INTERVIEW PRACTICE, BUILT LIKE THE REAL THING

Train for the interviews that decide the offer.

Practice coding, AI, and quant challenges in a real workspace. Get intelligent feedback, build a focused plan, and walk into the loop knowing what to improve.

Try a real challengeUnlock the 7-day trial

Start with a free challenge. Upgrade only when you want the full plan.

Focused tracks across coding, AI & quantAI review on every submission
Practice workspaceTimed mode
Challenge 01Interview grade

Optimize a score under a fixed move budget.

Make the tradeoffs explicit, implement the solution, then explain why it holds under the constraints.

FocusState design
LanguageC++ / Python
FeedbackAI review

Review prompt: Explain how your state transitions avoid repeated work.

CHOOSE YOUR TRACK

Start where your next interview starts.

Every track opens a focused challenge set, not a generic problem dump.

Quant & trading

Math, probability, and optimization patterns for quantitative reasoning.

Explore track

Software engineering

Arrays, data structures, and implementation under pressure.

Explore track

AI & machine learning

State modelling, dynamic programming, and applied technical reasoning.

Explore track

System design

Caching, tradeoffs, and clear technical communication at scale.

Explore track
INTERVIEW-GRADE PRACTICE

Practice the patterns they ask. Get feedback that holds up in the loop.

Each challenge is tagged with its interview pattern and, where sourced, the relevant firm and round. Solve in a full editor, then run against the test cases that decide the result.

Jane StreetMediumTrading round

Max score in k moves

You start at index 0 of an integer array arr. On each move you may stay or advance to i + 1. Before every move you collect arr[i]. Return the maximum total achievable after exactly k moves.

  • 1 ≤ n ≤ 10⁵
  • 1 ≤ k ≤ 10⁵
  • arr[i] may be negative
Try a problem free
max_score.cppC++23 · GCC 14
long long maxScore(vector<int>& arr, int k) {
    int n = arr.size();
    // dp[j] = best total using exactly j moves from here
    vector<long long> dp(k + 1, 0);
    for (int i = n - 1; i >= 0; --i) {
        long long best = 0;
        for (int j = 1; j <= k; ++j) {
            // collect arr[i], then stay or advance
            long long stay = arr[i] + dp[j - 1];
            best = max(best, stay);
            dp[j] = best;
        }
    }
    return dp[k];
}
TestTimeStatus
#1 arr=[1,2,3] k=30.3msAccepted
#2 arr=[1,20,3] k=30.5msAccepted
#3 arr=[5,-2,9] k=40.4msAccepted
27Curated problems
StructuredLearning paths
Hands-onCode editor + tests
Pattern-firstInterview prep

Browse company-tagged practice

Google
Meta
Amazon
Apple
Microsoft
Netflix
Stripe
Uber
Airbnb
LinkedIn
X
Spotify
27

Curated problems

Multiple

Languages supported

Always

Editorials per problem

The AlgoCracked Ladder

Five tiers. Only two matter once you're past the phone screen.

Every problem is scored by global solve rate — not hand-waved into “Easy / Medium / Hard”.

Easy> 75%Warmups
Medium40 – 75%Phone screens
Hard15 – 40%Onsite loop
Cracked5 – 15%Jane St · Meta E6
Cooked< 5%Final quant screen
The quant edge

The quant interview is a different animal.

Quant screens combine probability, statistics, markets, and implementation. Practice those disciplines in focused tracks and review progress after each session.

Trading

Read the market, not just the array

Practice options, probability, and P&L reasoning under timed conditions.

Quant · ML

The statistics they really test

Work through distributions, expectation, and Bayesian reasoning used across quant and ML interviews.

Your standing

Know you’re ready before the room

Use submission history and pattern progress to decide what to revisit before interview day.

Features

Everything you need to succeed

A comprehensive platform designed for modern engineers to master coding interviews.

VisualizationsCore

Algorithm Visualizations

Watch algorithms come to life with interactive visualizations. Understand sorting, searching, trees, and graphs step by step.

AI hints

AI-Powered Hints

Get intelligent hints when you're stuck. Our AI assistant guides you without giving away the solution.

Multi-language

Multi-Language Support

Write code in Python, JavaScript, TypeScript, Java, C++, Go, Rust, and more with full syntax highlighting.

Mock interviewsCore

Mock Interviews

Practice with realistic interview simulations. Get timed challenges and performance feedback.

Learning paths

Learning Paths

Follow structured paths for DSA, system design, and company-specific preparation. Track your progress.

Analytics

Detailed Analytics

Track your performance with charts, streaks, and skill breakdowns. Know exactly where to improve.

Algorithm visualizations

See algorithms come alive

Explore interactive visualizations for supported algorithms. Step through sorting, trees, graph traversal, and dynamic programming alongside the practice workspace.

  • Binary Search Trees
  • Sorting Algorithms
  • Graph Traversals
  • Dynamic Programming
Try visualizations
quick_sort — step 5 / 9
Voice-first practice

Learn by talking, not just typing

Practice explaining your approach out loud, review structured walkthroughs, and rehearse the follow-up questions that make interviews feel different from solo coding.

Preview the workflow here, then open the real product surface to try it.

Try a practice problem

In-browser practice · transcript-based review

Voice AI TutorTalk through problems like a real interview

A Socratic AI tutor that listens to your approach, asks guiding questions, and helps you discover solutions — all through natural voice conversation. No typing needed.

