AI Playbook with Ravi

What if the future of tech education isn't about having a laptop or fast internet? In this episode, Ravi Harsh sits down with Chidi Nwaogu, founder of EFIWE, to discuss how AI and technology can make learning more accessible for people who are often left behind. Chidi shares how his journey started at 16, the story behind his early startups, and why his mother's experience with technology shaped his mission. They also discuss AI powered adaptive learning, coding without a laptop, learning in your native language, vibe coding, AI dependency, and why understanding the fundamentals still matters in an AI powered world. Timestamps: 0:00 - AI hype vs. broken products 1:59 - Intro: Chidi, coding since age 16 5:10 - Why he started: mom lost her job 7:36 - First startup: climate change game at 16 10:12 - LagBook: connecting students 12:12 - Publisha: paying African creators 15:51 - Origin of Feweh 18:45 - Resigning to build it full-time 21:04 - Why offline, adaptive AI 25:04 - Coding in 246 languages 27:14 - The feedback story that changed everything 30:02 - Realizing rural users were excluded 31:07 - Building Feweh Zero (SMS coding) 38:37 - "AI is the new internet" 42:24 - Why coding fundamentals still matter 46:14 - The danger of vibe coding 49:38 - How AI self-corrects mistakes 51:16 - The India connection 56:12 - Vision for the next 5 years 1:00:04 - His daily AI use 1:01:41 - What he wishes AI did better In this episode • How Chidi started coding at 13 • Why his mother's job loss shaped his mission • Building startups from lived experiences • Why AI education needs to be more inclusive • Learning to code without a laptop or reliable internet • How AI adapts to different learning styles • Why user feedback can completely change a product • How Feway uses AI to help people learn and find jobs • Why AI won't replace the need to understand coding • The risks of relying too heavily on AI • Why vibe coding can be dangerous • Chidi's vision to help millions of people in the Global South learn and earn through technology Connect with Chidi LinkedIn: https://www.linkedin.com/in/chidinwaogu/ Website: https://efiwe.com 🎙️ AI Playbook with Ravi is available across all major podcast, newsletter, and social platforms. Listen, subscribe, and follow on your preferred platform: 🎧 Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-playbook-with-ravi/id6801309997 🎧 Spotifyhttps://open.spotify.com/show/033VeYRpT0wfwcyctis4T6 📰 Substackhttps://substack.com/@aiplaybookwithravi 💼 LinkedIn Newsletterhttps://www.linkedin.com/newsletters/ai-playbook-with-ravi-7492329752616284160/ 📸 Instagramhttps://www.instagram.com/ai_playbook_with_ravi/ 🤝 Connect with Ravi Harsh on LinkedInhttps://www.linkedin.com/in/raviharsh/ Subscribe wherever you listen or read—and join us as we explore how leaders, founders, and innovators are using AI in the real world. #AIPlaybookWithRavi

AI isn't just changing jobs. It's changing how we work, learn, hire, and build organizations.In this episode of The AI Playbook, Ravi Harsh sits down with Priyanka Bali, a workforce and organizational transformation professional with over 20 years of experience across technology, recruitment, and workforce strategy.They discuss whether AI is actually replacing jobs or exposing deeper problems that already existed in hiring, education, and the workplace. Priyanka explains why AI literacy is becoming essential, why experience and human judgment still matter, and why simply knowing how to prompt AI isn't enough.The conversation also explores AI-generated CVs, ATS bias, the growing talent paradox, coding and vibe coding, the future of entry-level jobs, employee upskilling, AI change management, shadow AI, data security, and how companies can redesign work without creating unnecessary anxiety.0:00 - Does AI take your job?1:56 - Intro: Priyanka, 20+ years in IT recruitment3:04 - Her background and career journey6:52 - Why education failed to teach us to question8:53 - Recruitment: the first industry hit by AI11:36 - The problem: every CV now looks perfect14:16 - Should schools ban AI?16:31 - What AI literacy actually means21:26 - The doctor analogy: AI vs. real experience24:55 - Coders and creatives: the two most disrupted fields26:04 - Why IT teams lose sight of the