# AlgoZilla > AlgoZilla is a native macOS app for coding interview preparation, visual algorithm learning, system design practice, mock interviews, and career preparation. [AlgoZilla landing page](https://www.algozilla.app/en) Practice coding interviews, visualize algorithms, and rehearse system design in one native Mac app. Build real understanding with offline coaching, then bring it to the interview. Requires macOS 14 or later. Core practice, lessons, hints, whiteboards, progress, and Offline Coach work offline. Optional remote AI requires consent and may incur provider charges. ## Availability [Download for Mac](https://apps.apple.com/us/app/algozilla/id6812899902) For macOS 14 and later ## How AlgoZilla works ### Find your starting point. Choose a role and a learning path. Follow clear prerequisites, or jump into a challenge that puts a specific skill to work. ### Understand by doing. Write code, run local tests, and watch the algorithm unfold. Use progressive hints to work through the hard parts at your pace. ### Practice saying it out loud. Explain your reasoning, defend the trade-offs, and rehearse follow-up questions. Bring your experience together in a tailored application. ## Coding practice Build a solution you can actually explain. Write real code, test your assumptions, and understand the trade-offs behind every approach. - JavaScript, TypeScript, Python & Java - Visible tests, hidden checks & progressive hints - Native editor, local autocomplete & flexible panes ## System design Turn open-ended prompts into clear architectural decisions. Map requirements, draw your system, and defend the choices that make it work. - Offline Excalidraw canvas with local history - Scale assumptions, deep dives & rubric feedback - Architecture fundamentals & AWS scenarios ## Mock interviews Practice thinking out loud, handling follow-ups, and finding your rhythm. Turn every session into a specific, useful next step. - Coding, behavioral, design & mixed formats - On-device voice recognition & spoken responses - Resumable sessions, transcripts & rubric reports ## Visual algorithm learning Slow an algorithm down. Follow the pointers. See what changes, and understand why. Then put that insight into practice. - Step-by-step visualizations with pseudocode - Structured paths with clear prerequisites - Worked examples, prediction practice & Big O - 280+ challenges & follow-up drills - 93 algorithm techniques to explore - 4 coding languages. Your choice. - 1 workspace for the whole journey ## Technical interview toolkit ### Patterns, not just problems. Learn algorithms through prerequisite-based paths, worked examples, four-part drills, and guided solutions. Algorithms · Study tracks ### A real frontend playground. Build with React, Vanilla DOM, and TypeScript. Multi-file editing, live previews, browser checks, and responsive viewports. React · TypeScript · DOM ### Data deserves practice, too. Work through SQL and NoSQL interview exercises, from joins and window functions to document pipelines and caching. SQL · NoSQL ### Think clearly at scale. Practice system design and AWS architecture with requirements, diagrams, scaling decisions, and explained trade-offs. System design · AWS ### Know your O(n) from O(log n). Build intuition in the Big O Lab with step-by-step derivations, operation counts, growth charts, and local answer checks. Big O Lab · Visual learning ### Give your experience a voice. Build a behavioral Story Bank, structure CARL answers, and rehearse with voice interviews and guided follow-up questions. Behavioral · Voice practice ### Find your next right step. Use role-aware recommendations, resumable study tracks, and evidence-based progress to focus on the skills that need you. Progress · Learning paths ### Make the workspace your own. Plan on an offline whiteboard, practice test-driven development, save favorites, import challenges, and use native keyboard commands. Whiteboard · TDD · ⌘ shortcuts Also available to explore: Vue, Angular, and Svelte workspaces, currently in preview. ## A place for every part of getting better. Learn the foundations, practice the work, and rehearse the conversation. Explore each part of a preparation workspace designed to connect the dots. ## Language curricula Learn the language. Keep the understanding. Go deeper than syntax with dedicated JavaScript, TypeScript, and Java curricula. Build a mental model, trace an example, and apply it in a related challenge—all without needing an AI subscription. ### JavaScript, from the inside out 34 lessons connect fundamentals, scope, closures, asynchronous behavior, and the decisions behind reliable JavaScript. ### TypeScript that explains itself 18 lessons build from everyday types toward generics, narrowing, mapped types, and expressive API contracts. ### Java with practical depth 18 lessons cover the language, collections, object modeling, and patterns you can use in coding interviews. - Prerequisites - Worked examples - Four drills per lesson - Read aloud - Bookmarks ## Coding practice Write the solution. Understand every decision. Move from a blank editor to a solution you can defend. Practice easy, medium, and hard problems with local execution, visible tests, masked hidden checks, and feedback that helps you take the next step. ### Four languages. One focused workspace. Practice algorithms in JavaScript, TypeScript, Python, and Java with a native editor, local completion, diagnostics, and a persistent timer. ### Hints that leave the thinking to you Reveal progressively deeper guidance, then compare distinct approaches with correctness reasoning, complexity, and failure cases. ### Go beyond the first pass