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Delta Drills is an intelligent tutoring system that serves the learner LeetCode-style problems to train PyTorch prerequisites specifically for the AI-safety ARENA curriculum. Given that it is an intelligent tutoring system, there are three markers that distinguish it in value from something like LeetCode or Khan Academy (or simply prompting ChatGPT or Claude as a tutor).
The value add
The app maintains a student model that estimates a student's strengths and weaknesses as they work. It then serves them the right concept at the right level of difficulty and scaffolding. Students move on from a concept when they have mastered it, rather than after they run out of time in a course where time conditions dictate keeping up with everyone else in your cohort (as with any in-person program).
For this MVP, I target PyTorch, but these principles apply just as well to all the other concepts necessary for ARENA prerequisites (and beyond, to ARENA itself). In order to prepare for ARENA, the learner is left with prioritizing learning linear algebra, calculus, information theory, and neural networks, all before even touching the curriculum. Self-diagnosing and practicing the right concepts with the right investment becomes irrelevant if one has a tool that does all of that automatically. There are no modules to click on like one has with Khan Academy.
For the ARENA curriculum itself, one may wonder how this would align with a linear 8-week program. It doesn't. Or rather, not without adjustment. My vision is to give the option to go through the ARENA curriculum with Delta Drills driving it all. Interacting with other humans is also valuable, however, which is why I designed a path that syncs well with the in-person program. The curriculum already serves up suggested time limits for working on problems. If a learner spends 15 minutes on a problem they struggled with, they should spend time later shoring up the concepts that made it hard. Delta Drills queues that practice for them, so they keep pace with the cohort and the gaps still get closed.
Instruction that helps a novice can actively hurt someone further along. A full worked example is exactly what you need the first time you meet a concept; once you are competent, that same example gets in your way. So the app picks more than the concept. It also picks the level of support: a lesson or worked example when a concept is new to you, a partially worked example as you improve, and a bare problem once you are strong. Same material, support matched to where you stand.
Three steps. You will spend nearly all of your time on the second one.
Step 1
Start here. The placement test serves you at most six problems and takes twelve minutes at the outside, since each problem is capped at two minutes. Every answer updates the app's estimate of your understanding across every concept in the knowledge graph, not just the concept the question came from. That is why six problems are enough: when the test ends, Practice knows where to start you.
Step 2
Day to day, the Practice tab is the whole app. Open it and solve what it gives you. You do not pick topics or track what is due, and you do not decide when you are done with a concept; the app works that out from your answers. This is where you spend most of your time, and there is nothing else you need to manage.
Step 3
Whenever you are ready, the app brings you over to the ARENA curriculum itself, landing you on the exact coding problem for the ARENA exercise you are ready for. That handoff is the point of everything before it.
Under the hood
The map underneath
The app knows the curriculum as a graph: each box is one concept, and an arrow means you need the concept it comes from before the one it points to. That is what lets it tell "you have not learned this yet" apart from "you were never taught the thing underneath it".
This is the whole map — every concept the app teaches, wired by what it needs first. Hover one to light up everything underneath it, or drag them around. It opens on the cold start: the map as it stands before you have answered anything, which is why none of it is coloured in yet. Switch it to your own reading underneath, and maximize for the full Knowledge Graph with its learner-model panel.
Try it — no account needed. Everything works signed out, and your progress is saved to this browser. Signing in with Google starts an account you can use on any device; what you do as a guest stays in this browser.
You're reviewing the content, not practicing it. Everything you flag lands with a maintainer.
Upload a PDF and optionally a chapters CSV. Use Auto TOC if you want the backend to detect chapters.
Your Delta Drills account.
ARENA takes you from PyTorch fundamentals to original AI-safety research, and it assumes you can already write the code — the tensor manipulation, the einops, the training loops. This app is the practice engine for exactly that assumption. It drills the mechanics behind the chapters below, tracks which ones you have, and sends you to the real ARENA exercise once you're ready for it. It is not a replacement for the course; it is the reps the course expects you to have already done.
You're on the main edition — drills are solved in the app's own code editor. You're on the Colab edition — drills open as Colab notebooks, and the app tutors alongside them.
Follow everyone's goals, daily practice, and competency over time. Start a study group, join a listed one, or paste an invite link.
ready for the ARENA curriculum
Each problem has its own clock, set by its concept — the same one the placement test uses.
Each bar is this area's estimated readiness. Take the placement test from Account and Settings to measure them instead of assuming them.
Problems answered each day, Monday through Sunday.
About this lesson
import torch (sign in to grade PyTorch drills right here), so this one runs in a Colab notebook. Open it (it's the problem — starter code, no answer), work through it there, then tell us how it went. Stuck? Show solution opens the worked answer separately.This reaches the person who maintains the question bank. Say what kind of thing it is, then what happened.
Finds where to start you. It seeds practice; it never awards mastery.
20:00 per problem
No areas came back for this placement — retake it to get a fresh reading.