business problem32:32 - Do degrees still matter?35:40 - How can candidates compete now?36:52 - Why rejected candidates return as freelancers39:23 - AI writes CVs, AI screens CVs — what do recruiters do?41:36 - "There was never a talent shortage"43:20 - Bias built into ATS systems46:18 - Upskilling employees who are already in jobs48:28 - Why training fails without changing work design52:47 - Which jobs AI can actually replace55:02 - The psychological safety problem57:06 - Shadow AI: when employees use AI their company hasn't approved1:02:38 - What "sustainable recruitment" means1:07:19 - How she personally uses AI1:10:30 - The environmental cost of AI1:14:28 - Responsible AI and the closing messageIn this episode• Is AI really replacing jobs?• Why AI-generated CVs are creating a new hiring problem• The hidden problems with ATS and recruitment automation• Why experience still matters in an AI-powered world• What schools should teach when AI can answer everything• Why AI literacy is more than just prompt engineering• The future of coding and entry-level tech jobs• Why companies need to redesign work, not just add AI tools• How employees can adapt and stay relevant• Shadow AI, data leakage and responsible AI use• Why human judgment and ownership still matterConnect with PriyankaLinkedIn: https://www.linkedin.com/in/priyanka-b-b94518214🎙️ AI Playbook with Ravi is available across all major podcast, newsletter, and social platforms.Listen, subscribe, and follow on your preferred platform:🎧 Apple Podcastshttps://podcasts.apple.com/us/podcast/ai-playbook-with-ravi/id6801309997🎧 Spotifyhttps://open.spotify.com/show/033VeYRpT0wfwcyctis4T6📰 Substackhttps://substack.com/@aiplaybookwithravi💼 LinkedIn Newsletterhttps://www.linkedin.com/newsletters/ai-playbook-with-ravi-7492329752616284160/📸 Instagramhttps://www.instagram.com/ai_playbook_with_ravi/🤝 Connect with Ravi Harsh on LinkedInhttps://www.linkedin.com/in/raviharsh/Subscribe wherever you listen or read—and join us as we explore how leaders, founders, and innovators are using AI in the real world.#AIPlaybookWithRavi

AI is moving fast. But are businesses and people actually ready for it?In this episode of The AI Playbook, Ravi Harsh sits down with Rabiha Ansari, an AI strategist and advisor based in Germany, to discuss what it really takes to adopt AI in the real world.Rabiha shares her journey from computer science and 12 years of global IT consulting to building her own AI coaching and automation business. She explains why non-technical professionals need to understand AI, how she built a 3,500+ member global AI community, and why businesses should solve real problems instead of adopting AI just because everyone else is doing it.They also discuss AI automation with n8n, GDPR and the EU AI Act, why human oversight still matters, the risks of AI-generated mistakes, cybersecurity and data privacy, and why AI should enhance human expertise rather than replace it.Timestamps:0:00 - fears people bring to AI events1:56 - Intro: Rabiha, AI strategist & coach in Germany4:28 - From computer science to global IT consulting9:50 - Why companies still don't understand GDPR or EU AI Act10:53 - Leaving corporate to build her own company19:51 - Building a 3,500-member AI community from scratch26:36 - Why people fear "AI will take my job"33:50 - Shifting from AI coaching to AI automation34:51 - The problem with young "AI experts" selling voice agents40:00 - Why humans must stay in the loop for critical tasks46:17 - The plumber story: how she landed her automation client51:03 - Why she chose n8n over Zapier/Make55:41 - ChatGPT vs. n8n: why tool flexibility matters59:36 - Her honest take on the EU AI Act1:07:15 - What she still worries about: AI cybersecurity1:10:30 - Advice for women and non-tech people entering AIIn this episode• Rabiha's journey from computer science to AI strategy• Why AI literacy matters for non-technical professionals• Building a 3,500+ member global AI community• AI coaching vs AI automation• Why businesses shouldn't automate everything• n8n, AI workflows and staying flexible with different AI models• GDPR, the EU AI Act and AI compliance• Why humans should remain in the loop• AI cybersecurity and sensitive data risks• How AI can help professionals become more productive• Why