Ready Set Do

Naman Pandey
  • 4.7 (3)
  • How To
  • Updated Weekly

A podcast about how successful people got unstuck. Each episode goes back to the moment they were stuck and walks through what they actually did to move. Their story is proof the door opens. What you do next is yours.

  1. 3h ago

    How to Get Hired for Microsoft AI Roles Without Applying in 2026 using Recruiter Inbound Playbook - w/ Shrey

    Shrey Shah never applied to Microsoft. Microsoft executives watched him give a talk on AI coding workflows, then reached out. Meta came knocking not long after, asking for something similar. Here's the part that stings a little: that wasn't luck. It traces back to a decision he made years earlier, when senior engineers around him said going all in on AI-assisted coding would hurt his career. He ignored them. He was building with agents before agent jobs existed, and using Cursor before most engineers could spell it. In this episode of Ready Set Do, Shrey — now Senior Software Engineer, AI at Microsoft — walks through how inbound offers actually happen in tech, and what he did to make himself findable. We get into the interview loop too. Four rounds, two technical, zero LeetCode. One problem was so big he had to keep solving it out loud while talking to his interviewer. He explains why that format tests something the standard algorithm grind never touches. Then the harder conversation starts. Shrey doesn't believe in resumes anymore. His argument: every resume is now tailored by the same AI tools, every application lands in the same ATS pile, and the traditional job application is finished. (If you're applying into silence right now, you already suspect he's right.) So what replaces it? Visibility. Posting what you learn. Forming your own point of view on what you read. Building a public track record long before you need one. He gets specific about what to build, what to post on LinkedIn as a software engineer, and how he never runs out of things to say. He also breaks down how meetup and conference speaking invitations actually arrive. Then the technical gut-check. Most engineers using AI tools can't explain the difference between a skill, a sub agent, a hook, a rule, and MCP — or when to reach for which. Shrey can, and he lays out the architecture in plain language. We close on his 2028 prediction. He doesn't think AI takes your job. He thinks roles merge, everyone carries more scope, and the new jobs created won't line up with the ones that vanish. Worth your 45 minutes if the job market has gone quiet on you. 🎧 Timestamps: 00:00 Cold Open: How He Got Hired at Microsoft Without Applying 02:10 Hired at Microsoft Without Applying — How Inbound Offers Happen 03:42 Microsoft AI Interview With No LeetCode: What They Test Instead 09:46 Forward-Compatible Software: Building Agents That Survive Model Updates 13:29 How to Get Recruiter Inbound in Tech 20:57 Are Resumes Dead? Why AI Broke Job Applications 23:44 Personal Branding for Engineers: Visibility Before You Need a Job 27:58 What to Post on LinkedIn as a Software Engineer 30:57 How to Get Invited to Speak at Tech Meetups and Conferences 34:08 Vibe Coding Mistakes Most AI Engineers Still Make 36:08 Skill vs Sub Agent vs MCP: AI Tool Architecture Explained 42:27 AI Job Loss 2028 Prediction: Roles Merging, Not Replaced Guest: Shrey Shah — Senior Software Engineer, AI at Microsofthttps://www.linkedin.com/in/shreyshahh/ Host: Naman Pandeyreadysetdopodcast.com Subscribe on YouTube and Spotify.

  2. Sep 5

    How to Start With AI When You've Already Decided It's Too Hard (13 Year Google Veteran POV) - w/ Aishwarya

