Ready Set Do

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

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.

  1. 5d ago

    How to Turn LinkedIn Posts Into Career Opportunities - w/ Daniel

    Most people treat LinkedIn like a résumé site. Daniel Greenberg thinks that is exactly why they stay invisible. Daniel has racked up 8 million impressions on LinkedIn and co-hosts Connection Accepted, a show about communication and online influence. So when he says the feed now behaves more like TikTok than a digital CV, I paid attention. Here is the part nobody wants to hear: posting on LinkedIn feels awkward at first, and that awkwardness is the price of entry. Daniel walks through how he actually started, what kept him going, and why the first few posts matter less than the hundredth. We get into AI writing tools too. They make you faster, sure. But faster at producing forgettable content? Daniel and I both agree most AI-generated posts read like they were written by a polite robot trying to win an award (we have all scrolled past that guy). The bigger idea is that communication beats algorithm hacks. You can chase reach all day, but if your one message does not stick, the impressions do not turn into anything. Daniel breaks down how to make a single point land and how to test new formats without abandoning what you actually care about. Then there is the podcasting problem. These episodes eat hours. So how do you know the time is worth it? Daniel uses real listener feedback as the scoreboard, not vanity metrics, and he showed me how he turns raw podcast transcripts into LinkedIn content and search-friendly material that gets discovered through ChatGPT. The last stretch might be my favorite. Daniel explains how consistent content quietly creates warm leads, so opportunities come to you instead of you cold-pitching strangers and hoping. (Imagine that.) If you want to grow on LinkedIn, build a personal brand, sharpen your communication, or create career and business opportunities without begging for them, this one will shift how you see the platform in 2026. 🎯 Listen to the full episode of Ready Set Do with Naman Pandey. Guest: Daniel Greenberg, LinkedIn creator and co-host of Ideas.Host: Naman Pandey Timestamps: 00:00 LinkedIn: The Next TikTok? 04:59 How to Start Posting on LinkedIn 10:37 AI Writing Tools: Productivity vs Quality 15:01 Why Major Creators Are Moving to LinkedIn 20:08 Making One Message Stick 25:10 Experimenting With Formats Without Losing the Mission 30:15 Podcasting's Time-Investment Problem 35:17 Using Real Feedback to Measure Content 40:21 Turning Podcast Episodes Into LinkedIn Content 45:19 How Content Creates Warm Leads

    49 min

  2. May 25

    How to Turn a Civic Frustration Into a Viral Product (NammaKasa Bangalore Founder POV) - w/ Jyothish

    Picture this. You spend a few weekends building a small web app to track garbage piles in your city. You post about it once on LinkedIn. You go to sleep. You wake up to 250,000 users and your local government quietly using your tool to clean the streets. That's Jyothish's actual 2025. The app is Namma Kasa. It does one thing — lets Bangalore residents drop a pin on a map when they spot uncollected trash, then routes it to the people who can actually pick it up. No login walls, no gamification, no pretending it's a "platform." Just a map and a civic problem. Jyothish is a solo developer and indian product designer who shipped at version 0.1 instead of polishing for six months. The polish came after the users did (and yes, that order matters more than the build-in-public crowd lets on). The Bangalore garbage app went viral on LinkedIn with a 5-word hook. BBMP marshals started using it without a single pitch meeting. Investors slid into his DMs. He turned them all down. In this Ready Set Do conversation, Naman pulls apart how it actually went down — the exact LinkedIn post that broke it open, the mindset behind shipping an MVP in india before it feels ready, how civic technology gets adopted when nobody is forcing a partnership deck, and why he's anti-VC on principle for this one. If you've got a half-built side project sitting on your laptop right now (yes, that one), and you've been told you need a FAANG resume before anyone takes your work seriously — this is the one to play. Civic tech india doesn't need permission. It needs people who ship. ⏱ Chapters:00:00 The Viral Journey Begins03:30 Designing a Map-First Civic Reporting Journey06:40 The Mechanics of Reporting Garbage09:45 Going Viral, Hitting Limits, and Coming Back Online12:30 Accountability, Visibility, and Reaching Authorities15:01 Scaling and Future Plans18:54 Product Design Lessons for Civic Tech23:45 Shipping Imperfectly and Learning from Feedback28:30 Keeping Nammakasa Citizen-Led32:52 Building Ideas Without Overthinking the Outcome34:52 Final Reflections: Keep Experimenting and Keep Going Connect with Jyothish:LinkedIn: https://www.linkedin.com/in/jyothish-vm/Namma Kasa (Bangalore): nammakasa.in Subscribe for weekly conversations with people figuring out what careers and building actually look like in the AI era — career advice india 2026, indie hacker india stories, bootstrapped app journeys, and indian developer side projects worth paying attention to.