curiosity matters more than your background or gender when learning AIConnect with Rabiha..LinkedIn: https://www.linkedin.com/in/rabihaansariYouTube Channel Link: https://www.youtube.com/@ai_rabihaMeetup Community Link: https://www.meetup.com/frankfurt-genai-for-non-techiesMy Business Website: https://rabiha-ansari.eu/------- ----- ------🎙️ AI Playbook with Ravi is available across all major podcast, newsletter, and social platforms.Listen, subscribe, and follow on your preferred platform:🎧 Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-playbook-with-ravi/id6801309997🎧 Spotify: https://open.spotify.com/show/033VeYRpT0wfwcyctis4T6📰 Substack: https://substack.com/@aiplaybookwithravi💼 LinkedIn Newsletter: https://www.linkedin.com/newsletters/ai-playbook-with-ravi-7492329752616284160/📸 Instagram: https://www.instagram.com/ai_playbook_with_ravi/🤝 Connect with Ravi Harsh on LinkedIn: https://www.linkedin.com/in/raviharsh/Subscribe wherever you listen or read—and join us as we explore how leaders, founders, and innovators are using AI in the real world.#AIPlaybookWithRavi

AI Doesn’t Understand the Real World. Here’s Why.AI's next big challenge isn't just building smarter models.It's giving those models better data from the real world.In this episode, Ravi Harsh sits down with Sunil Nair to explore the data powering the next generation of AI, robotics, and autonomous systems.Sunil explains why AI has a major representation gap when it comes to the Global South, why real world video and multimodal data matter, and how better contextual data could help AI understand places like Mumbai, Delhi, Jakarta, and beyond.They also discuss AI colonization, data consent and provenance, synthetic data, the future of jobs, and why the people contributing real world data should share in its economic value.Timestamps:0:00 - Will AI take my job?2:06 - Intro: Sunil, co-founder of clairva3:48 - What clairva does: "pix and shovels" of AI8:08 - Better data vs. better models debate11:27 - 93-95% of AI training data is Western-focused14:44 - Why AI misrepresents South Asian culture19:47 - The pivot from content library to bespoke data21:52 - Why AI only needs 8-10 minutes of a 1-hour video24:39 - How the data collection process actually works29:49 - Explaining it in simple terms (the omelette analogy)36:02 - Human cohort network across Southeast Asia38:06 - Why consent, copyright, and provenance matter40:41 - Can CCTV footage be used?43:48 - Do individual contributors get paid?45:20 - "Will this automate away my own job?"50:11 - His early startup Naukri that was ahead of its time53:01 - Lessons from working with Balaji, Alt, and Firework58:05 - How AI is already reshaping Indian content (micro-dramas)1:00:03 - The danger of AI training on synthetic "junk" data1:03:37 - Meet the co-founders and team1:07:36 - Closing thoughts```In this episode:• Why AI needs real world data• The Global South's AI representation gap• Why video is becoming critical for AI training• How raw video becomes structured AI data• Teaching AI to understand real world tasks• Data, consent, copyright and provenance• How people can earn from contributing data• AI, robotics and the future of jobs• The risk of AI colonization• Why synthetic data can't replace real world data• Who will control the world's AI data?Connect with Sunil NairLinkedIn:   / sunilrnair  Company: https://www.clairva.ai/🎙️ AI Playbook with Ravi is available across all major podcast, newsletter, and social platforms.Listen, subscribe, and follow on your preferred platform:🎧 Apple Podcastshttps://podcasts.apple.com/us/podcast...🎧 Spotifyhttps://open.spotify.com/show/033VeYR...📰 Substackhttps://substack.com/@aiplaybookwithravi💼 LinkedIn Newsletter  / ai-playbook-with-ravi-7492329752616284160  📸 Instagram  / ai_playbook_with_ravi  🤝 Connect with Ravi Harsh on LinkedIn  / raviharsh  Subscribe wherever you listen or read—and join us as we explore how leaders, founders, and innovators are using AI in the real world.#AIPlaybookWithRavi