    Thirteen years at Google. Trust and Safety in Hyderabad first, then the Bay Area, then most of the back half inside YouTube — finance, then analytics, then managing YouTube inventory and monetization. Then Aishwarya Raghavan quit. No job lined up. Two months later a friend referred her to a company she actually wanted. She didn't get it. That rejection landed right as the layoff headlines were peaking, and that's where this conversation starts. Most advice about the AI job market in 2026 is built to make you feel behind. Aishwarya's take goes the other way. She says a lot of postings that say "AI skills required" mean something far more basic than you'd guess. The people who never start are usually the ones who jumped straight to AI agents, decided it was too hard, and quit before level one. (If that's you, no judgment. It was most of us.) So she walks through four levels anyone can climb. Level one is small enough to feel silly: getting ChatGPT to stop sounding like a stranger. Custom GPTs come later. Agent orchestration comes after that. Is that really enough to get hired in AI? Her answer is more specific than yes. We also get into why she couldn't just move into AI work internally at Google, even with the badge and the tenure. How to read a job description and tell whether a company has actually thought about AI or is checking a box. And the interview skill she rates above every technical signal. Fair warning — it has more to do with storytelling than with reciting the STAR method at a hiring manager. Then there's the networking habit she regrets not building while she still had the Google email. Nobody tells you that your network has an expiration date. She's now a principal product manager at Arrivia, wiring AI into a travel business full of legacy systems. Different problem entirely from YouTube creator monetization, and she's candid about what transferred and what didn't. If you're a student, or a few years into your career and quietly worried the market already moved past you, start here. Chapters below. If this helped, subscribe on YouTube and Spotify. 🎧 00:00 - Aishwarya Raghavan on Leaving Google After 13 Years 04:12 - How AI Is Changing Big Tech and Product Management 07:14 - Product Manager Job Search Advice in a Tough Tech Market 10:09 - Product Interview Storytelling: How to Stand Out as a PM 13:24 - Why Product, Engineering, and Strategy Roles Are Blending 16:10 - Best AI Tools and Workflows for Product Managers 19:08 - AI Agents and Agent Orchestration: The Next PM Skill 22:03 - Job Search Lessons After Leaving Google 25:17 - Travel Tech and AI: Modernizing Legacy Product Workflows 30:45 - YouTube Monetization, Creator Tools, and AI Product Strategy 35:59 - Networking Without an Agenda for Big Tech Career Growth 40:23 - Final Advice for PMs Building Rare AI Skills

  3. Sep 2

    How to Decide if a US Masters Is Worth It in 2026 (Purdue MBA Director POV) - w/ Prof Dunford

    Should an international student still move to the US for a master's right now? That's the question sitting in thousands of inboxes and WhatsApp groups this admissions cycle. Not "which school," not "what score." Just: should I go at all? Naman put it to someone who has watched this play out for over two decades — and who has no reason to sell you the dream. Professor Benjamin Dunford taught leadership and management at Purdue's Mitch Daniels School of Business, where he was academic director over the full suite of Purdue MBA programs. He also taught in Kellogg's family business executive program, and most recently at the Indian School of Business in Mohali. His answer on the headwinds international students face in 2026 is more direct than you'd expect from someone inside the system. He names what's real. Then he tells you what actually still holds up. A big piece of it: work experience. Ben is blunt that it's the biggest differentiator in MBA admissions, and the thing most applicants under-invest in while they optimize everything else. Which brings us to the 4.0. If you're chasing a perfect GPA, he'd argue you might be playing it safe — picking the courses you'll win instead of the ones that will stretch you. (Yes, this is going to sting a little. Sit with it.) We also get into why so much leadership advice falls flat. The gap between the real and the ideal. Why change is a choice, not a command. "Compliance theater" — that thing where everyone nods in the meeting and disagrees in the hallway after. And how to influence people when you have zero authority over them. Ben's research on pairing accountability with forgiveness comes up too, including why CEOs get visibly uncomfortable the moment you say the word forgiveness in a boardroom. Then there's his work at ISB Mohali, teaching 20-something CEOs who inherited Indian family businesses. How do you honor your parents and still change the thing they built? He's watched a lot of people try. 🇮🇳 We close on where business education is headed as certificates and badges start pressuring traditional degrees, what AI is doing to how leadership gets taught, and the difference between advising and consulting. If you're a student, a recent grad, or early in your career and weighing a move abroad, this one is required listening. Timestamps: 00:00:00 - Professor Dunford on Purdue MBA Programs and Executive Leadership Education 00:03:59 - What Separates Elite MBA Students From Average Applicants? 00:06:12 - Perfectionism vs Excellence in Business School 00:07:45 - Should International Students Still Pursue a US Master's Degree? 00:11:59 - Why Students Should Stop Chasing a 4.0 GPA 00:17:09 - How AI Is Changing Leadership Education and Business Schools 00:20:02 - Will Certificates and Badges Replace Traditional Degrees? 00:23:42 - Best Advice for Early Career Leaders: Keep Going and Iterate 00:25:44 - Why Leadership Advice Feels Too Theoretical 00:28:40 - Change Is a Choice, Not a Command 00:29:38 - How to Influence Without Authority at Work 00:30:20 - Why Accountability Needs Forgiveness 00:34:26 - Teaching at ISB and Working With Young Family Business Leaders in India 00:38:53 - How Family Businesses Can Honor Tradition Through Innovation 00:43:32 - Consulting, Advising, and Why Human Problems Still Need Human Solutions Subscribe on YouTube and Spotify for new episodes.

