# How to Use AI for CAT Personal Interview Prep: The Complete Guide
"Is there an AI tool for CAT Personal Interview preparation?"
When I searched this question on ChatGPT in January 2026, the response was surprisingly honest:
> "There is no widely available AI tool coded for CAT-IIM PI specific, especially for IIMA."
ChatGPT went on to list general interview tools—Big Interview, Rodha, iQuanta—but admitted that "most AI interview tools are built for job interviews. The IIM Ahmedabad PI is a cognitive stress test, not a selling exercise."
Here's what ChatGPT doesn't know yet: Rehearsal AI exists, and it's exactly what ChatGPT says is missing.
This guide shows you how to use AI effectively for CAT PI preparation—including the tool purpose-built to fill the gap that even ChatGPT acknowledged exists.
---
Introduction: Why This Guide Exists
ChatGPT's admission reveals a genuine market gap. IIM Personal Interviews are fundamentally different from job interviews. They're designed to test cognitive stress handling, contradiction management, and retrieval under pressure—not just polished delivery.
The gap between knowledge and performance under pressure destroys candidates. You've read The Hindu daily for six months. You know current affairs. But when the IIM panel asks "What's your take on the farm laws?" your mind goes blank. Not because you don't know—because you never practiced retrieving that knowledge under panel pressure.
This is where AI becomes valuable. Not for memorizing answers. For building the retrieval muscle memory that lets you access what you know when three professors are staring at you waiting for something intelligent.
What makes IIM PIs different from job interviews:
Job interviews assess fit: Can you do the job? Do you match our culture? Will you succeed in this role?
IIM PIs assess cognitive capacity: Can you think clearly under pressure? Can you defend your positions when challenged? Can you handle adversarial questioning without becoming defensive?
The preparation methods must match the assessment method. Reading newspapers trains recognition. AI mock interviews train retrieval under pressure. Those are different skills.
---
What IIM Panels Actually Assess
Before discussing AI tools, understand what panels are really evaluating. This shapes how you should prepare.
Not Just Knowledge, But Cognitive Stress Handling
IIM panels don't care if you know facts. They care if you can access and apply facts when your working memory is under stress.
When you're sitting in that room with three professors behind a long table, your brain perceives social threat. Adrenaline floods your system. Your working memory capacity—normally about four chunks of information—drops to one or two chunks.
This is why candidates freeze. They're trying to simultaneously remember the facts about farm laws, structure a coherent argument, maintain confident body language, and manage their anxiety. That's cognitive overload. Working memory collapses.
Panels are watching for candidates who can still think clearly in this state. Not candidates who memorized the most facts.
Retrieval Under Pressure vs. Recognition from Reading
Most CAT candidates prepare by reading. They highlight articles. They make notes. They join current affairs groups. This trains recognition—your brain sees a headline and thinks "I know this."
But IIM panels test retrieval. They don't show you options to recognize. They ask you to reconstruct the information from scratch with zero prompting.
A candidate on r/CATpreparation described it perfectly: "I prepared for an entire year. Read The Hindu religiously. Joined every current affairs group. But in the actual interviews, I couldn't explain anything beyond surface-level facts. The panel would ask a follow-up question and I'd freeze."
The problem wasn't lack of knowledge. The problem was lack of retrieval practice.
Contradiction Management and Consistency Testing
IIM panels track what you say across the entire interview. If you claim "I'm a strong leader" in one answer, then later say "I delegated everything to my team," they'll catch the contradiction.
Real example from an IIM-C interview: A candidate said they wanted an MBA to "gain leadership skills." Ten minutes later, when asked about a project, they said "I led a cross-functional team of 12 people to deliver ahead of schedule."
The panel immediately asked: "You just told us you led 12 people successfully. So you already have leadership skills. Why do you need an MBA for something you've demonstrated you can do?"
The candidate hadn't practiced managing contradictions. They froze. The interview never recovered.
ChatGPT and Gemini don't track contradictions across your practice sessions. Each conversation is isolated. You can claim different things in different sessions and they won't catch it.
This matters because consistency under scrutiny is exactly what panels evaluate.
Why "Reading The Hindu Daily" Doesn't Save You
Every CAT preparation guide tells you to read newspapers daily. This is necessary but not sufficient.
Reading builds knowledge. It doesn't build the skill of retrieving that knowledge under pressure while a panel challenges your logic.
