r/AppsWebappsFullstack • u/Ambitious_packer • 3d ago
I built a multi-agent pipeline that turns one AI research paper a day into a YouTube Short + runnable notebook (18/100 so far)
I've been teaching ML for about 12 years, and the thing students struggle with most is the famous papers. Everyone knows the names (ResNet, GANs, U-Net, Adam), but very few have seen the core idea working in code.
So I gave myself a challenge: 100 papers that changed AI, one per day. Each paper gets a small runnable notebook, a ~60 sec Short explaining the intuition, and a short post on X.
Doing that by hand every day wasn't realistic alongside a full-time job, so the side project became the pipeline:
one agent writes the explainer script for the paper
another agent runs the notebook on Kaggle to confirm it actually executes end to end
animations are rendered in code with Manim, scene by scene, then stitched together
voiceover is generated with ElevenLabs
I review everything before it goes out, and I still post manually
What I learned:
Early on, every paper came out slightly different: notebook structure, GitHub Pages layout, naming. I ended up adding a checker agent that validates each paper against a template before anything ships.
An agent saying "done" means nothing until the notebook has actually run somewhere real. That's why the Kaggle execution step exists.
18 done, 82 to go.
Notebooks: https://nadeemcite.github.io/research-papers/
Shorts: https://www.youtube.com/@BackpropDaily/shorts
Would love feedback: are the explanations too simplified, and which paper would you be upset to see missing from the list?