  4. Aug 27

    How To Break Into Site Reliability Engineering on A F-1 Visa - w/ Sai Joshitha

    Somewhere it's 3 a.m. and a Kubernetes pod just quietly died. A guy in a different time zone taps his card for coffee and it works. He'll never know how close that was. Keeping him from finding out is Sai Joshitha's job. She's a Senior Site Reliability Engineer at Visa. Here's the part I care about for anyone sitting on an F-1 right now. SRE is one of the most underrated doors into the US tech market, and almost nobody in the international student group chats is talking about it. Everyone's fighting over the same software engineer postings. Meanwhile there's an entire discipline hiring for a completely different skill. Start with this: SRE interview loops have no LeetCode. None. Someone hands you a system that's on fire and watches how you think while it burns. Is that easier? Definitely not. It's just different, and it rewards people who like fixing things over people who ground through 300 array problems. Joshitha breaks down what the job actually is day to day — monitoring, deploying, automating, and hunting for root cause when dozens of connected systems start acting strange. Then we get to how she got there. She finished her MS at University of Michigan-Dearborn and walked into one of the ugliest markets in years, firing off 200+ applications a week before she changed the whole approach. What worked was fewer applications, aimed better, with the resume rewritten per role and real recruiter outreach instead of apply-and-pray. (We've all done apply-and-pray. It's a petri dish for burnout.) She also lays out the exact stack recruiters screen for. Kubernetes and Docker, one cloud learned end to end (not three learned halfway), observability tools like Grafana, Prometheus and Kibana, scripting for automation, plus the networking fundamentals holding all of it up. Her honest take? Knowing the tools matters way less than knowing how to solve a real problem with them. We close on where this is heading — how Visa is folding AI into on-call work for repetitive incidents, why she reads AI as a teammate instead of a replacement, and what she'd say to someone who wants a tech career but got scared off by coding-heavy roles. If you're a student, a recent grad, or someone quietly plotting a switch into reliability engineering, this is a plan you can start on Monday. 🙂 Connect with Sai Joshitha — https://www.linkedin.com/in/joshithak/ Chapters: 00:00:00 - Sai Joshitha on Becoming a Site Reliability Engineer at Visa 00:00:20 - What Does a Site Reliability Engineer Actually Do? 00:02:59 - What Happens During a Production Incident? 00:05:18 - How SREs Use Logs, Metrics, Alerts, and Monitoring 00:08:19 - How Sai Joshitha Discovered SRE and Cloud Infrastructure 00:10:23 - University of Michigan-Dearborn MS and Starting a US Tech Career 00:12:14 - How to Break Into SRE After a Computer Science Master's 00:13:37 - Applying to 200+ Jobs Per Week in a Tough Market 00:16:11 - SRE Job Strategy: Targeted Roles, Resumes, and Recruiter Outreach 00:19:52 - What Is the SRE Interview Process Like? 00:23:20 - Are SRE Interviews LeetCode-Heavy or Troubleshooting-Focused? 00:24:48 - Must-Have SRE Skills: Kubernetes, Cloud, Observability, and Scripting 00:28:43 - Why Troubleshooting Matters More Than Just Knowing Tools 00:31:41 - How AI Is Changing Site Reliability Engineering 00:36:09 - Best Advice for Future SREs: Networking, AI Tools, and Programming