    38 min

  3. May 12

    How to Make $80K on Upwork (From a Top 3% Freelancer) - w/ Anas

    Two years ago, Anas lost his full-time UK job. He went back to Upwork — the platform he'd already used to make over $80K while studying — and within months landed an 18-month Swedish contract that generated over $5M in client revenue. His unfair advantage? A 60-second intro video that gets him hired in 24 hours. In this episode of Ready Set Do, I sit with Anas, a Top Rated Plus Upwork freelancer (roughly the top 3% on the platform), to walk through his exact playbook for freelancing on Upwork in 2026. We cover how to start freelancing on Upwork with zero reviews, how to write Upwork proposals that actually get opened, how to price freelance work across countries without underselling yourself, and how to escape the "Upwork is saturated" trap that keeps most beginners stuck. Anas is a Moroccan-born industrial engineer who pivoted into data science, freelanced his way through grad school in the UK, and rebuilt his income on Upwork after a layoff. So he's lived both sides — the broke student grinding for first reviews, and the senior freelancer competing against AI and offshore pricing. If you're trying to figure out how to get clients on Upwork, build a freelance data science career, or future-proof yourself against AI eating junior work — this is the full breakdown. A few things we get into: → The Upwork proposal mistake 90% of beginners make (and the niche-down fix)→ Why milestones beat hourly contracts on bigger projects→ How to filter bad clients before you ever get on a call→ The LinkedIn + YouTube combo that pre-sells you before the proposal lands→ Where Anas thinks "Chief AI Operator" roles are headed next Whether you're sending your first Upwork proposal this week or you've been freelancing for years and feel the AI pressure closing in, Anas gives you the tactical playbook and the bigger story behind it. (Quick heads-up: I learned more about freelance pricing in 25 minutes of this conversation than in any Upwork course I've seen.) Subscribe to Ready Set Do for more honest career conversations with people who've actually done it — international students, immigrant founders, freelancers, PMs, and engineers building unconventional paths into tech. 🔗 ABOUT ANASLinkedIn → https://www.linkedin.com/in/riadanas/YouTube → https://www.youtube.com/@UC2L6md1QyYAMRAoar_9ZFaw Ready Set Do podcast: readysetdopodcast.com Chapters: 00:00 The Biggest Misconception About Freelancing01:55 From Industrial Engineering to Data Science03:15 Saturation, AI Tools, and the Changing Job Market05:00 Starting on Upwork Before Feeling Fully Ready06:42 Niching Down and Writing Targeted Proposals09:47 Getting First Reviews and Building Social Proof11:01 Filtering Clients and Setting Clear Project Boundaries14:32 Milestones, Hourly Work, and Project Structure19:19 Pricing, Undercharging, and Negotiating Rates24:02 Re-Entering Upwork and Landing a Larger Client28:47 Building Trust with LinkedIn, YouTube, and Video Proof35:28 AI's Impact on Freelance Data Work and Future Roles38:13 AI Agents, Chief AI Operators, and Guardrails

    45 min

  4. May 9

    How To Get Hired For Agentic AI Big Tech Roles in 2026 (Amazon Sr Data Scientist POV) - w/ Surya