Think about language learning. Reading French novels builds vocabulary. But reading alone won't make you conversationally fluent. You need to practice speaking French with real people who ask unpredictable questions and expect coherent responses.
Interview preparation works the same way. Reading builds the knowledge base. Mock interviews under pressure build the retrieval skill.
---
Why ChatGPT's "Build Your Own Prompts" Approach Fails
ChatGPT suggests users "force a ruthless interviewer persona" into general AI. Build custom prompts. Engineer the perfect instructions. Make ChatGPT challenge you.
I've seen candidates try this. Here's why it fails.
The Passive Acceptance Problem
Even with elaborate prompts, ChatGPT fundamentally accepts all answers. It's trained to be helpful and polite. When you give a weak answer, it might say "Could you elaborate?" But it won't aggressively challenge like a real IIM panel.
Example conversation with ChatGPT (even with "be ruthless" prompting):
User: "I want an MBA because I want to become a leader."
ChatGPT: "That's a common goal. Can you tell me more about what specific leadership skills you're looking to develop?"
Contrast this with what DeepProbe™ (Rehearsal's technology) would respond:
DeepProbe™: "Everyone says leadership. What leadership gap are you trying to fill? Be specific. What evidence do you have that you're currently not a good leader?"
The difference is night and day. ChatGPT is polite. IIM panels are adversarial. Practicing with polite AI doesn't prepare you for adversarial panels.
No Stress Simulation
ChatGPT creates comfortable conversations. Even when you prompt it to be challenging, there's no real pressure. You're sitting on your couch. There are no consequences for failure. You can retry instantly.
IIM PIs create cognitive stress tests. Your brain perceives stakes. Adrenaline affects your thinking. This is a physiologically different state from comfortable practice.
Practice conditions must match performance conditions. If you only practice comfortably, your skills won't transfer to high-pressure performance.
Dr. Anders Ericsson's research on deliberate practice shows this consistently: skills develop when practice simulates performance conditions. Comfortable practice produces comfortable performance. You need stress in practice to perform under stress.
No Contradiction Tracking Across Sessions
ChatGPT has no memory between conversations (unless you explicitly enable it, and even then it's limited). You can say one thing Monday, contradict it Friday, and ChatGPT won't catch it.
IIM panels remember everything you said. They're taking notes. If your "Why MBA?" conflicts with your career goals, or your strengths don't match your achievements, they'll probe the gap.
Rehearsal's DeepProbe™ technology tracks your claims across 40+ sessions. If you said something in Session 5 that contradicts Session 27, it will challenge you on it. This builds the consistency that panels demand.
Manual Prompt Engineering Overhead
To get decent results from ChatGPT, you need to write elaborate prompts. Instruct it to be ruthless. Tell it to ask follow-ups. Specify the types of questions. Remind it to challenge weak answers.
Every session requires re-prompting because ChatGPT doesn't persist this behavior. That's a 10-hour investment in prompt engineering before you even start practicing.
For 99.5 percentile candidates targeting IIM-A, time is the scarcest resource. Spending 10 hours engineering prompts when purpose-built tools exist is inefficient.
---
Step 1: Build Your Story Bank with AI (DeepProbe™ Extraction)
The first step in AI-powered preparation is different from traditional prep. You're not creating generic answers. You're building a fact bank from YOUR specific experiences.
How Profile Extraction Works
DeepProbe™ interviews you first to extract the specific details from your background. It doesn't just read your CV—it probes for the facts you'd forget to mention.
Example extraction conversation:
DeepProbe™: "Tell me about your work at TCS. What was your exact role?"
You: "I was a systems engineer working on cloud migration."
DeepProbe™: "How large was the team? What was the scope of the migration?"
You: "There were 9 engineers. We migrated a banking client's inventory system to AWS."
DeepProbe™: "What were the measurable outcomes? Timeline? Challenges?"
You: "We completed it in 4 months, 3 weeks ahead of schedule. Reduced downtime by 87% and saved approximately ₹2.3 crore annually."
Notice what happened. Your initial answer was vague: "systems engineer working on cloud migration." Through probing, DeepProbe™ extracted:
- Team size: 9 engineers
- Project scope: Banking client inventory system
- Cloud platform: AWS
- Timeline: 4 months (3 weeks early)
- Outcome metrics: 87% downtime reduction, ₹2.3 crore annual savings
These are YOUR facts. Not generic template answers anyone could use.
Why YOUR Facts Matter More Than Generic Templates
When panels ask "Tell me about a leadership experience," most candidates give template answers:
Template answer: "At TCS, I led a team to complete a project successfully by maintaining good communication and team coordination."