  5. Aug 21

    How To Escape The Family Business Trap in 2026 & The Real Reason Your Brain Fears Success - w/ Abhinav

    Picture running a resort deep inside Jim Corbett National Park. Tigers on one side of the fence, guests on the other, and a family business you never actually applied for... That was Abhinav Jindal's twenties. The business did fine. He didn't. That gap — doing well on paper, feeling hollow off it — is where this episode of Ready Set Do lives. Abhinav is an empowerment coach and a certified master practitioner of NLP and MER®, plus the founder of Cydir. He got there sideways. A manifestation course in Delhi in 2019 that he only half believed at the time. (He admits the eye-rolling was real. He went back anyway.) Then 2022. He did emotional baggage work that he says reset his business and his marriage in the same stretch. Not a slow drift toward better. A hard reboot. So what happens when a second generation business owner stops running on his father's scoreboard? We get into why New Year's resolutions fail by the second week of January. Short version: your conscious mind writes the goal, your unconscious mind quietly vetoes it, and nobody told you there was a vote. Abhinav calls that unconscious programming. The stuff wired in before you turned seven, still humming in the background while you wonder why the gym membership went untouched again. Understanding the conscious vs unconscious mind split is the whole ballgame here, and he explains it without any woo. His four steps for making change stick: clear the emotional baggage, set goals your entire system agrees with, take purposeful action, then stay present on the path. That third one is where most people fold. We also dig into how to set goals that survive contact with your own limiting beliefs — a different exercise than writing a list in January and hoping. Then there's the client story that stuck with me. A guy who quit every job right before he was about to succeed. Not once. Every single time. Abhinav traces it back to one childhood moment, and watching him unpack it is the most useful stretch of the episode if you've ever sabotaged yourself and couldn't name the reason. We close on AI. Where AI coaching and therapy genuinely help people, and where they run out of road. His read is more generous than I expected, and more specific. 🙂 Call it manifestation for skeptics. Buy into it or roll your eyes at it — as a mindset coach and transformation coach, Abhinav still hands you a framework you can use, especially if you're mid career pivot and stuck between success without fulfillment and no clear next step. If you've been treating personal growth as a someday project, this one is a nudge. Finding fulfillment isn't a reward for hitting the number. Turns out it's the thing that makes hitting the number bearable. Connect with Abhinav: https://www.instagram.com/abhinavjindal.coach/Cydir: https://www.cydir.com/ Chapters: 00:00 - Introduction to Second Generation Entrepreneurs 06:04 - Understanding Fulfillment-Driven Success 11:06 - The Impact of Internal Programming 16:15 - Common Pitfalls in Business Ownership 21:14 - Abhinav's Personal Journey to Coaching 26:27 - The Concept of Manifestation 27:55 - Transformative Breakthrough Sessions 30:26 - The Importance of Goals and Action 32:08 - Skepticism and Openness to Change 34:04 - Qualities of an Effective Coach 35:51 - Unique Client Stories and Breakthroughs 40:29 - The Process of Unpacking Client Issues 43:22 - AI vs. Human Coaching 47:33 - Future Aspirations and Impact

  6. Aug 12

    How To Go From No Job Offer To Amazon's AGI Development Team In 18 Months - w/ Kunal

