Practice
Workplace simulations and interview practice. Optional beyond the weekday lessons; studios embed selected scenarios. Everything simulated is labelled.
- 100scenarios
- 25capabilities covered
- 62 hof simulated work
- 150interview questions
Scenarios by capability100
Production incident
Senior code review
Stakeholder simulation
Messy real-world data
ADR centre
Live coding and SQL
- SQL gym: rolling and same-weekday features with window functions30 min
- Python gym: entity-safe lag and rolling features in pandas30 min
- SQL gym: consecutive nearly-full streaks and why the first query lies35 min
- Python gym: turning cumulative booking curves into pickup in pandas35 min
- SQL gym: booking pace against the same weekday last year40 min
ML system design
Ambiguous business case
Verbal defense
Statistical traps
Ablations
Decision theory and value
Robustness and stress tests
Paper reproduction
RAG evaluation workbench
LLM failure lab
- Unsupported citations and broken JSON in a claims assistant35 min
- Injected instructions and a looping helpdesk agent40 min
- A claims summariser that never saw its last document35 min
- A refund assistant that paid twice, in the wrong unit35 min
- An oversized voucher late in a long baggage-claim conversation40 min
Multi-agent company
End-to-end lifecycle
Golden test set and regression
Hiring committee
AI cost–quality
Agents vs workflows
Teach-back and Socratic interviewer
Executive presentation
Research reading protocol
- Read a churn paper before believing its abstract35 min
- Read an agent benchmark paper before adopting its framework35 min
- Does long context make retrieval obsolete? Read the claim40 min
- A language-model judge that agrees with humans 85% of the time35 min
- LoRA matches full fine-tuning: how much can 400 invoices show?35 min
Interview gym159
- An experiment configured for a 50/50 split ends with 50,600 users in control and 49,400 in treatment. Treatment shows a significant +2% revenue lift. Do you trust it?senior10 min
- Revenue management introduced a new overbooking policy on 12 routes in March; the other 40 routes kept the old policy. Routes were chosen by managers, not at random.senior15 min
- A telecom company sends retention discounts to the 10% of customers with the highest churn-model scores.senior12 min
- A redesigned seat map lifts paid seat selection by 6% in week 1, 3% in week 2 and 2% in week 3. Separately, product complains that tests take too long.senior12 min
- A new in-app 'price alert' feature is rolled out in an A/B test: 50,000 users get access to the feature and 50,000 do not (hypothetical). Only 30% of users with access ever turn the feature on.senior12 min
- An airline launches a lounge-subscription marketing campaign in one city (Izmir) and cannot randomise users. There are 20 comparable cities that did not get it.senior15 min
- A pricing-page test randomised 40,000 users (20,000 per arm). The analyst compared revenue per session across about 160,000 sessions with a two-sample test and got p = 0.03.senior12 minin review
- You randomise 50/50 on whether users are offered a new "trip planner" flow. Only 30% of users in the treatment arm actually open it; control users cannot access it.senior12 minin review
- A new rebooking flow should cut support calls and must not increase flight cancellations through accidental self-service cancels. The cancellation rate in control is 2.0% (hypothetical).senior15 min