    Here's the uncomfortable thing nobody at career services will tell you: "I use Claude every day" stopped being a resume line about six months ago. The people hiring at Amazon, Google, and the frontier AI labs already assume you do. So what actually gets you hired in 2026? I sat down with Surya Kari, a Senior Generative AI Data Scientist at Amazon, to find out. Surya works on Amazon's white-glove GenAI team. His days are spent shipping with Fortune 500 customers and the frontier model labs you read about on Twitter. He's in the room when hiring decisions get made. And his honest read on early-career AI hiring is way more specific than the LinkedIn-thinkpiece version. We start with the thing I keep seeing destroy promising careers: using Claude (or any AI tool) like glorified autocomplete. Surya calls this the fastest way to plateau in your twenties. The fix isn't more tools — it's depth. The kind of moat that doesn't melt the next time a frontier model ships. Then we get into agents. Surya doesn't think agentic AI is actually production-ready yet (and yes, he works at Amazon, so he's seen the receipts). We talk about what's still broken, what the hype is missing, and what "agents" will probably mean by the time you graduate. His own story is pretty wild too. He was running a Canadian startup competing against Amazon Go before he ended up running GenAI deals at Amazon itself. The arc from analyst to startup founder to senior AI scientist is full of stuff that won't show up on a tidy career-advice carousel. The conversation I'm proudest of comes near the end. Surya grew up in India, studied in Canada, works in the US — and he's watched how each region is building AI from the inside. The contrast between how the East and the West think about AI right now is sharper than I expected. His take on India treating AI as public infrastructure is the kind of thing you don't hear in the usual big tech hiring discourse. If you're a CS student or new grad trying to figure out where to bet your career in the generative AI era, this one's for you. Surya tells you exactly what he'd do today if he were starting over. Subscribe for weekly conversations with the people figuring out what work actually looks like in the AI era. Connect with Surya:LinkedIn: https://www.linkedin.com/in/suryakari/ ⏱ Chapters:00:00 A Day in the Life of a Generative AI Data Scientist01:17 Understanding Customer Personas in Generative AI04:17 Upskilling in a Rapidly Evolving Field06:09 The Contrast of Experience in AI Tools09:33 Navigating Production Code and Testing12:15 The Hype Around AI Agents16:28 The Future of AI Agents and Their Limitations20:56 Surya's Journey: From Analyst to AI Expert23:48 Innovations in Retail Technology24:09 Transitioning to Edge Computing and AI26:36 Upskilling in Data Science and AI31:39 Cultural Differences in AI Development36:10 AI as Public Infrastructure in India

    46 min

  5. May 6

    How to Build a Global Health Career (Public Health Master’s, Oxford & WHO Africa) - w/ Dyuti

    How do you go from running tuberculosis programs in rural Bihar to studying at Oxford and eventually working with WHO Africa? There is no clean answer — and that is sort of the point. In this episode, I sit down with Dyuti Sen to talk about what a public health career actually looks like when you do not start as a doctor, do not have a linear plan, and refuse to pretend the journey was smooth. Dyuti studied economics, then entered the development sector through a social leadership fellowship in India. That fellowship dropped her into Dalsinghsarai in Bihar — not a posting you would find on a glossy career brochure. She spent five years there working on tuberculosis, community health delivery, and the enormous gap between what policy says on paper and what happens when a patient in a remote village needs treatment. She calls those years her real master's degree, and after hearing the details, you will understand why. We get into what public health work looks like day to day — the fieldwork, the project management, the bureaucracy. Why "free medicine" does not automatically mean people can access it. Why community health workers carry deep practical expertise that often gets overlooked. And why the distance between a well-designed health policy and its execution on the ground is where the real work lives. Then we talk about her Oxford journey. How she shortlisted master's programs, why scholarships were non-negotiable, what shifted after getting into International Health and Tropical Medicine, and how she later navigated the confusing world of WHO and UN applications. If you have ever stared at a UN job portal and thought "how does anyone actually get hired here?" — Dyuti walks through it with real specifics. This conversation is for anyone interested in global health careers, public health in India, international development pathways, WHO jobs, Oxford scholarships, or what it takes to build a meaningful international career from a non-medical background. No fluff, no fairy tale — just the real version of the path. Guest: Dyuti SenHost: Naman Pandey Disclaimer: Views expressed in this conversation are personal and do not represent WHO or any affiliated institution. Chapters:00:00 Dyuti's journey into public health03:52 Experiences in Bihar: a unique perspective06:39 Adapting to rural life and community dynamics09:14 A day in the life: from fieldwork to project management12:11 Challenges in public health: insights from the ground13:58 The importance of community health workers16:58 Lessons learned: the reality of public health work20:01 Battling tuberculosis in Bihar28:24 Navigating the application process for graduate studies36:09 Navigating scholarship applications and mindset39:19 India vs. the West: contrasting public health perspectives48:48 Journey to WHO: career path and lessons01:01:15 Understanding WHO's role in global health01:06:15 Future aspirations in public health