Work through edge cases, debugging, scaling, and interview-narration drills. Check your plan, tests, complexity, and explanation before moving on. - Arrays & strings - Trees & graphs - Dynamic programming - Search & sorting ## Frontend practice Practice the interface. And everything behind it. Build real components in a frontend workspace with multiple files, local builds, and a live preview. Explore the connection between code, state, behavior, and the person using your interface. ### React and Vanilla DOM Work through component behavior, DOM interaction, state, and accessible interfaces with purpose-built reference workspaces. ### A dedicated TypeScript type gym Practice tuple inference, conditional and mapped types, recursive structures, template literals, and discriminated unions with local type checks. ### See what your code actually does Use phone, tablet, and desktop previews alongside build diagnostics, browser console output, and visible and hidden checks. - React - Vanilla DOM - TypeScript - Vue / Angular / Svelte in preview ## SQL & NoSQL Learn the model. Write the right query. Pair dedicated SQL and NoSQL learning paths with a balanced set of 36 data-practice challenges. Understand how the data is shaped before deciding how to retrieve, aggregate, and explain it. ### SQL: from filters to analytical thinking 18 lessons and 18 challenges cover joins, grouping, NULL behavior, window functions, recursive queries, and deterministic pagination. ### NoSQL: think in access patterns 18 lessons and 18 challenges explore document modeling, aggregation pipelines, caching, time series, replication, and graph fan-out. ### Practice with useful feedback Inspect schema guidance, run visible checks, submit against masked checks, and compare three reviewed approaches. SQL runs locally; NoSQL uses a focused Mongo-style pipeline interpreter. - Schema guidance - Progressive hints - Query editor - Local feedback ## TDD & contracts Make the behavior clear. Keep the change safe. Explore testing as a design skill with dedicated TDD and contract-testing curricula, then put the ideas to work in the app’s test-driven practice workspace. ### Learn the red–green–refactor loop Six TDD lessons cover the first failing test, boundaries and partitions, refactoring, test doubles, and property-based and mutation testing. ### Understand the contract between services Six contract-testing lessons explore consumer-driven contracts, provider verification, schema evolution, event contracts, and delivery pipelines. ### Explain what the test protects Practice choosing useful cases, identifying design seams, and separating a behavioral guarantee from an implementation detail. - TDD practice - Boundary cases - Provider verification - Compatibility ## Engineering skills Think like the engineer you want to become. Build the judgment that sits around the code. Sixteen engineering-skills lessons connect technical decisions to reliability, security, accessibility, performance, and clear communication. ### Design for real operating conditions Study capacity, queues, backpressure, observability, SLOs, and incident response. Learn to ask what happens when assumptions stop holding. ### Make safer changes Explore threat modeling, authentication, API compatibility, risk-based testing, delivery strategies, rollback, and production-readiness reviews. ### Build for people and teams Practice keyboard and focus accessibility, performance investigation, code review, technical communication, and learning from incidents. - Reliability - Security - Accessibility - Performance - Communication ## System design From a vague prompt to a design you can defend. Build architectural intuition with 35 system-design lessons and 55 original design prompts. Turn requirements and scale assumptions into a coherent system, then explain what you chose and why. ### Learn the building blocks Explore routing, APIs, caching, replication, consistency, queues, observability, security, CDNs, and patterns for resilient systems. ### Practice a complete design interview Clarify requirements, sketch in Excalidraw, explore bottlenecks, and rehearse follow-up questions for easy through hard scenarios. ### Review the reasoning behind the drawing Get deterministic offline rubric feedback, revisit checkpoints, and reveal staged solutions covering scope, interfaces, architecture, deep dives, and trade-offs. - 35 lessons - 55 design prompts - Offline whiteboard - Rubric feedback ## AWS architecture Learn the services. Design the system. Connect cloud fundamentals to architecture with 52 AWS learning lessons and a dedicated AWS design-practice area. Build a vocabulary for choosing services, explaining boundaries, and handling failure. ### Understand what each building block solves Study networking, identity, compute, storage, databases, messaging, observability, backups, and disaster recovery. ### Apply the knowledge to a scenario Move from service selection to read-heavy, write-heavy, asynchronous, and collaborative architectures with explained design choices. ### Learn through the diagram Follow managed architecture visualizations and use AWS-aware design exercises to connect service responsibilities with system requirements. - VPC & IAM - Compute & storage - Queues & events - Resilience & recovery ## Big O Lab Don’t just name the Big O. Show how you got there. Build an intuition for time and space with 38 searchable Big O exercises. Work through loops, recursion, data structures, trees, graphs, and amortized analysis with a clear derivation at every step. ### Reason before revealing Write your time and space estimates, explain the reasoning, and check equivalent