Data & AI with Mukundan | Learn AI by Building

I missed my parents, so I built an AI that talks like them. This isn’t about replacing people—it’s about remembering the voices that make us feel safe.In this 90-minute episode of Data & AI with Mukundan, we explore what happens when technology stops chasing efficiency and starts chasing empathy. Mukundan shares the story behind “What Would Mom & Dad Say?”, a Streamlit + GPT-4 experiment that generates comforting messages in the voice of loved ones.You’ll hear:The emotional spark that inspired the projectThe plain-English prompts anyone can use to teach AI empathyBoundaries & ethics of emotional AIHow this project reframed loneliness, creativity, and connectionTakeaway: AI can’t love you—but it can remind you of the people who do.🔗 Try the free reflection prompts below:THE ONE-PROMPT VERSION: “What Would Mom & Dad Say?” “You are speaking to me as one of my parents. Choose the tone I mention: either Mom (warm and reflective) or Dad (practical and encouraging). First, notice the emotion in what I tell you—fear, stress, guilt, joy, or confusion—and name it back to me so I feel heard. Then reply in 3 parts:Start by validating what I’m feeling, in a caring way.Share a short story, lesson, or perspective that fits the situation.End with one hopeful or guiding question that helps me think forward. Keep your words gentle, honest, and simple. No technical language. Speak like someone who loves me and wants me to feel calm and capable again.”Join the Discussion (comments hub): https://mukundansankar.substack.com/notesTools I use for my Podcast and Affiliate PartnersRecording Partner: Riverside → Sign up here (affiliate)Host Your Podcast: RSS.com (affiliate )Research Tools: Sider.ai (affiliate)Sourcetable AI: Join Here(affiliate)🔗 Connect with Me:Free Email NewsletterWebsite: Data & AI with MukundanGitHub: https://github.com/mukund14Twitter/X: @sankarmukund475LinkedIn: Mukundan SankarYouTube: Subscribe

What happens when an AI starts asking better questions than you?In this 60-minute episode, I share the real story behind “The AI That Thinks Like an Analyst” — a Streamlit + GPT-4 project that changed the way I see data, curiosity, and creativity.This isn’t a technical tutorial. It’s a journey into the mind of a data professional learning to think deeper — and how building this AI taught me the most human lesson of all: how to stay curious.We’ll explore:Why the hardest part of analysis isn’t code — it’s curiosity.How I built a privacy-first Streamlit app that generates questions instead of answers.What AI can teach us about slowing down, observing, and thinking like explorers.The moment I realized data analysis and self-reflection are the same skill.If you’ve ever felt stuck staring at your data, unsure what to ask next — this episode is for you. 📖 Read the full story: https://mukundansankar.substack.com/p/the-no-upload-ai-analyst-v4-secure Join the Discussion (comments hub): https://mukundansankar.substack.com/notesTools I use for my Podcast and Affiliate PartnersRecording Partner: Riverside → Sign up here (affiliate)Host Your Podcast: RSS.com (affiliate )Research Tools: Sider.ai (affiliate)Sourcetable AI: Join Here(affiliate)🔗 Connect with Me:Free Email NewsletterWebsite: Data & AI with MukundanGitHub: https://github.com/mukund14Twitter/X: @sankarmukund475LinkedIn: Mukundan SankarYouTube: Subscribe

