Thanks to everyone who tried this today and those who provided feedback. I really appreciate your time. Here are some stats:

100 papers processed.

Cost breakdown:

LLM cost $64

AWS cost $0.0003

Claude's editorial comment about this breakdown, "For context, the Anthropic API cost ($63.32) is roughly 200,000x the AWS infrastructure cost. The AWS bill is a rounding error compared to the LLM spend."

Category breakdown:

Computer and Information Sciences 41%

Biological and Biomedical Sciences 15%

Health Sciences 7%

Mathematics and Statistics 5%

Geosciences, Atmospheric, and Ocean Sciences 5%

Physical Sciences 5%

Other 22%

There were a handful of errors due to papers >100 pages. If there were others, I didn't see them (but please let me know).

I'd be interested in hearing from people, what's one thing you would change/add/remove from this app?

That decision-tree page is killer!

Sorry you hit this. 100 papers were processed today. Cost to me was $63.

Make this a paid service! This could go viral

Very nice of you to say.

Very cool. Appreciate it.

Agree. Curious if you’ve played with landing.ai?

I hear you.

For me personally, the pain point is being interested in more papers than I can consume so I’ve gotten into the habit of loading papers into LLMs as a way to quickly triage. This app is an extension of my own habit.

I also have friends without scientific backgrounds who are interested in topics of research papers but can’t understand them. The reason for the cutesy name, Now I Get It!, is because the prompt steers the response to a layperson

Sorry. Reached 100 uploads today. Check out the gallery

LLMs, even the best ones, are still hit or miss wrt quality. Constantly improving, though.

I see more confusion from Opus 4.x about how to weight the different parts of a paper in terms of importance than I see hallucinations of flat out incorrect stuff. But these things still happen.

surely, but it is a considerable concern? deflecting constructive feedback is probably not the best encouragement for others for a show HN?

Hmmm, didn’t realize I was deflecting - just stating facts. But if I came across that way then criticism noted.

If I turned this into a paid app then more attention would be given to quality. There’s only so much an app that leverages LLMs can do, though. With enough trace data and user feedback I could imagine building out Evals from failure modes.

I can think of a few ways to provide a better UX. One is already built-in - there’s a “Recreate” button the original uploader can click if they don’t like the result.

Things could get pretty sophisticated after that, such as letting the user tweak the prompt, allowing for section-by-section re-dos, changing models, or even supporting manual edits.

From a commercial product perspective, it’s interesting to think about the cost/benefit of building around the current limits of LLMs vs building for an experience and betting the models will get better. The question is where to draw the line and where to devote cycles. Something worthy of its own thread.

Sometimes the LLM output isn’t great. If you uploaded the paper you can click Recreate. Otherwise just upload the PDF and see if you get a better response

Good to know. There are also limits to context window of file size. These errors are emerging as people use the app. I'll add them to the FAQ.

The app doesn't do any chunking of PDFs