notation locally. Progressive hints help when you get stuck. ### See the cost grow After checking an answer, explore operation-by-operation walkthroughs and growth comparisons that connect the notation to the work being done. ### Practice the interview explanation Revisit saved attempts and learn to distinguish independent inputs, nested work, recursion depth, and auxiliary space. - Time & space - Operation counts - Growth charts - Local answer checks ## Behavioral preparation Find the story. Make the lesson clear. Prepare for the conversation around your work with 33 behavioral story sets. Explore what interviewers are asking, organize evidence from your experience, and practice a clear CARL response. ### Build your own Story Bank Capture examples of collaboration, conflict, ownership, influence, and learning. Keep the facts and evidence available for future practice. ### Understand the shape of an answer Use Context, Action, Result, and Learning to connect a situation to your choices and what changed because of them. ### Prepare for the next question Compare sample answers, review preparation tips and red flags, and work through follow-ups that probe your reasoning. - CARL structure - Story Bank - Leadership - Follow-up questions ## Mock & voice interviews Make saying it out loud part of the practice. Move from knowing an answer to communicating it. Rehearse with follow-up questions, continuous voice turns, local transcripts, and an evidence-linked report you can learn from. ### Practice the interview you’re preparing for Start with coding interviews in Free. Pro adds behavioral, system-design, and mixed formats for a broader rehearsal. ### Keep a natural rhythm Use on-device recognition and native spoken responses. Pause, continue, or finish a session while keeping control of your transcript. ### Turn the rehearsal into a next step Review the evidence behind rubric feedback, export your report, and return to the areas that need another attempt. Offline Coach works without a model. - Voice turns - Follow-ups - Local transcripts - Exportable feedback ## Tracks & progress A direction for today. A record of how you got here. Give your preparation a structure with resumable study tracks, prerequisite-aware learning, and role-aware recommendations. Keep the next useful step close, even when you’re returning after a break. ### Follow a connected path Move through learning and practice in an intentional order. The Complete Interview Patterns track connects 16 chapters, 32 lessons, and 97 core problems. ### Look at evidence, not a single score Review submissions, retries, hints, timing, complexity reasoning, communication, and recency in the context of your target role. ### Pick up where you left off Return to saved practice, revisit techniques, and focus on the skills that need attention across frontend, backend, mobile, or generalist preparation. - Study tracks - Role-aware guidance - Saved progress - Readiness checkpoints ## Whiteboards & tools Sketch it. Save it. Come back with a better idea. Good practice needs room for unfinished thinking. Keep your plan, code, notes, favorite challenges, and reusable material together in a workspace that lives on your Mac. ### A real offline planning canvas Use the bundled Excalidraw editor for shapes, arrows, free drawing, libraries, and open-format files. Local history gives you recovery checkpoints. ### A workspace that adapts to you Resize, reorder, and hide solve-room panes. Use native find, keyboard commands, timers, notes, and saved layouts to stay focused. ### Keep building your library Save favorites, search and filter content, and import challenge drafts through a review-and-validation workflow in Settings. - Excalidraw - Local history - Native shortcuts - Favorites & import ## Coaching & guidance A useful nudge. Your own breakthrough. Start with authored guidance and deterministic Offline Coach. When you want a model’s perspective, choose an available local provider or explicitly connect a supported remote service. ### Learn without an LLM Lessons, worked examples, progressive hints, visualizations, and readiness guidance are available offline. Understanding is the starting point. ### Get feedback in context Use tutoring, Teacher Mode, complexity coaching, and interview guidance to explore your reasoning. AI Solver and advanced reviews are part of Pro. ### Choose your provider and boundaries Eligible Macs can use Apple Foundation Models; Ollama offers another local option. OpenAI and Gemini require your key and consent, with provider usage billed separately. - Offline Coach - Teacher Mode - Optional local AI - Explicit remote consent ## AI & models Think with AI. Stay in control. Get a second perspective on your code, your reasoning, or your next interview. Use AI on your Mac, connect a supported cloud provider with your own key, or keep practicing with Offline Coach. - Local AI options - Bring your own API key - No LLM mode available ### Useful guidance, even without a model. Offline Coach uses deterministic feedback. Lessons, authored hints, local tests, whiteboards, and progress remain available in No LLM mode—no AI subscription required. Automatic mode stays local. Apple first, then available Ollama. A cloud provider is always an explicit choice. ### Choose where the thinking happens. #### Apple Foundation Models Use Apple’s on-device model for AI assistance without connecting a cloud provider or adding an API key. - Requires macOS 26+ on an eligible Mac - Apple Intelligence must be enabled - The system model must be downloaded and ready #### Ollama Choose a model running on the same Mac. Install Ollama and a model separately, then