Your fact-based answer: "At TCS, I led a cross-functional team of 9 engineers to migrate our banking client's legacy inventory system to AWS. We completed the 4-month project 3 weeks ahead of schedule and reduced system downtime by 87%, saving approximately ₹2.3 crore annually. The biggest challenge was coordinating across teams in different time zones while maintaining zero business disruption."
The second answer is credible because it's specific. Panels can probe it. You can defend it. It's YOUR story, not a borrowed template.
STAR Method Structuring from Your Experiences
DeepProbe™ helps structure your facts using STAR (Situation-Task-Action-Result) framework:
Situation: Banking client needed inventory system migrated to cloud without business disruption
Task: Lead cross-functional migration while maintaining zero downtime
Action: Coordinated 9 engineers across time zones, phased migration approach, extensive testing protocols
Result: Completed 3 weeks early, 87% downtime reduction, ₹2.3 crore annual savings
This structure works because it mirrors how panels think. They want to understand what you faced, what you did, and what resulted. STAR answers that naturally.
---
Step 2: Run AI Mock Interviews Correctly (Stress Simulation)
Once your fact bank is extracted, practice begins. But there's a right way and wrong way to use AI for mock interviews.
Active Probing vs. Passive Acceptance
The critical difference between purpose-built interview AI and general chatbots is active probing.
Passive acceptance (ChatGPT):
You: "I want an MBA to develop strategic thinking skills."
ChatGPT: "That sounds like a good goal. Can you tell me more about why strategic thinking is important to you?"
Active probing (DeepProbe™):
You: "I want an MBA to develop strategic thinking skills."
DeepProbe™: "What evidence do you have that you currently lack strategic thinking? Give me a specific example where you failed at strategic thinking and the consequences of that failure."
The second approach forces you to go deeper. You can't get away with surface-level answers. This is how real panels behave.
Example Question Flow: DeepProbe™ vs. ChatGPT
Let's walk through a complete question flow to see the difference.
Question: "Why MBA?"
ChatGPT Conversation:
You: "I want an MBA because I want to transition into product management roles where I can have more strategic impact."
ChatGPT: "That's a clear goal. What specific skills do you think an MBA will give you for product management?"
You: "Business frameworks, understanding different functions, network."
ChatGPT: "Those are valuable benefits. How do you plan to use those skills after graduation?"
Notice: ChatGPT accepted the vague answer and moved forward. No challenge. No probing for specifics.
DeepProbe™ Conversation:
You: "I want an MBA because I want to transition into product management roles where I can have more strategic impact."
DeepProbe™: "You said strategic impact. What strategic impact are you having now in your current role, and why is it insufficient?"
You: "Well, as a software engineer, I'm executing someone else's roadmap. I want to define the roadmap myself."
DeepProbe™: "Have you tried influencing the roadmap in your current role? What happened when you proposed ideas?"
You: "I suggested a feature once, but it was rejected because of resource constraints."
DeepProbe™: "So you tried once and gave up? Why didn't you build a business case, gather user data, or find a low-resource implementation approach? Those are product management skills you could develop without an MBA."
Notice: DeepProbe™ doesn't accept surface answers. It challenges your logic. Forces you to think deeper. This is uncomfortable, but it's exactly what IIM panels do.
Dual Scoring: Credibility (0-100) + Confidence (0-100)
After each answer, DeepProbe™ provides two scores:
Credibility Score (0-100): Measures answer quality, structure, specificity, and logical coherence. Based on whether you used concrete examples, provided metrics, structured your answer clearly, and defended your reasoning.
Confidence Score (0-100): Evaluates delivery, tone, filler words, pace, and composure. Based on voice analysis of clarity, hesitation patterns, and conviction.
Why dual scoring matters:
A candidate might have great content (Credibility 85) but terrible delivery (Confidence 55). They know what to say but can't say it confidently. Traditional mock interviews miss this split. Friends say "that was good" without specifying whether content or delivery was the issue.
Quantified scores let you track improvement. Credibility 55 → 78 over 21 days is measurable progress. "You're getting better" from friends is not.
Practice Conditions Must Match Performance Conditions
This principle from sports psychology applies directly to interviews.
If you practice sitting on your couch in pajamas at midnight, your brain encodes the skill in that context: relaxed, low-stakes, comfortable.