Why Most AI Projects Fail Before They Even StartMost AI projects don't fail because the technology doesn't work.They fail because companies start with AI instead of the problem.In this episode, Ravi Harsh sits down with Nikhil to break down what actually makes AI projects succeed inside real businesses.Nikhil explains why companies need to define the business outcome first, how to identify the right AI use cases, and why AI should be treated as one layer of a larger system involving people, processes, software, and automation.They also discuss what happens when AI makes building easier but deciding what to build harder, how companies can calculate the real ROI of AI, and why humans still need to stay in control of important decisions.Timestamps :0:00 - The $5,000 AI vs $500 human cost problem1:43 - Intro: Nikhil — IIT grad, 20+ years in tech, runs an AI company in Sydney with his wife2:44 - Why 95% of generative AI projects fail (MIT report)5:24 - AI is a tool, not "the" solution6:14 - Career journey: dot-com era (2000) vs. the AI era today8:53 - Productivity leap: building multiple designs in parallel with AI10:02 - The "too many choices" problem (Netflix analogy)11:46 - Origin story: how "AI Too Easy" got its name13:58 - Early project: Decipher, the podcast automation SaaS16:16 - Finding the real problem: the AI discovery process17:41 - Case study: the proposal/quotation bottleneck19:28 - Why measurable outcomes matter (not just "enabling AI")20:58 - Deep dive: measuring ROI in time AND cost21:03 - Walkthrough: calculating token cost vs. staff cost24:18 - Addressing "AI is taking my job" fears26:41 - Why layoffs aren't always really about AI27:52 - Why AI Too Easy has 96% client retention28:25 - Case study: insurance company document automation32:11 - Data sovereignty & compliance (Australian data residency)34:47 - Why human-in-the-loop matters for high-stakes decisions34:55 - Managing AI hallucination and mistake risk38:40 - 3 things to do before starting an AI project41:16 - How Nikhil stays updated on AI (newsletters, X, automations)43:17 - Where AI is headed in the next 5 years45:39 - The real threats: overconfidence, blind trust, loss of critical thinking48:37 - Advice for young people entering tech in the AI era51:03 - Personal life: balancing work and home with his wife/co-founder52:38 - Closing question: "What are you still trying to figure out about AI?"54:56 - Final thoughts and sign-offIn this episode• Why most AI projects fail before development even begins• The biggest mistake companies make when adopting AI• How to identify a business problem worth solving with AI• Why AI is only one layer of the solution• How to define measurable outcomes before building• The AI Discovery Process Nikhil uses with businesses• How one company reduced a 30–40 minute process to just a few minutesConnect with NikhilLinkedIn: https://www.linkedin.com/in/nikhilsinghAI Too Easy: https://www.ai2easy.com.auConnect with MeLinkedIn: https://www.linkedin.com/in/raviharsh

This Founder Replaced Sales Calls With AI AgentsCan AI really replace your sales team? Or is it simply making them 10x more effective?In this episode of the AI Playbook Podcast, Ravi Harsh sits down with Khush Mutha, Co-Founder of AltaFlock, to explore how AI voice agents are transforming real estate sales, customer support, and business operations.At just 22 years old, Khush has built AI systems that instantly qualify leads, book site visits, automate follow-ups, and help businesses recover revenue that would otherwise be lost.They discuss why most businesses lose customers within minutes, how AI voice agents sound almost human, what makes AI adoption successful, and why the next wave of AI won't just be software—it will be physical robots.Whether you're a founder, agency owner, real estate developer, or simply curious about the future of AI, this episode offers practical insights into where the industry is heading.Timestamps:0:00 - Cold open: Lead follow-up & the AI voice agent pitch1:36 - Intro: The staffing problem that isn't actually a staffing problem2:14 - Guest intro: Khush Mutha, Penn State grad2:53 - Why he got into AI with zero coding background5:26 - Learning n8n, Claude Code, Supabase — starting small6:20 - First idea: automating manufacturing back-office work8:08 - Automating the PO (purchase order) approval pipeline9:39 - Landing the first client via warm network referrals10:07 - Discovering the real estate lead-response problem12:06 - Why real estate specifically? (high-ticket logic)14:57 - How the voice agent workflow