    1h 11m

  6. Apr 29

    How to Vibe-Code 20 Production Apps in 13 Days - w/ Avi

    Twenty apps. Thirteen days. Some already making money. That's what Avi Pilcer actually shipped while most of us were still picking a domain name. And the wild part? He didn't do it alone. He built an autonomous system called System Zero that does the heavy lifting for him. If you've been told "AI is making it easier to build" but you still freeze at "what should I build, how do I ship it, who's going to use it?" — this episode unjams the whole pipeline. Avi's path is not a normal founder origin story. He went from a struggling engineering student to an electric violinist in China (yes, really) to leading AI innovation at Motorola — all before "deep learning" was on most people's vocabulary list. Now he runs a framework-agnostic orchestration system that ships apps, buys Google Ads, writes SEO blogs, and nurtures email lists. All of it runs 24/7. None of it needs him babysitting. Host Naman Pandey gets into the parts nobody actually explains: Why "meta thinking" is the one skill that still matters when AI handles the code and the copy. How an automated AI process picks which apps to build — so you stop drowning in a Notion doc full of half-baked ideas. A live demo of Fleet AI launching a business in real time (this part will probably make you close your laptop and rethink your week). The "prune and purge" method for killing dead apps fast, because shipping is only half the game. The other half is knowing when to walk away. And why Avi thinks money and traditional jobs are on borrowed time — plus what to actually do about it before that clock runs out. If you're an indie hacker or a solopreneur who keeps refreshing Twitter looking for permission to start — this is the permission. 🚀 Built for the Peter Levels crowd and the Claude Code curious. Anyone tired of vibe coding their way into half-finished AI apps will find a real playbook here. Whether you're chasing your first profitable agentic AI workflow or trying to wire up autonomous AI agents that genuinely run without you, Avi hands over the full stack. This one belongs in the "watch twice, take notes" pile. ⏱️ TIMESTAMPS 00:00 – Building 20 Apps in 13 Days13:18 – Navigating AI Tools for Beginners19:19 – Demo of Apps26:45 – System Zero32:07 – Autonomous Operations and Self-Improvement36:11 – Integrating Multiple Projects and Use Cases37:59 – Distribution Strategies for App Success39:03 – Cost Optimization and Business Viability41:03 – The Future of Software Engineering in an AI World51:03 – Exploring System Zero: The Autonomous App Builder Subscribe to Ready Set Do for more raw conversations with the people building what comes next.

    52 min

  7. Apr 26

    How to Get Hired for Applied AI Roles in Fortune 500 Companies (Target Sr Data Scientist POV) - w/ Sowmya