Data interviews do not have to feel messy. In this episode, I share a simple AI Interview Copilot that works for data analyst, data scientist, analytics engineer, product analyst, and marketing analyst roles.What you will learn today:How to Turn a Job Post into a Skills Map: Know Exactly What to Study First.How to build role-specific SQL drills (joins, window functions, cohorts, retention, time series).How to practice product/case questions that end with a decision and a metric you can defend.How to prepare ML/experimentation basics (problem framing, features, success metrics, A/B test sanity checks).How to plan take-home assignments (scope, assumptions, readable notebook/report structure).How to create a 6-story STAR bank with real numbers and clear outcomes.How to follow a 7-day rhythm so you make steady progress without burnout.How to keep proof of progress so your confidence comes from evidence, not hope.Copy-and-use prompts from the show:JD → Skills Map: “Parse this job post. Table: Skill/Theme | Where mentioned | My level (guess) | Study action | Likely interview questions. Then give 5 bullets: what they are really hiring for.”SQL Drill Factory (Analyst/Product/Marketing): “Create 20 SQL tasks + hint + how to check results using orders, users, events, campaigns. Emphasize joins, windows, conditional agg, cohorts, funnels, retention, time windows.”Case Coach (Data/Product): “Run a 15-minute case: key metric is down. Ask one question at a time. Score clarity, structure, metrics, trade-offs. End with gaps + practice list.”ML/Experimentation Basics (Data Science): “Create a 7-step outline for framing a modeling problem (goal, data, features, baseline, evaluation, risks, comms). Add an A/B test sanity checklist (power, SRM, population, metric guardrails).”Take-Home Planner: “Given this brief, propose scope, data assumptions, 3–5 analysis steps, visuals, and a short results section. Output a clear report outline.”Behavioral STAR Bank: “Draft 6 STAR stories (<120s) for conflict, ambiguity, failure, leadership without title, stakeholder influence, measurable impact. Put numbers in Results.”

If your job search feels like tab-hell—applications everywhere, prep scattered, follow-ups forgotten—this episode is your reset. I walk you through three small but mighty AI agents you can build in an afternoon:• Application Tracker Agent — paste a job link → extract company, title, pay, location → auto-log to Notion/Sheets → set a 7-day follow-up. • Interview Prep Agent — feed the JD + your resume → get tailored behavioral questions, SQL/case drills, and a tight “Tell me about yourself.” • Follow-Up Agent — generate a thank-you in your voice, log the interview date, and nudge you if you haven’t heard back.You’ll learn the agent essentials—planning, memory, feedback loops—plus a copy-and-paste framework, example prompts, and quality checks so your agents save time instead of making noise.Chapters below. Show notes include my working templates, prompts, and affiliate tools I actually use (Riverside for recording, RSS.com for hosting, Sider for research). Rate the show if this helped—it means a lot.Primary keywords: ai agents, job search, interview prep, application tracking, follow-up emails Secondary keywords: Notion, Google Sheets, SQL interview, behavioral questions, automation, productivity, podseo, career toolsLinks & ResourcesRecording Partner: Riverside → Sign up here (affiliate)Host Your Podcast: RSS.com (affiliate )Research Tools: Sider.ai (affiliate)Join the Newsletter: Free Email Newsletter to receive practical AI tools weekly.Join the Discussion (comments hub): https://mukundansankar.substack.com/notes🔗 Connect with Me:Website: Data & AI with MukundanTwitter/X: @sankarmukund475LinkedIn: Mukundan SankarYouTube: Subscribe

Plain-English agents, not hype: plan, use tools, add guardrails—then dry-run a calendar + inbox agent that saves hours.You’ve heard “AI agent” everywhere, but definitions vary. In this episode, Mukundan explains—in plain, practical language—what a real agent is and when to use one. We’ll contrast agents with chatbots and simple automations, walk through the five pillars (goal, plan, tools, memory, feedback), and strip the tooling of buzzwords. Then we run a live dry-run: two 90-minute deep-work blocks, one 45-minute admin sweep, and a 30-minute workout that avoids your existing commitments. We finish by triaging sample emails into reply/delegate/archive/read-later and drafting five concise replies with one clear next step each. Safety first: drafts-only, tentative calendar holds, approval gates, and fallbacks if tools fail. Copy the templates from the show notes and ship your v0.5 tonight.Lightning Round: True/False (answers in the episode)An AI agent is just a chatbot.Remove a tool and it still makes progress → probably a real agent.Clear success criteria matter less than good prompts.Chatbots reply; agents execute across steps.Fixed automations are best when inputs rarely change.If a tool disconnect breaks everything, it’s a brittle macro.Links & ResourcesAI Agent Copy-Paste Templates (run these in ChatGPT): Get your free copyRecording Partner: Riverside → Sign up here (affiliate)Host Your Podcast: RSS.com (affiliate )Research Tools: Sider.ai (affiliate)Join the Newsletter: Free Email Newsletter to receive practical AI tools weekly.Join the Discussion (comments hub): https://mukundansankar.substack.com/notes🔗 Connect with Me:Website: Data & AI with MukundanTwitter/X: @sankarmukund475LinkedIn: Mukundan SankarYouTube: Subscribe