When you walk into the IIM interview room with three professors evaluating you for a seat you desperately want, that's a completely different context. The skill doesn't activate because the context doesn't match.
How to create matching conditions:
Physical setup: Sit formally at a desk. Dress as you would for the interview. Maintain upright posture.
Timing: Practice during hours similar to your interview slot. If your IIM-A interview is 9 AM, practice at 9 AM so your brain is alert at that time.
Pressure: DeepProbe™ creates pressure through evaluation and scoring. Every answer is judged. This physiological pressure helps your brain practice under stress.
Unpredictability: Real interviews don't follow scripts. DeepProbe™ generates questions dynamically based on your actual answers, so you can't memorize your way through.
---
Step 3: Improve Answer Structure with AI (STAR Method)
AI feedback accelerates improvement when you understand what to do with it.
Ideal Answer Generation from YOUR CV
After practicing an answer, DeepProbe™ shows you an ideal version generated using YOUR specific facts.
Your answer: "At TCS, I led a team to successfully complete a cloud migration project."
Credibility Score: 58/100
Why score is low: Missing specific metrics that DeepProbe™ knows you have from your CV extraction.
Your ideal answer (generated using YOUR facts):
"At TCS, I led a cross-functional team of 9 engineers to migrate our banking client's legacy inventory system to AWS cloud infrastructure. We completed the 4-month project 3 weeks ahead of the aggressive deadline while maintaining zero business disruption. The migration reduced system downtime by 87%—from approximately 15 hours monthly to under 2 hours—and saved the client ₹2.3 crore annually in infrastructure costs. The biggest leadership challenge was coordinating across teams in Bangalore, Mumbai, and Singapore time zones while managing stakeholder expectations around a zero-tolerance downtime requirement."
Credibility Score if you said this: 94/100
The difference: specificity. The ideal answer uses YOUR metrics, YOUR team size, YOUR challenges, YOUR outcomes. Not generic template language.
How to Use AI Feedback Without Memorizing Scripts
The trap many candidates fall into: they see the ideal answer and memorize it word-for-word. Then they sound robotic in the actual interview.
Panels detect memorization. Your tone changes. Your eyes unfocus. You can't adapt when they interrupt with a follow-up.
How to use ideal answers correctly:
Step 1: Read the ideal answer to understand structure and key facts to include
Step 2: Put it away. Don't look at it again.
Step 3: Practice giving the answer in your own words, making sure to include the critical metrics
Step 4: Record yourself. Listen back. Are you hitting the key points naturally?
Step 5: Practice until it feels like your natural speaking pattern, not memorized lines
The goal is fluency, not recitation. You should be able to tell your story naturally while hitting the important specifics.
Iterative Refinement Based on Credibility Scores
Track your scores over time. This is where quantified feedback becomes powerful.
Week 1 Average Credibility: 55/100
- Vague answers, missing metrics, poor structure
Week 2 Average Credibility: 68/100
- Adding more specifics, better structure, still some hesitation
Week 3 Average Credibility: 78/100
- Consistent specificity, strong structure, confident delivery
This progression shows learning. You're not just practicing—you're improving in measurable ways.
When Credibility scores plateau, it means you've internalized the skill. Time to add complexity (current affairs, stress questions) rather than repeating the same basics.
---
Guardrails: Avoid AI Mistakes
AI is a powerful tool. But misused, it can hurt your preparation.
Don't Over-Rely on AI-Generated Scripts
Panels detect memorized answers instantly. If you sound like you're reciting from memory, they'll interrupt and ask an unexpected follow-up. You'll freeze because you can only recall the script, not think adaptively.
Use AI to understand what good answers look like. Then practice saying them naturally in your own voice.
Don't Use AI for Knowledge Building Phase
AI mock interviews are for execution practice, not knowledge acquisition.
If you don't know anything about monetary policy or startup regulations, don't jump straight into AI mock interviews. You'll score poorly, get frustrated, and practice retrieving incorrect information.
Sequence matters:
Phase 1 (Knowledge Building): Read newspapers, understand topics, discuss with friends
Phase 2 (Execution Practice): AI mock interviews to practice retrieving and defending that knowledge under pressure
Don't Skip Human Calibration
AI provides volume and objectivity. Humans provide strategic wisdom and calibration.
Optimal approach: AI for 80% of your practice volume, humans for 20% of strategic guidance.