  • Socratic method — guides, never gives answers
  • Real-time voice input and response
  • Adapts to your skill level
  • Simulates real interview dynamics
Open the practice workspace
AI Video WalkthroughsStructured explanations when you need a walkthrough

Walkthroughs organize the approach, code, and complexity analysis into a sequence you can revisit without losing your place in the problem.

  • Chapter markers: Approach → Code → Complexity
  • Problem context stays alongside the explanation
  • Available on supported problem walkthroughs
  • Adjustable playback speed
Browse supported walkthroughs
Voice Mock InterviewsPractice phone screens with an AI interviewer

A realistic phone screen simulator where an AI interviewer asks follow-up questions, challenges your assumptions, and scores your communication — all via voice.

  • Realistic AI interviewer personality
  • Communication and technical scoring
  • Follow-up questions and edge-case probing
  • Detailed feedback and transcript
Open mock interviews
Create a free accountBrowse practice problems

Start with a free problem. Upgrade only when you need the full plan.

Learning path

Your path to interview success

Follow our structured roadmap from fundamentals to advanced topics. Track your progress every step of the way.

Choose a learning roadmap
View all learning paths
Product walkthrough

See the practice flow

Move from the prompt to executable feedback in one workspace, then use targeted hints when you need a nudge.

  • Step-by-step algorithm visualizations
  • AI hints that guide without spoiling
  • Real-time code execution feedback
  • Mock interview simulations
Practice workspace

Two Sum

Find the matching pair

Easy
def two_sum(nums, target):
    seen = {}
    for index, value in enumerate(nums):
        complement = target - value
        if complement in seen:
            return [seen[complement], index]
        seen[value] = index
    return []
Returns the matching indices

From prompt to feedback

  1. 1. Understand the promptConstraints and examples stay beside the editor.
  2. 2. Run sample testsSee output before submitting against hidden cases.
  3. 3. Ask for a targeted hintGet a nudge without revealing the full solution.
  4. 4. Submit and reviewUse test feedback to make the next attempt focused.
Open a real problem

CONNECTED PRACTICE

One preparation loop. No tab-hopping.

See how the workspace turns a practice session or an interview goal into a clear next step.

Choose a preparation workflow
Start with a real challenge before checkout

Upgrade only when you want the complete plan and premium workflow.

Try a free challengeStart $1 trial

PRICING

Simple, transparent pricing

Try a real challenge free. When you are ready for the full system, start with seven days of Pro for $1.

Start with seven days of Pro for $1.

Full access, then choose the plan that fits your preparation window.

Start the trial
MOST POPULAR

Pro

For serious interview prep

$199/year
Save 53%
  • A curated, growing library of real interview problems
  • All learning paths
  • Interactive algorithm visualizations
  • Unlimited AI-powered hints
  • Mock interview practice
  • Company tags (Google, Meta, etc.)
  • All 13 languages supported
  • Certificate of completion
Choose Pro
BEST ROI

Lifetime

One payment, unlimited access forever

$399one-time
  • Everything in Pro, permanently
  • Entire problem library
  • All learning paths
  • Interactive algorithm visualizations
  • Unlimited AI-powered hints
  • Mock interview practice
  • Completion certificates
  • One payment with no renewal
Get lifetime access

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FAQ

Frequently Asked Questions

Everything you need to know about AlgoCracked.

01How is AlgoCracked different from LeetCode?

AlgoCracked combines coding practice with interactive algorithm visualizations, contextual AI hints, structured learning paths, and timed mock interviews. The goal is to help you understand patterns, apply them in the editor, and review what to revisit next.

02Is there a trial or risk-free way to start?

Yes — our $1 trial gives you full Pro access for 7 days as a one-time purchase. It does not auto-renew or enroll you into a paid plan. Prefer to commit upfront? Pro plans also come with a 14-day money-back guarantee.

03What programming languages are supported?

We support 13+ languages including Python, JavaScript, TypeScript, Java, C++, C, C#, Go, Rust, Ruby, PHP, Swift, and Kotlin. Our Monaco-powered editor provides full syntax highlighting, auto-completion, and language-specific templates.

04How do the AI-powered hints work?

Our AI analyzes your code and provides contextual hints that guide you toward the solution without giving it away. It identifies where you're stuck, suggests relevant concepts, and helps you build problem-solving intuition rather than just memorizing solutions.

05Can I prepare for specific companies?

Yes. Use company tags and focused learning paths to narrow the catalog to the interview areas you want to practice. Company names identify practice categories and do not imply endorsement or affiliation.

06How do mock interviews work?

Our mock interviews simulate real technical interviews with timed sessions, realistic problems, and comprehensive feedback. You can choose company-specific formats, difficulty levels, and even practice with AI interviewers that ask follow-up questions.

07Do you offer refunds?

Yes. Contact support within 14 days of your initial Pro purchase for a full refund.

08Can I use AlgoCracked on mobile?

Yes! AlgoCracked is fully responsive and works on tablets and mobile devices. While we recommend using a desktop for the full coding experience, you can review problems, watch visualizations, and study on the go.

Still have questions? Contact support

Ready to ace your interview?

Start with a single problem, climb the Ladder, and let AI review every submission.

Start $1 trial — full access for 7 daysTry a problem free

One-time $1 trial • No auto-renewal • 14-day guarantee on Pro plans