AI, data, numbers—without uploads. Hash, mask, and redact PII, then run data analytics locally for time-saving and privacy.In this episode, we build a No-Upload AI Analyst that keeps your PII safe: HMAC SHA-256 hashing, masking, and redaction using policy presets and client-side transforms. We’ll: • Reframe the problem (insights > risk) • Set four hard constraints (no uploads, local preferred, policy presets, human-readable audit) • Use rules-first privacy + schema semantics • Walk the 5-step workflow (paste headers → pick preset → set secret → transform → analyze) • Show real-world cases (HIPAA/HITECH-aware analytics, FERPA contexts, product analytics) • Share a checklist + quiz + local Streamlit approach Perfect for data teams in healthcare, finance, education, and privacy-sensitive orgs.Key takeawaysStop uploading customer data. Transform it client-side first.Use HMAC hashing to keep joins without exposing raw emails/IDs.Mask for human-readable UI; redact when you don’t need the field.Ship a data-handling report with every analysis.Run the app locally for maximum privacy.Affiliate note: I record with Riverside (affiliate) and host on RSS.com (affiliate). Links in show notes.LinksBlog version: (Free): https://mukundansankar.substack.com/p/the-no-upload-ai-analyst-v4-secure Join the Discussion (comments hub): https://mukundansankar.substack.com/notesTools I use for my Podcast and Affiliate PartnersRecording Partner: Riverside → Sign up here (affiliate)Host Your Podcast: RSS.com (affiliate )Research Tools: Sider.ai (affiliate)Sourcetable AI: Join Here(affiliate)🔗 Connect with Me:Free Email NewsletterWebsite: Data & AI with MukundanGitHub: https://github.com/mukund14Twitter/X: @sankarmukund475LinkedIn: Mukundan SankarYouTube: Subscribe

I first built an AI that thinks like an analyst. Now I have built a better AI Data analyst for the practical use of AI. This episode breaks down the simple rebuild: start with a clear objective, pick 5–8 focus columns, and ship a one-page Markdown brief. You’ll also get a 3-minute quiz (10:33), a Substack discussion (17:04), and a 9-step checklist you can use today.What you’ll learnHow to start with a clear business goal (not charts)Why focusing on 5–8 columns increases signalHow a 1-page brief moves work faster than a dashboardQuiz & DiscussionTake the Lightning QuizJoin the Substack discussion: https://mukundansankar.substack.com/(Tell your day-two story, your one metric, and your 5–8 focus columns.)Listener ChecklistCopy/paste:1) Objective (one line)2) 5–8 focus columns3) 10 questions + why4) Quick data health checks5) Export 1-page brief6) Share in Slack/Notion/Jira7) Run 2–3 quick analyses today8) Log learning + next decision9) Repeat tomorrowLinksBlog version: (with Medium membership): https://medium.com/data-science-collective/i-built-an-ai-that-thinks-like-a-data-analyst-then-it-went-viral-so-i-made-it-smarter-1f3206a8254b(Free): https://mukundansankar.substack.com/p/i-built-an-ai-that-thinks-like-aSubstack Note (comments hub): https://mukundansankar.substack.com/notesTools I use for my Podcast:Recording Partner: Riverside → Sign up here (affiliate)Host Your Podcast: RSS.com (affiliate )Research Tools: Sider.ai (affiliate)🔗 Connect with Me:Free Email Newsletter: https://data-ai-with-ms.kit.com/bae4d0c550Website: https://mukundansankar.substack.com/Twitter/X: @sankarmukund475LinkedIn: https://www.linkedin.com/in/mukundansankar/YouTube: https://www.youtube.com/@MukundSankar

