Master real-world engineering through hands-on, high-stakes scenarios.

Engineering is more than just passing a coding interview. In the real world, you aren't asked to invert a binary tree on a whiteboard; you're asked to debug a production race condition, optimize a slow database query, or fix a broken CI/CD pipeline. We were tired of the "LeetCode vacuum" where problems are disconnected from actual infrastructure. We wanted a platform where the environment is as much a part of the challenge as the code itself.

real_work provides a marketplace of engineering "labs" that run inside fully isolated Docker containers. Unlike traditional platforms that only give you a text editor, real_work gives you a full Linux environment.

• Hands-on Labs: Solve challenges ranging from backend performance tuning to distributed systems debugging.
• Persistence: Progress is saved automatically. When you leave a workspace, your exact container state is committed to a local image, allowing you to resume exactly where you left off.
• Performance Benchmarking: Compare your solutions against "Gold Standard" implementations with built-in execution timing and correctness verification.
• Community-Driven: Anyone can publish a challenge by linking a GitHub repository. Users can rate, comment, and discuss strategies for every lab.

The platform is a modern full-stack application built with:

• Frontend: Next.js 15 (App Router) with TailwindCSS for a sleek, engineering-focused UI.
• Backend/Auth: Supabase for real-time database management, user authentication, and storage (thumbnails/avatars).
• Infrastructure: A custom Node.js/Docker orchestration layer that manages container lifecycles, port mapping, and state persistence using docker commit.
• Challenge Creator: A multi-step wizard that parses GitHub repositories, extracts function signatures, and allows authors to bake custom configurations into reusable Docker images.

• State Persistence: Moving beyond simple volume mounts to a robust docker commit workflow was difficult. We had to ensure that user progress was captured across sessions without bloating the local filesystem.
• Windows Compatibility: Navigating the differences between Docker on Windows (PowerShell/WSL) and Linux required careful path sanitization and permission handling (chmod in-container vs. Windows paths).
• Security: Running arbitrary user code is dangerous. We implemented multi-layered isolation to ensure that containers remain sandboxed and system-level access is restricted.

• The "Resume" Experience: Achieving a "VM-like" feel where you can close your browser, turn off your computer, and come back to the same terminal state.
• The Creator Wizard: Building a tool that can take a raw GitHub URL and transform it into a ready-to-solve engineering challenge in under a minute.
• Unified Thematic UI: Creating a cohesive design language that feels professional and "alive," using consistent animations and interactive feedback.

• Docker Internals: We gained deep knowledge of the Docker Engine API, specifically image layering, committing container diffs, and dynamic port allocation.
• Next.js Server Actions: Leveraging Server Actions for complex infrastructure tasks (like launching containers) allowed us to keep the client light while maintaining a high level of security.
• Context is King: We learned that learners engage more deeply when they are "solving a fire" in a realistic environment than when they are solving abstract mathematical puzzles.

• Multi-Container Labs: Supporting complex environments like "Debug this Kubernetes Cluster" or "Fix this Microservices Mesh."
• Leaderboards & Competitions: Real-time engineering sprints where the community competes to solve production incidents the fastest.
• Company Tracks: Helping companies build internal training labs that mirror their actual tech stacks.