    Picture this: it's 2023, ChatGPT just dropped, every Fortune 500 suddenly needs an "AI strategy," and the job postings want 5 years of experience in a technology that's barely 18 months old. How does anyone actually get hired in that mess? Sowmya Podila figured it out. She's now a Senior Data Scientist on Target's centralized Generative AI team — basically the internal startup that decides which AI use cases get built, killed, or scaled across the entire company. Before Target, she was deep in the chaos: interviewing at Google and other Fortune 500s during the wildest hiring wave applied AI has ever seen. We pull back the curtain on what enterprise AI actually looks like from the inside. Not the LinkedIn version. The real one. She walks through how she prepped for GenAI interviews when nobody on Earth had three years of GenAI experience, why she picked Target over Google (the answer is more interesting than you'd think), and what Fortune 500 hiring managers are actually screening for in 2026 once the hype settled. Here's the part nobody tells you: knowing when NOT to use AI is the most valuable skill on her team right now. Every PM wants an LLM in their product. Most of those ideas should be a SQL query and a dashboard. Sowmya breaks down how her team plays gatekeeper — and why that judgment call is what gets you hired, promoted, and trusted with bigger budgets. We also get into the agentic AI question everyone's dancing around. Can AI agents actually run a Fortune 500 company? (Spoiler: no, and the reasons are way less sexy than Twitter would have you believe — it's data plumbing, not model capability.) She talks through building a multi-agent simulator at Target, why company size completely changes the AI adoption playbook, and the messy reality of getting clean data out of systems built in 2008. Then we go big picture. Utopian future vs. dystopian future. Will AI take your job? Sowmya gives an honest answer that doesn't pander in either direction, which is rare these days. If you're trying to break into applied AI, data science, or ML engineering at a large company — or you're already in and trying to figure out what to bet your career on next — this one's for you. We cut through the noise so you know what actually matters vs. what's just LinkedIn theater. Connect with Sowmya:LinkedIn: https://www.linkedin.com/in/sowmyapodila/ Podcast site: www.readysetdopodcast.com Timestamps 00:00 - AI Implementation Landscape in Fortune 500 Companies04:21 - The Evolution of AI Strategies in Enterprises07:20 - Interview Insights: Navigating the AI Job Market10:19 - The Current Landscape of AI in Enterprises13:28 - Understanding the Role of AI in Business Decisions16:24 - The Future of AI Agents in Enterprises28:01 - Building a Multi-Agent Simulator31:15 - Challenges in AI Data Utilization33:33 - The Impact of Company Size on AI Adoption40:02 - The Future of AI: Utopian vs. Dystopian Views45:45 - The Importance of Content Creation in AI Awareness

    55 min

  8. Apr 16

    How to Get a UK Work Visa With No Lottery (H-1B Lottery Reject POV) - w/ Hari

    Hari Prasad Renganathan got rejected from the H1B lottery three times. Most people in that situation spiral. They scramble for a second master's, beg their company for an internal transfer, or start mentally preparing to go back home. Hari texted 10 YC startups, got callbacks from four of them, landed an offer as a Senior AI Engineer, and moved to London. The UK work visa took three weeks. No lottery. But here's the thing — that's just the final chapter of a pattern that's been repeating his entire career. Every time Hari hit a wall, he did the thing nobody else was willing to do. He applied to Columbia with a mechanical engineering degree from Tamil Nadu. No CS background. His GRE score was so average he deliberately withheld it from his application. He wrote an SOP that broke every template the admissions consultants swear by. He got in. After Columbia, he couldn't land an interview for four months. When a senior data scientist on his team quit, Hari walked up to the decision maker and said — and I'm quoting him here — "I'll be much cheaper than that guy." He got the full-time offer. Then he launched My Real Product, a community workshop where he helped data scientists and AI engineers stop building cookie-cutter Kaggle projects and start building actual products with real users. He put up a LinkedIn post expecting 20 people. 470 showed up. We also get into the AI conversation. Hari has a take on the whole "AI won't replace you, but people using AI will" thing. He disagrees. So do I, actually. He breaks it down into four layers of AI replacement and where you need to be if you want to be the last person standing. Whether you agree or not, it's the most specific framework I've heard anyone lay out on this topic. This conversation is for you if you're an international student navigating the US visa system, if you're trying to break into data science or AI without a traditional CS background, if you've been following every template and wondering why nothing is working, or if you just want to hear what happens when someone refuses to take no for an answer at every single turn. Timestamps, links, and ways to connect with Hari are all below. If this episode helped you think differently about even one thing, share it with somebody who needs to hear it. Site: readysetdopodcast.com Hari: https://www.linkedin.com/in/hariprasad20/ Timestamps: 00:00 Introduction & Connection03:23 AI, Personal Branding, and LinkedIn Presence05:29 From Mechanical Engineering to Data Science10:11 Navigating the Columbia Application Process14:56 Life at Columbia University19:43 Transitioning from Student to Professional23:26 Entrepreneurship and Building MyRealProduct26:26 Problem Solving with Data Science29:38 Building a Data Science Community33:12 Rejection from H-1B Lottery and Exploring Career Paths 45:43 The Future of AI and Its Impact

    54 min
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Ratings & Reviews

4.7
out of 5
3 Ratings

About

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.

Information

  • Creator
    Naman Pandey
  • Years Active
    2024 - 2026
  • Episodes
    109
  • Rating
    Clean
  • Copyright
    © Naman Pandey
  • Show Website
    Ready Set Do

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