Technical and Case Interviews

🔄 Quick Recall: In the last lesson, you prepared for tough behavioral questions — weaknesses, failures, gaps, and salary. Now let’s tackle the other major interview category: technical and case-based assessments.

Two Types of Structured Interviews

Technical interviews test your domain knowledge — coding, system design, data analysis, or domain-specific expertise.

Case interviews test your problem-solving process — market sizing, business strategy, operational challenges, or scenario analysis.

Both reward structured thinking over raw knowledge. And both can be dramatically improved with AI-assisted practice.

Technical Interview Preparation

Understanding the Format

I'm preparing for a technical interview at [company] for [role].

Based on this role and company, what technical interview formats should I expect?
1. What topics are most likely to be covered?
2. What difficulty level should I prepare for?
3. What tools or platforms might they use (whiteboard, HackerRank, take-home)?
4. What's the typical time allocation?
5. Suggest a 1-week preparation plan targeting these specific areas

Practice Problem Pattern

For each topic area, follow this cycle:

Step 1: AI explains the concept

Explain [technical concept] for an interview context:
1. Core concepts I must understand
2. Common interview questions about this topic
3. Typical mistakes candidates make
4. One example problem with walkthrough

Step 2: You solve independently

Close AI, attempt the problem on your own. Time yourself. Write out your thought process.

Step 3: AI reviews your solution

Here's my solution to [problem]:
[paste your solution and reasoning]

Review this as a technical interviewer:
1. Is the approach correct?
2. What's the time and space complexity?
3. What edge cases did I miss?
4. What's a cleaner or more efficient approach?
5. What follow-up questions would you ask?

✅ Quick Check: Why is Step 2 (solving independently) essential, not optional?

Because interview performance depends on retrieval — pulling solutions from your own understanding, not recognition. Reading AI solutions feels like understanding, but it’s passive learning. Struggling through a problem yourself, making mistakes, and debugging your thinking builds the active problem-solving skills that work under pressure. The discomfort of getting stuck is where learning happens.

System Design Interviews

For senior roles, system design tests your ability to architect solutions:

Act as a system design interviewer. Ask me to design [type of system]:
- Start with the question
- Let me ask clarifying questions
- Let me propose my design
- Then probe: What happens when traffic increases 10x? How do you handle failures? Where are the bottlenecks?

After my design, give feedback on:
1. Scalability considerations I missed
2. Trade-offs I should have discussed
3. How my design compares to typical good answers

Case Interview Preparation

The Structured Approach

Case interviews follow a predictable flow:

1. Listen and clarify — Restate the question, ask for any missing information
2. Structure the problem — Break it into 3-5 components
3. Analyze each component — Work through the data systematically
4. Synthesize — Pull your analysis together
5. Recommend — State your recommendation with supporting evidence

Practice with AI

Give me a case interview question appropriate for [role/industry].

Rules:
1. Present the case with initial data
2. Let me ask clarifying questions (answer them)
3. Let me propose my structure before diving in
4. Provide additional data when I ask for it
5. After I give my recommendation, evaluate:
   - Was my structure logical?
   - Did I ask the right clarifying questions?
   - Was my analysis sound?
   - Was my recommendation well-supported?
   - What did I miss?

Common Case Types

Generate 3 practice cases for each type:
1. Market sizing (e.g., "How many piano tuners are in Chicago?")
2. Profitability (e.g., "Profits are declining at a restaurant chain — why?")
3. Market entry (e.g., "Should this company enter the Indian market?")

For each, give me the question, then wait for my answer before providing analysis.

✅ Quick Check: In a market sizing question, why is showing your approach more important than getting the exact right number?

Because nobody expects you to know how many piano tuners are in Chicago. They want to see if you can break an ambiguous problem into logical components: population of Chicago → households → percentage with pianos → tuning frequency → hours per tuning → tuners needed. A candidate who structures clearly and gets an estimate within 2x of reality scores higher than one who guesses correctly without showing work.

Exercise: Run a Practice Session

Choose one that matches your upcoming interview:

1. Technical: Have AI give you 3 practice problems in your domain. Solve each independently, then review with AI
2. Case: Run 2 full case interviews with AI as the interviewer. Get feedback on structure and analysis
3. System design: Design one system end-to-end with AI probing your choices

Key Takeaways

• Think aloud during technical and case interviews — interviewers evaluate your reasoning process, not just the final answer
• Use the three-step practice cycle: AI explains → you solve independently → AI reviews your solution
• Structure is your competitive advantage in case interviews: clarify → framework → analyze → synthesize → recommend
• System design interviews require discussing trade-offs, scalability, and failure modes — not just drawing diagrams
• Independent problem-solving (without AI) during practice builds the retrieval skills you need under pressure
• Market sizing questions test structured thinking — showing your approach matters more than the exact number

Up Next: In the next lesson, you’ll master salary negotiation and offer evaluation — the final stage where preparation directly translates to money.