    Here's the description, formatted for RSS/Spotify (timestamps on their own lines with spacing so they don't collapse): Seven years ago, Kunal Mishra was a summer intern at DRDO, facing the choice every engineering student knows: take the safe campus placement, or bet on the harder thing. He bet on machine learning. 🎯 That bet ran through a master's in the USA at Northeastern University and dropped him into the 2024 job market with no return offer and no sponsorship. Tough for anyone. Harder for an international student. So he built something. A 30-million-parameter LLM from scratch, trained for about $50 when the same build can cost thousands. (Yes, fifty dollars.) That one project got him his first US job. Then it got him Amazon. Today Kunal works on Amazon's AGI post-training team, building the Amazon Nova frontier models. This episode is the machine learning engineer roadmap he wishes someone had handed him. We open with what AGI actually means inside a big tech lab. Not the sci-fi version — the working definition his team uses to ship. Then the practical calls. Why fundamentals still beat chasing trends. How he chose between an MS in CS and an MS in AI (and why the label mattered less than he thought). What breaking into ML really looked like with no H1B sponsorship locked in. The heart of it is the project. Kunal walks through how to build an LLM from scratch — the design choices and the cheap-compute tricks that kept it under fifty bucks. A real llm project beats a polished resume every time. Then Amazon. The full interview loop, unfiltered. 450 LeetCode problems logged. Two DSA rounds. Two system design rounds — real ml system design, not whiteboard theater. And the 40% nobody preps enough for: the behavioral, mapped straight to Amazon's leadership principles. Plus how to hold your nerve through the bar raiser interview. He also hands over his prep shelf: Chip Huyen's Designing Machine Learning Systems and AI Engineering, Maxime Labonne's LLM Engineer's Handbook, Sebastian Raschka's blog and books, Andrej Karpathy's llama2.c, Hacker News (Show HN), and NeetCode 150. If you're a student or early-career engineer trying to break into ML in a 2026 market that feels stacked against you, this is your FAANG interview prep and your career advice in one sitting. Especially if you're doing it on hard mode as an international student. Press play. Then subscribe to Ready Set Do wherever you listen → readysetdopodcast.com New episodes on AI careers and the unconventional routes into big tech land every week. Chapters: 00:00 - Kunal's Journey: From Intern to ML Engineer 04:17 - Understanding AGI: Definitions and Perspectives 07:24 - The Importance of Specialization in Machine Learning 10:23 - Navigating Higher Education: Choosing the Right Program 13:16 - Job Market Insights: Finding Your First Role 16:27 - Building Projects: The Key to Job Success 19:10 - Lessons from Building an LLM from Scratch 22:15 - The Amazon Opportunity: Interview Process and Preparation 25:14 - System Design and Behavioral Interviews at Amazon 28:21 - Resources for Aspiring ML Engineers 31:28 - The Bar Raiser Experience at Amazon 34:12 - Working on Frontier Models at Amazon 37:15 - Final Thoughts: Health and Gratitude

  7. Aug 8

    How To Write A Resume Big-Tech Recruiters Can't Ignore

    I still have the exact one-page PDF that got me shortlisted for a Program Manager role at Apple. No headshot. No skill bars pretending "80% Excel" means anything. And here's the part the chapters give away early: I didn't get the job. (We get into why at 13:15, and it's the most useful thirty seconds in here.) So this episode is me pulling that resume apart, line by line. Not "delete your photo" advice — the layer most people miss even when the basics are already right. Everything hangs on one test: so what? If a bullet can't answer it, the bullet is decoration. That one question is how to write a resume a busy reader actually finishes. We start with sections and the order they belong in, because a strong program manager resume in the wrong sequence still reads as junior. Then the overview — small, or gone. Most resume summary sections are throat-clearing, and I'll show you when to cut yours. Then the engine: power verbs. Swap "responsible for" for a verb that did something, and half your resume mistakes fix themselves. The bullet formula comes next, plus the objection I hear most — "I don't have numbers." You do. I'll show you how to quantify resume bullets when nobody handed you a clean metric. After that, the project section. Which projects earn a spot, and which ones quietly sink you. Not every job on the page deserves equal space, either. Skills, one page versus two, and the almost-right details that get a resume for tech jobs tossed before a human reads it — think ATS resume tips and the tiny formatting killers that trip the filter. I built this for two people at once. The fresh MS grad with an internship or two, and the person about five years in whose entry level resume has gone stiff from too many rewrites. If you're running a US job search from abroad — a resume for immigrants, that Indian-in-US-jobs situation — the sequencing matters even more. Grab the one-page template (both layouts) here: https://www.overleaf.com/read/fcyfsjfgjnrk#a71930 📄 Chapters 0:00 – The resume that got into Apple 0:30 – The one test that runs everything 1:45 – Sections + the order that matters 3:15 – The overview: small, or gone 4:45 – Power verbs are the engine 6:15 – The bullet formula (and "I don't have numbers") 8:00 – Projects: which ones, how to write them 10:00 – Not every job gets equal space 11:00 – Skills + the almost-right killers 12:30 – One page vs two, and the JD 13:15 – Why I didn't get the job 14:00 – Steal the template Drop your weakest bullet in the comments — the one you know is soft — and I'll rewrite a few myself. Newsletter → readysetdigest.substack.comMore → namanpandey.me

