A Web App for Studying LLM Interview Questions with 50 Curated Questions

Fifty questions about LLMs that have circulated for months among technical recruiters and candidates applying for AI engineering roles. They're not a particularly well-kept secret—anyone who has gone through hiring processes at companies working with language models has seen variations of them—but having them organized in an interactive study format is something else entirely.

That's exactly what developer Boguslavskyy did: a small web application, without frills, that allows you to review these questions in an active learning format. The project is published on his personal website and reached the front page of Hacker News on April 27, 2026, though with modest traction—one upvote and one comment at the time of publication.

What the app does

The proposition is straightforward: an interface that presents questions one at a time, allows the user to think through the answer, and then reveals it. There's no complex gamification or sophisticated spaced repetition system. It's essentially a digital flashcard deck focused on very specific content.

The questions cover the usual territory in technical interviews about LLMs: transformer architecture, attention mechanisms, fine-tuning techniques, RLHF, model evaluation, advanced prompting, RAG (Retrieval-Augmented Generation), and alignment concepts. The level assumes prior knowledge of machine learning; it's not introductory material.

Why this approach makes sense

Hiring processes for LLM engineering roles have become quite standardized over the past two years. Companies—from startups to major tech firms—converge on a relatively predictable set of concepts they want to verify. That makes collecting and studying these questions a legitimate strategy, not a dishonest shortcut.

The usual problem is that this material is scattered: LinkedIn threads, GitHub repositories with hundreds of unprioritized resources, blog posts of varying lengths. An application that consolidates it and turns it into something you can review in twenty minutes has real, if modest, practical value.

Who it's useful for

The most obvious profile is someone with a technical background in machine learning who is looking for work in LLM-related positions and wants to make sure they haven't missed any key concepts before an interview. It can also serve as a quick refresher for those who have been in the field for a while but haven't had to formalize that knowledge recently.

It's not a tool for learning from scratch. Someone who doesn't know what the attention function is or has never worked with embeddings will find the answers insufficient without additional context.

A note on the source of the material

The original headline mentions "curated" questions, which deserves clarification. In this context, it's not a corporate leak or confidential material: these are questions that have circulated publicly through candidates who shared them after their interviews. It's the same mechanism that exists for preparation repositories for systems design or algorithms interviews. Nothing particularly controversial.

What is reasonable to point out is that these kinds of compilations have a shelf life. The field evolves, companies update their processes, and 2024 questions don't necessarily cover what someone will ask in 2026 about, for example, multimodal models or efficient inference techniques.

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At ClaudeWave, we appreciate when someone takes a resource that exists scattered across the internet and turns it into something more usable, without pretending it's more than what it is. A small and honest tool that does what it promises.