actually works16:19 - Measuring success: site visits before sales18:39 - AI voice agent vs. traditional call centers20:53 - Why customers don't realize they're talking to AI21:34 - The 3 factors: latency, filler words, tone22:15 - Explaining ~600ms latency in simple terms25:02 - ROI: breaking even with one extra project sale26:41 - Why voice agents aren't technically hard to build27:31 - How they trained the data (100+ test calls)28:21 - Mapping the call flow with each client32:39 - Building custom solutions, not a product33:51 - Integrating with existing tools (Zoho CRM example)34:54 - Hindi and regional language support35:30 - Handling hard/off-topic questions, escalating to sales39:00 - Governance, compliance & data privacy (HIPAA, GDPR)40:20 - Tech stack: multiple agents vs. single n8n workflow41:08 - Breakdown of the 4-agent infrastructure44:19 - WhatsApp integration for site visit confirmations44:51 - Where AI is headed in the next 3 years48:32 - Physical AI and robotics as the "next big phase"50:13 - Implementation timeline for new clients (~2 weeks)51:41 - Regional language expansion (Gujarati example)51:57 - Team size and structure52:36 - He's 22 years old52:49 - Company name origin: "AltFlock"53:55 - Closing thoughtsIn this episode:• Why AI voice agents outperform traditional sales follow-ups• How real estate companies increase qualified site visits• Why speed matters more than hiring more salespeople• Building human-like AI conversations• AI latency, tone and psychology explained• How AI qualifies leads and predicts buying intent• Multi-agent AI systems working together• Why integrating with existing CRMs is essential• The future of AI over the next 3 years• Why taste and critical thinking will remain human advantagesKhush Mutha social handlesLINKEDIN :   / khush007  Company website:https://www.oltaflock.ai/Connect with MeLinkedIn:   / raviharsh  

How This filmmaker is Rebuilding Indian Stories Through Rebrand IndiaIn this episode of The AI Playbook, Ravi Harsh sits down with Shantanu Tungare —filmmaker, AI storyteller, and the mind behind Rebrand India—to explore how AI is democratising filmmaking, why India needs to own its narrative, and why creators should stop calling themselves "AI filmmakers."Shantanu shares his journey from working with some of the biggest names in entertainment to building Ancient Indian Billionaires, a transmedia universe powered by AI. He explains why storytelling fundamentals matter more than prompting, why most creators are using AI the wrong way, and how AI can help reshape India's image globally.Whether you're a filmmaker, creator, founder, marketer, or simply curious about the future of AI and creativity, this conversation is packed with practical insights and fresh perspectives.Timestamps:0:00 - "There's no such thing as an AI filmmaker" 1:14 - Intro: AI as a weapon to free storytellers2:08 - What is "Rebrand India"?7:22 - The F1 x Mumbai campaign story9:59 - Shantanu's career journey: hotels to Disney/Hotstar13:24 - Leaving the corporate world to build with AI14:16 - Launching Ancient Indian Billionaires15:00 - What is Ancient Indian Billionaires (trans-media series)17:14 - Turma: the next Rebrand India project17:59 - Why "AI filmmaker" is the wrong term18:52 - How much fundamentals vs AI skill do you need?21:15 - Why the first draft must always come from a human23:50 - Biggest challenges of using AI in filmmaking26:07 - Why AI filmmaking demands editors, not just directors27:00 - Is AI really taking jobs?34:43 - Advice for beginners: get on a real set first34:50 - Two routes into AI filmmaking36:52 - Why AI never lets you fail (the "yes-man" problem)38:01 - The 7-Day LLM Conversation exercise41:04 - What is "Narrative Immunity"?44:59 - Deepfakes and owning your online narrative48:10 - ChatGPT vs Claude: which does he actually use?49:52 - Why he's skeptical of AI founders51:41 - Does India need its own foundational model?53:47 - Building fast vs building right55:37 - What's next: 26 IPs, Turma seasons58:03 - Closing mantra: automate the noise, humanize the storyWhat you'll learn✅ The mission behind Rebrand India✅ Why AI is a tool, not a replacement for storytellers✅ Why every filmmaker should learn editing first✅ The biggest mistakes creators make with AI✅ How Ancient Indian Billionaires was built with AI✅ Why storytelling fundamentals matter more than prompting✅ Will AI replace filmmakers and creative jobs?