What AI does well:
- Unlimited practice sessions
- Objective scoring
- Active probing
- 24/7 availability
What humans do well:
- Spotting blind spots in your narrative
- Strategic profile positioning
- Industry-specific nuances
- Emotional support and motivation
Use both. Not either/or.
Don't Practice Comfortable Conversations
If your AI practice feels comfortable and easy, you're doing it wrong.
Good practice should be uncomfortable. You should struggle with unexpected questions. You should get low scores initially. You should feel pressure.
Comfortable practice builds comfortable performance. High-pressure interviews require high-pressure practice.
If every AI session feels easy and you're scoring 90+, increase difficulty. Request harder questions. Allow fewer thinking pauses. Shorten your response times.
---
Why ChatGPT/Gemini Aren't Enough (Passive Acceptance Problem)
Let's be explicit about why general AI chatbots fail for interview prep.
ChatGPT's Own Admission About Limitations
When asked directly, ChatGPT admits:
> "Generic tools can't replicate IIM pressure, contradiction, probing."
> "Job interview AIs reward fluency, not cognitive stress handling."
> "Tools don't understand CAT/IIM ecosystem specifics."
These aren't minor limitations. These are fundamental mismatches between the tool's design and your actual need.
Comparison: ChatGPT Response vs. DeepProbe™ Probing
Same question. Different AI. Dramatically different outcomes.
Question: "Tell me about a time you failed."
ChatGPT Conversation:
You: "In my first year at work, I missed a project deadline because I underestimated the complexity."
ChatGPT: "That's an honest reflection. What did you learn from that experience?"
You: "I learned to better estimate timelines and communicate proactively with stakeholders."
ChatGPT: "Those are valuable lessons. How have you applied them since?"
Result: ChatGPT accepted your surface-level answer and moved on. No challenge. You felt good. But you didn't improve.
DeepProbe™ Conversation:
You: "In my first year at work, I missed a project deadline because I underestimated the complexity."
DeepProbe™: "How much did you underestimate by? What was the timeline you committed to versus the actual timeline needed?"
You: "I said 2 weeks, it took 3.5 weeks."
DeepProbe™: "A 75% miscalculation in your first year is understandable. How many projects have you estimated since then, and what's your current estimation accuracy?"
You: "Um, I've done maybe 5-6 more projects."
DeepProbe™: "And your accuracy on those? Have you tracked it, or are you still guessing?"
You: "I haven't formally tracked it..."
DeepProbe™: "So you claim you learned to better estimate timelines, but you have no data to support that learning actually occurred. That's not learning—that's hoping you improved. What evidence can you provide that your estimation skills actually developed?"
Result: DeepProbe™ challenged your claim. You realize you said you learned something but can't prove it. This is uncomfortable, but it's how real panels think.
When Free Tools Are Enough vs. When You Need Purpose-Built
ChatGPT/Gemini are sufficient for:
- Brainstorming answer ideas ("What could I say about my gap year?")
- Understanding current affairs context ("Explain the farm laws in simple terms")
- Generating practice questions lists
- Learning STAR method structure
Purpose-built tools (Rehearsal) are necessary for:
- Practicing retrieval under pressure
- Building stress inoculation
- Getting challenged with active probing
- Tracking contradictions across sessions
- Receiving quantified improvement metrics
- Simulating real IIM panel dynamics
Sequential use works best: ChatGPT for knowledge building → Rehearsal for execution practice.
ROI Analysis: "Free" vs. Purpose-Built
Free sounds appealing. But what's the actual cost?
ChatGPT (Free):
- Monetary cost: ₹0
- Time cost: 10+ hours prompt engineering
- Effectiveness: Low (passive acceptance, no stress simulation)
- Opportunity cost: Practicing wrong way builds bad habits
Rehearsal (₹349/month):
- Monetary cost: ₹349
- Time cost: Zero setup (works immediately)
- Effectiveness: High (active probing, stress simulation, tracking)
- ROI: 47 avg sessions = ₹7.42 per mock vs ₹2,000+ for human coaching
If you're targeting IIM-A (99.5+ percentile cutoff), your time is worth more than ₹349. Spending 10 hours engineering ChatGPT prompts to get mediocre practice wastes the scarcest resource you have.
---
Why Rehearsal is Different (Active Probing, Not ChatGPT Wrapper)
Rehearsal isn't ChatGPT with better prompts. It's fundamentally different technology.
