Ready Set Do

Learn relatably from high-agency individuals, from all walks of life — currently just a few steps ahead in your journey of choice.The only podcast where you learn from artists, sages, techies and children - and everyone in between.What makes the stories on Ready Set Do podcast real, relatable, and actually useful is that they aren't selling you lottery tickets they already won with.Instead, we show you the first few steps they took- so you can find your own way forward. No spoon-feeding, ever.New episodes every Wednesday.

Ready Set Do is a education podcast hosted by Naman Pandey, with 121 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Naman Pandey hosts Ready Set Do, a education show with 121 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #122

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

  Aug 12, 202638 min

  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

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  Episode #121

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

  Aug 7, 202616 min

  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

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  Episode #120

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

  Aug 5, 202636 min

  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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  Episode #119

  How to Get Attention Online: What a Magician Knows That Marketers Don't - w/ Jimi

  Jul 31, 20261 hour

  I asked Jimi Gibson how attention actually works. Ten minutes later he'd named a card I picked inside my own head — live, on camera. (I've rewatched the clip. Still can't explain it.) Here's the part that pays rent: that trick and a LinkedIn post that blows up run on the identical script. Jimi spent 16 years as a working magician before becoming the voice of Thrive Internet Marketing Agency, a 20-year-old shop whose work has landed in Forbes and Entrepreneur. Along the way, he studied 400 brands to figure out why some people get attention online and most don't. In this episode of Ready Set Do, he hands over the whole method. We start with the 3-phase "magic script" — connection, curiosity, conversion — and the brain chemistry firing at each step. An open loop hits different than a finished thought, and Jimi explains exactly why. He also names the reason most personal brands feel fake: they skip the first two phases and sprint straight to the close. (You know the guy. He pitches you the second you accept the connection request.) Then the tool I haven't stopped thinking about: the five finger framework. Promise, passion, villain, audience, thumbprint. Five questions, one hand, and suddenly you have a year of content ideas without staring at a blank screen. If you're building a personal brand in 2026 — or trying to grow on LinkedIn without cringing at your own posts — this is the closest thing to a copywriting cheat code I've heard on this show. We also get into AI content and the question everyone keeps asking: will AI replace writers? Jimi's answer is to build with the one thing AI structurally can't copy — your thumbprint — and it's far more useful than the usual hand-wringing. And if you're convinced you have nothing to say? His advice for aspiring creators starts smaller than you'd expect. Incremental steps. Read the room. Open a loop. Close it. Whether you're an early-career professional learning content marketing, a freelancer chasing content that converts, or someone who wants to understand how attention works before the algorithm shifts again — this one earns its runtime. If it helped, do two things: subscribe wherever you're listening, and send it to that one friend who's been "meaning to start posting" since 2023. More episodes at readysetdopodcast.com Timestamps: 00:00 — The Magician's Journey: From Stage to Strategy 05:49 — The Three Phases of Engagement 15:59 — The Art of Connection in Communication 17:32 — Exploring Feelings and Connections 19:04 — The Curiosity Phase: Reading the Room 20:10 — The Experience of Being Led 21:55 — Neurochemistry of Curiosity and Closure 26:34 — The Magic Script: Phases of Communication 30:09 — Creating Unique Content in the Age of AI 31:38 — The Five Finger Framework for Content Creation 38:44 — Building a Personal Brand Through Storytelling 42:12 — The Importance of Incremental Steps 57:31 — Encouragement for Aspiring Creators

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  Episode #118

  How to Become a Graphic Designer (Your Portfolio Doesn't Have to Be Real) - w/ Cynthia

  Jul 27, 202652 min

  Cynthia Wagner almost quit art in high school. Not because she lacked talent — because building a portfolio felt so intimidating she figured she'd rather not try. (If you've ever stared at a blank page and talked yourself right out of something you actually wanted, you already know the feeling.) She didn't quit. She got into a competitive design program, spent years doing brand and campaign work, and eventually opened her own studio at CynthiaWagner.co. This is the conversation about how to become a graphic designer that I wish someone had handed me when I was starting from zero. Cynthia breaks down how to break into design when you have nothing real to point to yet. And her portfolio advice is the part people need to hear: your portfolio doesn't have to be real to be good. Read that again. You can build a design portfolio around invented briefs and personal projects, and it still counts. That one idea kills the biggest excuse most people use to never start. We get practical too. She lays out how to build a design portfolio from scratch and how to land a first design job when your experience section is basically empty. Getting design clients before anyone knows your name? She's done it, and she tells you how. Then Cynthia flips the mic on me. In the back half she walks me through the exact "Find Your Why" questionnaire she uses with real clients — the one built on Simon Sinek's Golden Circle — and applies it live to my own business, no rehearsal. It got a little uncomfortable (which, apparently, is the point). Having someone pull your "why" out of you in real time is a different animal than reading about it in a book. We also get into visual communication design, brand design, and why good design quietly changes how people value your work, often before they've read a single word. If you're a beginner mapping your first move into design, or a working creative sharpening your freelance design path or eyeing a career change, this one is for you. New episodes land every week. Subscribe on YouTube, Spotify, or wherever you listen so the next one finds you — and if this helped, send it to the friend who keeps saying they'll start "once their portfolio is ready." More at readysetdopodcast.com How to Become a Graphic Designer (Your Portfolio Doesn't Have to Be Real) Chapters: 00:00 — Journey into Art and Design 03:57 — Navigating Art School and Graphic Design09:56 — First Steps into the Professional World 13:12 — Building a Portfolio and Finding Clients 16:07 — Insights and Wisdom for Aspiring Designers 19:40 — Setting the Stage for the Conversation25:30 — The Importance of Authenticity in Branding 30:49 — Understanding the Podcasting Landscape 36:14 — Navigating the Challenges of Content Creation40:11 — The Beauty of Podcasting42:05 — The Role of Discomfort in Growth 43:59 — Understanding High Agency49:04 — The Value of Design in Perception 54:06 — The Impact of Design on Value

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