Picture this: six years in IT security, based in Bangalore. Family 1,700 km away in Karnal. And the classic career trap: salary hike or relocation, pick one.
Take the better offer and the family stays distant. Move closer and the career stalls. The job market doesn’t care about your personal geometry. Most people grimace and choose.
Shivam ran a three-month AI experiment instead.
New job in Noida. Better pay. Family nearby. Both, somehow, at the same time.
Here’s what he actually did.
🎯 Why This Matters More Than Resume Polishing
The standard AI job-search tip is cosmetic. Fix your resume. Rephrase the bullet points. Write a cover letter in 30 seconds. Fine. But Shivam didn’t use AI as a writing assistant. He used it as a training environment.
That shift is the whole story. One approach makes your documents look better. The other changes how you actually perform when the stakes are real. Think of it like the difference between buying better running shoes and actually logging miles. The shoes might help. The miles are what get you across the finish line.
🛠️ The Three-Tool Setup
1. NotebookLM for role-specific intelligence extraction
Shivam loaded 150+ articles into NotebookLM and queried them with precision. The exact prompt he used: “Extract threat frameworks relevant to Azure cloud compliance from these sources.”
Compare that to “Summarize this.” The first gives you targeted, interview-ready intel. The second gives you a paragraph you already half-knew. The whole trick is specificity. Feed NotebookLM a focused question and it surfaces something actually useful. Feed it vagueness and it returns vagueness.
In practice, this meant he could walk into conversations about NIST CSF, MITRE ATT&CK mapping, and Azure Policy with real texture. Not buzzword familiarity. Actual depth, built by asking the right questions of the right sources over several weeks.
2. ChatGPT as the skeptical hiring manager
He told ChatGPT to roleplay as a skeptical hiring manager with something to prove. Not the encouraging coach. The one who follows up your answer with: “That’s interesting, but why should I believe you?”
That kind of pressure is hard to manufacture on your own. Most people practice answers in their heads, and their heads tend to be very agreeable audiences. The AI isn’t. It pokes at vague claims, asks for specifics, and circles back. After enough sessions like that, the real interview starts to feel like a review rather than an ambush.
The overlap with his actual interview questions was, by his account, significant. Pressure inoculation is real. Once you’ve had to defend your reasoning to an AI that won’t just agree with you, the stakes feel lower when a real human does the same thing.
3. Knowing exactly where NOT to use AI
In IT security, feeding sensitive data into public AI tools isn’t just careless. It’s a compliance violation. Shivam knew this and worked around it deliberately.
That judgment, knowing which workflows are safe and which create liability, is a skill in itself. It’s also exactly the kind of thing technical interviewers in regulated industries will probe for directly. Demonstrating that awareness doesn’t just signal competence. It signals trustworthiness, which is often the thing that actually breaks a tie between two otherwise equal candidates.
💡 Tips to Run This Yourself
- Start with NotebookLM and a focused prompt. Don’t summarize. Extract. Ask it role-specific questions against a curated set of sources. If you’re in cloud security, ask about specific compliance frameworks. If you’re in finance, ask about regulatory exposure. The more targeted the question, the more useful the output.
- Make the ChatGPT interviewer hard to satisfy. Tell it to challenge your reasoning, not confirm it. Comfortable practice sessions don’t prepare you for uncomfortable interviews.
- Map your compliance constraints first. If you work in a regulated field, know what data can go into public tools before you start. This protects you and becomes a natural talking point in interviews.
- Do this consistently over 90 days, not 90 minutes. Shivam’s results came from repeated sessions, not a weekend sprint. Three months of consistent practice compounds in a way that a single intensive weekend never will.
🚀 What to Try This Week
If AI hasn’t moved the needle on your job search yet, check what you’re actually using it for. Polishing documents is fine. But it’s table stakes. The real leverage is in using AI to train how you think and perform under pressure.
Pick one of these three tools. Run it with intent, not just curiosity. Give it 30 days and see what changes.
Shivam didn’t have to choose between the career he wanted and the life he wanted. He built a prep system that helped him earn both.
Used AI for 3 months. Got a salary hike AND moved closer to home. Here’s what actually worked.
by u/designbyshivam in PromptEngineering