  8. Aug 6

    How to Build an AI Governance Career Without Writing Code ( Lawyer -> AI Architect POV) - w/ Aashita

    Aashita Jain's H-1B didn't get picked. She was on an L-1 visa at Informatica, working against a clock that wasn't hers to control. Most people in that spot panic and start mass-applying to any job that will sponsor them. She built an O-1 visa case instead, and turned herself into an AI governance architect. That's a job title most engineers have never heard of, and one that barely existed five years ago. This episode is about what happens when the standard visa route closes and you have to build your own door. We start with the stereotype: governance people as the ones who show up late and say no to everything. Aashita's version looks nothing like that. She sits with engineers, reads architecture diagrams, and figures out how a product survives regulators in the US, the EU, and India before it ships, not after. (If your mental image of a lawyer in tech is someone slowing down a sprint review, this will reset it.) Her path is not a straight line. Law school in India, then Infosys, then Ireland, then the US. Each stop added a different lens on how privacy law actually works on the ground versus how it gets taught in a classroom. We get into how she treats privacy as a product decision, not a checklist someone fills out at the end. Consent architecture, GDPR, the EU AI Act: these come up constantly in her work, but she talks about them the way an engineer talks about tradeoffs, not the way a textbook does. Then we get to the O-1. The extraordinary ability visa has a reputation for being reserved for Nobel laureates and Olympic athletes. Aashita breaks down the exact mindset shift that won her case: thought leadership over article count. Getting cited in one meaningful place beats publishing ten forgettable ones. That distinction was her whole immigration strategy. We also get into the IAPP, what a non-coding tech job actually looks like inside an AI company, and why AI governance jobs are quietly becoming one of the more durable AI policy careers out there. Not the flashiest path, but one where demand keeps climbing as AI regulation catches up to the technology. If you're an engineer curious about privacy engineering, a lawyer eyeing a pivot into tech law, or someone staring down an H1B not selected notice and wondering what an H1B alternative even looks like, this one's your blueprint. 🎯 Subscribe on YouTube and Spotify for more career pivot stories that don't follow the script. Timestamps: 00:00 — The Journey from Law to AI Governance 03:32 — Bridging Law and Technology 06:25 — Understanding Governance in AI 09:17 — The Role of Lawyers in Tech 12:09 — Real-World Examples of Governance Challenges 15:21 — Cultural Influences on AI Governance 18:30 — Career Pathways in AI Governance 21:10 — Navigating the O-1 Visa Process 24:16 — Contrasting Global Perspectives on AI Governance 27:14 — The Future of Privacy and AI Governance 30:11 — Advice for Aspiring Professionals in AI Governance

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Ratings & Reviews

4.7
out of 5
3 Ratings

About

A podcast about how successful people got unstuck. Each episode goes back to the moment they were stuck and walks through what they actually did to move. Their story is proof the door opens. What you do next is yours.

Information

  • Creator
    Naman Pandey
  • Years Active
    2024 - 2026
  • Episodes
    127
  • Rating
    Explicit
  • Copyright
    © Naman Pandey
  • Show Website
    Ready Set Do