Practice the work you will do on the job
17 labs put you in real work situations. An AI reviewer watches how you solve a problem, not only what you submit. Read an unfamiliar codebase. Find the cause of a live incident. Defend a design. Learn where your thinking failed while you can still correct it.
Prove you can solve it, then explain it
AI Coding Lab
4.7You work on a real codebase with AI, the way engineers work now. Four phases: understand the code, fix a broken feature, build a new one, and make it faster.
- How well you read code you did not write
- Your fix, your feature, your speed-up
- The reasoning you write at each step
DSA Coding Lab
4.6You solve a DSA problem in the editor. Your code runs against the test cases set for that problem, and you see every pass and every failure.
Probing Interviews Lab
4.5You solved the problem. Now explain it. An AI interviewer reads your code, then asks four or five questions: why this approach, why this algorithm & more.
See how you would work on a real codebase with AI
Query real data, not a screenshot of it
SQL Coding Lab
4.6You write a query against a real database. It runs on the data, and your rows are compared with the correct rows.
- The exact result set, row by row
- Query cost on large tables
- Correct joins and grouping
SQL Coaching Lab
4.7Your query failed. Instead of showing you the answer, an AI interviewer coaches you to the correct query, one question at a time.
See a query checked against a live database
Design it, draw it, then defend it
Schema Design Lab
4.5You write the schema for a product in a text editor. AI reads it and marks the keys, the relations, and the parts that will not scale.
Class Diagrams Lab
4.6You define the class structure for the product you want to build. AI reads the diagram and tests it against the behaviour the product needs.
LLD Coding Lab
4.7You design a system the way an interviewer asks for it. Aria, the AI interviewer, takes you through requirements, then entities, then code. A simulator shows you the problem before you start.
- Your functional and non-functional requirements
- Your entity design and the relations between them
- The code you write against your own design
HLD & LLD Interviews Lab
4.6A full design interview, run by AI. You take it at high level or low level, and it lands in your assignment list like any other task.
Design a parking lot, then defend it to Aria
Show your working, not just your answer
Business Case Studies Lab
4.6You solve the case in a Python or SQL notebook on the platform. The work moves in stages, and you get feedback at the end of each stage, not after you finish. An AI companion reads your notebook while you work.
- Your method at every stage, not only the answer
- Your queries, your code, and your charts
- Your findings against the case rubric
Tableau Workbooks Lab
4.5You build a Tableau workbook. AI reads your dashboards and tells you whether they answer the business question.
Find out if your dashboard answers the question.
ML Coding Lab
4.6You write Python with NumPy, pandas, and the usual machine learning libraries. Your code runs against set test cases.
Learn how your code holds up on every test case.
See what the feedback says about your method
Run the system. Break it. Fix it.
Linux Lab
4.7A real Linux terminal in your browser. It ships with templates for Docker, Kubernetes, AWS, Terraform, and Grafana, and with Windows and Ubuntu desktops for security work.
- Whether the commands you run reach the goal
- Your configuration files, not only your commands
- How you recover a broken environment
See the lab a DevOps engineer works in every day.
Debug Simulator Lab
4.7You get a live system and a symptom, not a file marked broken. You read logs, metrics, and alarms across the load balancer, API, database, and queue until the evidence names the cause. Then you fix it and watch the system react.
- Triage, evidence discipline, and diagnostic reasoning
- Your written root cause analysis
- Whether your fix solves the problem or hides it
Find out how you work on a system that is failing.
Your own work, put under questioning
Project Interviews Lab
4.6You give us your GitHub repository. AI reads your project, then interviews you on it: the choices you made, the parts you would change, and how it would hold up at scale.
- Your design choices and your trade-offs
- How well you know your own code
- Your answers on scale, testing, and failure
Hear the questions your own project raises.