refresh the model list in AlgoZilla. - Choose from your installed local models - Only local loopback server addresses are accepted - Connection checks and model refresh in AI & Models #### OpenAI & Gemini Connect either supported cloud provider with your own API key. Select a model and explicitly consent before sending learning context remotely. - An internet connection is required - Session-only keys by default; optional macOS Keychain - Remote usage is billed separately by your provider ### An extensible provider system. — Integration required AlgoZilla’s shared provider interface allows additional AI services to be integrated into the same learning workflows. Connecting another API requires a compatible provider integration. The current app settings support Apple Foundation Models, Ollama, OpenAI, and Gemini; there is no field for connecting an arbitrary API URL. ### A second perspective, across your preparation. #### Tutor & Teacher Mode Ask about the current challenge, unpack a concept, and explore your reasoning with contextual guidance. #### Complexity coaching Work through time and space complexity with a coach that can discuss the approach you are practicing. #### AI Solver Generate a reviewable solution and explanation, then inspect the result and its local test evidence. Available with Pro. #### Design & interview feedback Get an additional review of architectural decisions and behavioral answers alongside the app’s offline guidance. #### Challenge import Turn pasted challenge text into a draft, validate it, run generated sample tests, and save it to your local library. #### Resume & application assistance Explore suggestions using redacted, evidence-based context. Review proposed changes before applying them to your materials. AI Solver and advanced AI reviews require Pro. Model availability depends on your device or provider; remote usage charges are separate from AlgoZilla. ### One place to set things up. Open AI & Models in the app’s Settings to choose how you want to work. 1. **Choose a mode** — Pick automatic local selection, a specific supported provider, or No LLM. 2. **Connect and select** — Check local availability or add a remote key and consent. Refresh the available models and select one. 3. **Practice with context** — Return to your workflow for guidance. Offline Coach remains available when AI is unavailable. ## Resume and applications Bring your practice and your next move together. Build an evidence-backed resume, tailor it to the role, and keep every application organized. ### Resume studio Master and tailored resumes, local imports, 12 templates, and PDF, DOCX, and more. ### Applications, in order Jobs, cover letters, screening answers, follow-ups, and saved submission packets. ### Your story stays yours Version history, verified evidence, and optional AI suggestions you review before applying. ## Offline practice and optional AI Your learning shouldn’t depend on a connection—or another subscription. The core AlgoZilla experience works offline, with your work stored locally. ### Offline at the core Code execution, lessons, hints, diagrams, and progress work without a network or an LLM. ### AI is your choice Start with Offline Coach. Add Apple Foundation Models or Ollama locally, or opt into OpenAI or Gemini. ### You stay in control Remote AI needs your consent. API keys are session-only by default, with optional macOS Keychain storage. Apple Foundation Models requires an eligible Mac and supported macOS. Remote providers may charge for usage. ## Frequently asked questions ### What is AlgoZilla? AlgoZilla is a native macOS workspace for technical interview preparation. It brings coding practice, algorithm learning, system design, mock interviews, behavioral preparation, resumes, and applications into one app. ### Does it really work offline? Yes. Core coding practice, local tests, authored lessons, hints, visualizations, whiteboards, progress, and Offline Coach work without an internet connection. Remote AI providers and store purchases need a connection. ### Do I need an AI subscription? No. Offline Coach and the authored learning library work without an LLM. You can optionally configure a supported local model or connect OpenAI or Gemini with your own key and explicit consent. Remote usage may have provider charges. ### Which languages and frameworks can I practice? Algorithm practice supports JavaScript, TypeScript, Python, and Java. There are dedicated SQL and NoSQL exercises, plus frontend workspaces for Vanilla DOM, React, and TypeScript types. Vue, Angular, and Svelte are currently preview workspaces. ### Is it useful if I’m just getting started? Yes. Learner profiles and prerequisite-based tracks support beginners through senior engineers refreshing their skills. Worked examples, visual explanations, and progressive hints help you build understanding at your own pace. ### What’s the difference between Free and Pro? Free includes a sample of each curriculum with complete workflows for unlocked content, coding mock interviews, and limited career artifacts. The lifetime Pro upgrade unlocks the full library, all mock formats and templates, unlimited artifacts, AI Solver, and advanced AI reviews. The in-app store provides pricing when available. ### What Mac do I need? AlgoZilla targets macOS 14 or later. Packaged releases include the coding runtimes. Optional Apple Foundation Models needs an eligible Mac running a supported macOS version; other coaching modes remain available. ### Can I download AlgoZilla yet? Yes. Use the Download for Mac button in the section below to open the official download destination. AlgoZilla requires macOS 14 or later.