# How to Use AI to Practice LeetCode-Style Questions (Without Fooling Yourself)

> A concrete workflow for practicing algorithm questions with AI assistance: the attempt-first rule, graduated hints, structured review, and spaced re-solves.

Published 2026-08-14

There are two ways to use AI on LeetCode-style problems. One makes you dramatically better; the other manufactures the feeling of progress while your actual skill flatlines. The difference is not the tool — it's the workflow. Here is the one that works.

## The failure mode first

The trap: read problem → ask AI for solution → read solution → nod → "learned it" → next problem. Fifty problems later, you've built a superpower for *recognizing* solutions and no ability to *produce* them. Recognition feels identical to competence right up until an empty editor and a running clock, which is exactly where interviews happen.

The principle that prevents it: **AI enters after the attempt, never before.** Everything below is that principle turned into a routine.

## The workflow

### 1. Attempt cold, under a timer

Twenty-five minutes for a medium, in one sitting, no lookups. Struggling *is* the training — retrieval under mild pressure is what builds the pattern memory you'll need. Reaching the time limit without a solution is a fine outcome; you've now loaded the problem into your head, which makes the review stick.

### 2. Stuck? Take graduated hints, not answers

Ask your AI for the smallest useful push, escalating only as needed:

1. "Give me a nudge — no approach, no code." (e.g. "what if the array were sorted?")
2. "Name the pattern." ("this is a sliding-window problem")
3. "Outline the approach in three steps, still no code."
4. Full solution — only after a real attempt at each rung.

Every rung you *don't* descend is skill kept. Chatbots follow these instructions well if you state them explicitly.

### 3. Review against a complete answer — all four parts

After the attempt (solved or not), study a full worked answer: working code, test cases, time complexity, space complexity. Compare it against yours: Where did the approaches diverge? Which edge cases did their tests cover that yours missed? Is your complexity actually what you thought?

This is the step [Marauder Bot](https://www.marauderbot.com/) compresses. It reads the problem page directly in Chrome — no copy-paste, and it works on sites that disable text selection — and returns exactly that four-part answer for every question it finds (see the [live demo](https://www.marauderbot.com/demo-algorithm)). With three switchable models (GPT-6 Luna, Claude Opus 5.5, Gemini 3.5 Flash), a shaky answer gets a [second opinion in one click](https://www.marauderbot.com/blog/which-ai-model-is-best-for-solving-interview-questions). What took an evening of forum-thread archaeology takes seconds, which is what makes the review habit sustainable.

### 4. Interrogate until the "why" is yours

The worked answer tells you *what*; make the AI earn the *why*: "Why a heap and not sorting?" "When would this two-pointer approach break?" "Show me the naive solution and walk the optimization." A solution you can derive beats ten you've memorized — variations of a pattern show up far more often than exact repeats.

### 5. Re-solve from scratch, days later

The step everyone skips and the one that cements everything: three or so days after learning a problem's pattern, solve it again cold. If you can't, it was recognition, not competence — review again, re-queue it. (The JSON export of your analyses is handy for keeping this queue in a spreadsheet or flashcard deck.)

## Weekly structure

Practice in patterns, not random problems: a week on two-pointers, a week on BFS/DFS, and so on — three or four new problems a day through steps 1–4, plus two or three re-solves from earlier in the week. Add a weekly timed mixed session under [assessment conditions](https://www.marauderbot.com/blog/how-to-make-the-most-of-your-time-during-online-assessments) to train pacing alongside patterns.

## The one-sentence version

Attempt cold, hint minimally, review completely, interrogate the why, re-solve later — AI makes every step faster and none of them skippable. Run the loop for a few weeks and the difference is obvious in the editor, which is the only place it counts. If the review step is your bottleneck, [the free trial](https://www.marauderbot.com/sign-up) covers a week of practice sessions: 15 page analyses over 7 days.

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