Description: Join Mukundan Sankar as he explores the challenges of delivering an effective elevator pitch and how AI can assist in crafting one. Mukundan shares personal anecdotes and demonstrates AI-generated pitches tailored for different career stages.Key Takeaways:The importance of a well-crafted elevator pitch How AI can personalize pitches for different roles Real-life examples of AI-generated pitchesResources:1]Elevator Pitch AI Code Mukundan's Blog Post: https://substack.com/home/post/p-1704009772] Thinking about starting a podcast but worried it’ll take forever to grow? Here’s the thing — you don’t need a huge audience to get started or to earn money.I run my show on RSS.com, and it’s the simplest way to get your podcast live on Spotify, Apple, Amazon, YouTube, iHeartRadio, Deezer, and more — all in one step. Their analytics tell me exactly where my listeners are tuning in from, so I know what’s working.And here’s the best part — with their paid plan, you can start earning revenue through ads with as little as 10 downloads a month. That’s right — you don’t need to wait for thousands of listeners to start monetizing.Start your podcast for free today at RSS.com. (Affiliate link — I may earn a commission at no extra cost to you.)3] 💡 Sider.ai– Your AI Copilot for Productivity: Sider.ai is the all-in-one AI assistant that works inside your browser, letting you research, write, summarize, and brainstorm without switching tabs. Whether you’re prepping for an interview, drafting your next pitch, or refining your business plan, Sider.ai can supercharge your productivity. It’s like having GPT-4 on standby, ready to help you think faster and write better. Try Sider.ai today and see how much more you can accomplish in less time. (Affiliate link — I may earn a commission if you sign up.)

Turn writing into a clean, editable deck—create slides with AI so you focus on the message, not formatting. Includes a simple presentation workflow.🎧 Episode Summary:Create slides with AI—fast, clear, editable. This episode shows how I turned long-form writing (blogs, memos, outlines) into a polished slide deck you can download and edit—without getting stuck in formatting. You’ll get a simple AI presentation workflow, a reusable prompt, and ideas for diagrams that actually support your point.You’ll learnA repeatable blog → slides structure (7–10 slides, title + 3–5 bullets)How to keep slides human: clarity over decorationWhen to include a diagram (only for processes/flows)A fast export routine so you can present anywhereTry this (no code) “Convert this article into a 9-slide deck. For each slide: short title + 3–5 bullets, no paragraphs. If a slide describes a process, write a one-line prompt for a simple diagram. Keep language clear and speak to a non-expert audience.”Do next Generate → lightly edit → export → deliver. The goal is a message people can follow, not a template people admire.DIY guide https://medium.com/data-science-collective/i-built-an-ai-that-turns-any-blog-post-into-a-polished-slide-deck-with-smart-diagrams-10cbda8010aa

In this deeply personal episode, I share the story of a chaotic week, mounting pressure, and a craving for Sonic fries. But more importantly, I take you inside the quiet tool I built—an AI Thought Organizer.It didn’t coach me. It didn’t solve anything. It just… reflected what I was already feeling.Inside the episode:The emotional spiral that led to this toolHow I built it (yes, with code—but it’s not technical)Why the laugh that followed changed everythingWhat this experience taught me about overwhelm, clarity, and AIWhether you're a builder, creator, or someone looking for a new kind of peace—you’ll want to hear this.🛠 Full blog and source code:1] Medium: https://medium.com/data-science-collective/i-fed-my-thoughts-to-an-ai-and-it-helped-me-breathe-again-c9796f17c7912] Website: https://mukundansankar.substack.com/p/i-fed-my-thoughts-to-an-ai-and-it🍟 Craving fries after listening? You’re not alone.

TakeawaysAutomating presentations can enhance storytelling with data.Traditional Jupyter notebooks often lack narrative flow.The app allows users to upload notebooks for instant presentation creation.AI-generated content can significantly reduce preparation time.Effective communication is crucial for success in data roles.The app provides a strong foundation for presentations.Real-world use cases include students and data analysts.Future plans include more diagram types and voice narration.The project is open source and encourages collaboration.The tool is designed for anyone in the data field.Free Blog: https://mukundansankar.substack.com/p/beyond-the-notebook-how-to-turn-anyMedium Users: https://medium.com/data-science-collective/beyond-the-notebook-how-to-turn-any-data-science-jupyter-notebook-into-stunning-animated-slide-e738bebc195e

SummaryIn this episode, Mukund Sankar discusses the development of his AI reflection system, Reflection OS, which aims to provide emotional clarity and productivity support. He shares his personal struggles with time management and emotional burnout, leading to the creation of a tool that acts as a compassionate mirror for self-reflection. The conversation explores the technology behind the app, its purpose in building emotional habits, and future plans for community engagement and beta testing.Blog: https://medium.com/data-science-collective/i-built-an-ai-app-that-reflects-my-feelings-not-just-my-output-2a40c275243dWebsite: https://mukundansankar.substack.com/