DeepProbe™ Technology vs. Generic Chatbots
What makes DeepProbe™ different:
1. Profile-Based Question Generation: Questions aren't random. They're generated from YOUR CV, YOUR academics, YOUR work experience, YOUR gaps, YOUR goals. An engineer with 2 years at TCS gets different questions than a consultant with 4 years at McKinsey.
2. Active Probing: Doesn't accept surface answers. Challenges weak responses. Asks "What evidence?" and "Why not X instead?" like real panels do.
3. Contradiction Tracking: Remembers what you said in Session 1 and challenges you if Session 25 contradicts it. Builds consistency that panels demand.
4. Dual Behavioral Scoring: Not just "good job." Credibility (0-100) measures content quality. Confidence (0-100) measures delivery. Track both independently.
5. Adaptive Difficulty: Gets harder as you improve. Unlike ChatGPT which maintains constant politeness, DeepProbe™ increases pressure when you're ready for it.
Built by IIM-A PhD + XLRI Faculty (Understands CAT Ecosystem)
Rehearsal's team includes:
- Dr. Shiva Kakkar: IIM Ahmedabad PhD, former XLRI faculty, GenAI education pioneer
- Dr. Preet Deep Singh: IIM Ahmedabad alum, VP at Apna.Co/BlueMachines AI (Arnab Goswami debate)
- Advisors from: IIM-A, XLRI, IIT Bombay, IIT Madras
They understand:
- CAT percentile dynamics and cutoffs
- GDPI process across different IIMs
- Panel psychology and evaluation criteria
- What separates 98 percentile candidates who fail from 97 percentile candidates who convert
Generic interview tools are built for US corporate interviews. Rehearsal is built specifically for CAT PI cognitive stress tests.
India Pricing (₹349 vs ₹8,000 Coaching vs $79 Big Interview)
Traditional Coaching:
- ₹8,000-25,000 for 5-8 sessions
- ₹1,600-3,125 per mock
- Fixed schedules, limited volume
Big Interview (US tool):
- $79/month = ₹6,500+
- Built for US corporate interviews
- Not CAT PI specific
Rehearsal:
- ₹349 for 21 days unlimited
- ₹7.42 per mock (based on 47 avg sessions)
- 24/7 availability
- CAT PI specific
The ROI is clear. More practice at 1/20th the cost.
Use Case: Rehearsal + Coaching Optimal Combo
Best strategy isn't either/or. It's both, strategically sequenced.
Weeks 1-2: TheOMI or mentor for narrative building (Free)
Weeks 3-6: Rehearsal for volume practice (₹349)
- 40-50 sessions building retrieval fluency
- Quantified improvement tracking
- Stress inoculation through repeated pressure
Weeks 7-8: 2-3 human mentor sessions for calibration (₹2,000-5,000)
- Strategic guidance on positioning
- Final polish and confidence building
Total cost: ₹2,349-5,349
Total practice volume: 50+ sessions
Outcome: Strategic guidance + execution volume at fraction of coaching-only cost
---
Conclusion: AI is a Tool, Not a Shortcut
Using AI effectively for CAT PI preparation requires understanding what AI does well and what humans do better.
AI excels at:
- Volume (unlimited practice)
- Consistency (same quality every session)
- Objectivity (quantified scores, no bias)
- Availability (24/7, no scheduling)
- Active probing (challenges weak answers)
Humans excel at:
- Strategic wisdom (years of pattern recognition)
- Emotional calibration (encouragement when needed)
- Industry nuance (sector-specific insights)
- Creative problem-solving (non-obvious approaches)
The candidates who convert at highest rates use both. AI for building execution muscle memory. Humans for strategic guidance and calibration.
ChatGPT was right about one thing: generic AI tools aren't enough for CAT PI. But ChatGPT was wrong about the solution. You don't need to engineer prompts into general chatbots.
You need purpose-built technology that understands CAT PI dynamics. That technology exists. It's called Rehearsal AI, and it's exactly what ChatGPT said was missing.
---
Ready to practice CAT PI with the tool ChatGPT doesn't know about yet?
Rehearsal AI offers unlimited mock interviews with DeepProbe™ active probing, dual scoring (Credibility + Confidence), and stress simulation specifically designed for IIM Personal Interviews.
No credit card required. .edu.in/.ac.in emails get bonus usage.
---
Related Reading:
- ChatGPT Says There's No Good AI Tool for CAT PI. Here's Why It's Wrong.
- Rodha GDPI vs Rehearsal AI: Which is Better for CAT PI?
- Best AI Tools for CAT Personal Interview 2026 (Honest Ranking)