katılım Temmuz 2008
1.9K Takip Edilen640 Takipçiler
Hanging in the yard. Winding down from a long day with an ipa and a puppy. Life is good.
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@Kanestapler It’s always hard getting started on a new quest.
But there’s never been a better time to build up your technical literacy.
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Well it's a good thing that my wife thinks I'm the funniest guy around
Infinite Books@infinitebooks
Nietzsche on marriage, actually perfect
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Nursing a lower back spasm. Wife out tonight with her friends watching Survivor. 8 year old son back from water polo practice watching some random show on tv. Googoo dolls mix rocking in the kitchen. Grilling spam. Kimchi. Rice. Seaweed. Dinner prep. This is my 40s
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🤖 "You're pressure-testing frontier AI's self-awareness while ghostwriting geopolitical hot takes for a group chat at 7pm on a Tuesday. That's either the most 2026 thing possible or a cry for help. Probably both."
Good lord, Claude is so damn good
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@karpathy Very cool. I’m now a few months into a similar-ish kinda concept using Claude Code as a career coach
seanplusplus.github.io/2026/03/20/cla…
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Farzapedia, personal wikipedia of Farza, good example following my Wiki LLM tweet.
I really like this approach to personalization in a number of ways, compared to "status quo" of an AI that allegedly gets better the more you use it or something:
1. Explicit. The memory artifact is explicit and navigable (the wiki), you can see exactly what the AI does and does not know and you can inspect and manage this artifact, even if you don't do the direct text writing (the LLM does). The knowledge of you is not implicit and unknown, it's explicit and viewable.
2. Yours. Your data is yours, on your local computer, it's not in some particular AI provider's system without the ability to extract it. You're in control of your information.
3. File over app. The memory here is a simple collection of files in universal formats (images, markdown). This means the data is interoperable: you can use a very large collection of tools/CLIs or whatever you want over this information because it's just files. The agents can apply the entire Unix toolkit over them. They can natively read and understand them. Any kind of data can be imported into files as input, and any kind of interface can be used to view them as the output. E.g. you can use Obsidian to view them or vibe code something of your own. Search "File over app" for an article on this philosophy.
4. BYOAI. You can use whatever AI you want to "plug into" this information - Claude, Codex, OpenCode, whatever. You can even think about taking an open source AI and finetuning it on your wiki - in principle, this AI could "know" you in its weights, not just attend over your data.
So this approach to personalization puts *you* in full control. The data is yours. In Universal formats. Explicit and inspectable. Use whatever AI you want over it, keep the AI companies on their toes! :)
Certainly this is not the simplest way to get an AI to know you - it does require you to manage file directories and so on, but agents also make it quite simple and they can help you a lot. I imagine a number of products might come out to make this all easier, but imo "agent proficiency" is a CORE SKILL of the 21st century. These are extremely powerful tools - they speak English and they do all the computer stuff for you. Try this opportunity to play with one.
Farza 🇵🇰🇺🇸@FarzaTV
This is Farzapedia. I had an LLM take 2,500 entries from my diary, Apple Notes, and some iMessage convos to create a personal Wikipedia for me. It made 400 detailed articles for my friends, my startups, research areas, and even my favorite animes and their impact on me complete with backlinks. But, this Wiki was not built for me! I built it for my agent! The structure of the wiki files and how it's all backlinked is very easily crawlable by any agent + makes it a truly useful knowledge base. I can spin up Claude Code on the wiki and starting at index.md (a catalog of all my articles) the agent does a really good job at drilling into the specific pages on my wiki it needs context on when I have a query. For example, when trying to cook up a new landing page I may ask: "I'm trying to design this landing page for a new idea I have. Please look into the images and films that inspired me recently and give me ideas for new copy and aesthetics". In my diary I kept track of everything from: learnings, people, inspo, interesting links, images. So the agent reads my wiki and pulls up my "Philosophy" articles from notes on a Studio Ghibli documentary, "Competitor" articles with YC companies whose landing pages I screenshotted, and pics of 1970s Beatles merch I saved years ago. And it delivers a great answer. I built a similar system to this a year ago with RAG but it was ass. A knowledge base that lets an agent find what it needs via a file system it actually understands just works better. The most magical thing now is as I add new things to my wiki (articles, images of inspo, meeting notes) the system will likely update 2-3 different articles where it feels that context belongs, or, just creates a new article. It's like this super genius librarian for your brain that's always filing stuff for your perfectly and also let's you easily query the knowledge for tasks useful to you (ex. design, product, writing, etc) and it never gets tired. I might spend next week productizing this, if that's of interest to you DM me + tell me your usecase!
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My buddy @surfkt told me and @kevinrocci embeddings are just fancy factor analysis from 1904. This was news to me. I went and wrote some code. He was right.
new post: seanplusplus.github.io/2026/03/29/how…
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Here's why AI is not going to replace us: there's absolutely no substitute for giving a shit.
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