Enter, Now I Get It!
I made this app for curious people. Simply upload an article and after a few minutes you'll have an interactive web page showcasing the highlights. Generated pages are stored in the cloud and can be viewed from a gallery.
Now I Get It! uses the best LLMs out there, which means the app will improve as AI improves.
Free for now - it's capped at 20 articles per day so I don't burn cash.
A few things I (and maybe you will) find interesting:
* This is a pure convenience app. I could just as well use a saved prompt in Claude, but sometimes it's nice to have a niche-focused app. It's just cognitively easier, IMO.
* The app was built for myself and colleagues in various scientific fields. It can take an hour or more to read a detailed paper so this is like an on-ramp.
* The app is a place for me to experiment with using LLMs to translate scientific articles into software. The space is pregnant with possibilities.
* Everything in the app is the result of agentic engineering, e.g. plans, specs, tasks, execution loops. I swear by Beads (https://github.com/steveyegge/beads) by Yegge and also make heavy use of Beads Viewer (https://news.ycombinator.com/item?id=46314423) and Destructive Command Guard (https://news.ycombinator.com/item?id=46835674) by Jeffrey Emanuel.
* I'm an AWS fan and have been impressed by Opus' ability to write good CFN. It still needs a bunch of guidance around distributed architecture but way better than last year.
enos_feedler•3h ago
jbdamask•2h ago
Can you give me more info on why you’d want to install it yourself? Is this an enterprise thing?
poly2it•2h ago
jbdamask•1h ago
ayhanfuat•2h ago
jbdamask•1h ago
earthscienceman•1h ago
jbdamask•37m ago
Something I've learned is that the standard, "Summarize this paper" doesn't do a great job because summaries are so subjective. But if you tell a frontier LLM, like Opus 4.6, "Turn this paper into an interactive web page highlighting the most important aspects" it does a really good job. There are still issues with over/under weighting the various aspects of a paper but the models are getting better.
What I find fascinating is that LLMs are great at translation so this is an experiment in translating papers into software, albeit very simple software.