✅ How to build your Narrative DNA with AI✅ The future of storytelling in the AI era✅ ChatGPT vs Claude for creatorsShantanu Tungare's social handlesLINKEDIN :   / shantanutungare  Instagram :   / shantanu.tungare  YouTube :    / @shantanutungare  Substack : https://shantanutungare.substack.com/X : https://x.com/ShantanuTungareAll my socials : https://linktr.ee/shantanu.tungareConnect with MeLinkedIn:   / raviharsh  Read the full Substack article: *How One Filmmaker Is Rebranding India Through AI Storytelling* 👇https://bit.ly/3TqoK90SubscribeIf you enjoyed this conversation, subscribe for more interviews with founders, filmmakers, creators, and AI leaders building the future of technology, business, and storytelling.Is the term AI filmmaker actually hurting your creative reputation? We analyse why limiting your title to technology is a mistake.Many creators are adopting the AI filmmaker label, but this trend might be narrowing your professional identity rather than expanding it. This discussion examines why relying on specific tool-based terminology can diminish the actual work of the creator, much like how James Cameron never branded himself a motion capture artist despite his extensive use of the technology in Avatar.

How can one solo founder build real AI products without a traditional coding background? In this episode, Steve shares how Claude Code, Cursor, and AI-assisted development changed his entire product-building process.Steve comes from a video production and broadcasting background, but instead of only using AI as a writing or research tool, he started building real products with it. We discuss how he built tools like QScope for vMix live production, Circuit for creator monetisation, Privy AI for legal document summaries, a media recorder, and more.This conversation is not about AI hype. It is about the practical reality of building with AI: spotting a real problem, validating the market, choosing the right tools, pushing back against AI answers, knowing when to pivot, and understanding why marketing is often harder than building.On AI Playbook with Ravi, we explore how AI is being used in real business work by founders, creators, project managers, operators, and early adopters. Watch until the end for Steve’s advice on building something alongside a full-time job, why he prefers building right over building fast, and how he uses an “honesty agent” to challenge AI outputs.#AIPlaybookWithRavi #ClaudeCode #AIProducts#AIBusiness #AITools #SoloFounder #AICoding

Discover how an award-winning AI film was made from idea to final output — including the creative process, tools, workflow, challenges, and lessons behind AI filmmaking.In this episode of AI Playbook with Ravi, we explore the full process of creating a short film using AI. From concept development and visual planning to prompting, editing, storytelling, and final production, this conversation breaks down what it really takes to make an AI-powered film that stands out.This video is useful for filmmakers, creators, content producers, project managers, and anyone curious about how artificial intelligence is changing the future of content creation.You’ll learn how AI can support the filmmaking process, where human creativity still matters most, and what creators should understand before using AI tools for serious storytelling.Watch till the end if you want a practical look at how AI filmmaking works beyond the hype — and what this means for creators, media teams, and the future of production.What You’ll Learn • How an award-winning AI film was created from start to finish • What role AI tools played in the filmmaking workflow • How creators can use AI for ideation, visuals, editing, and storytelling • What mistakes to avoid when making films with AI • Why human creativity is still the most important part of AI filmmaking • What the future of AI-powered content production could look likeLinksAnkit Sharma LinkedIn:https://www.linkedin.com/in/ankitsharmatv/The Bhabha Files Untold story of Homi Bhabha - AI Short Film (Winner of TV9 AI Awardshttps://www.youtube.com/watch?v=G5gBce54WCsAnkits’s Porfoilio https://aceshotmovies.com/AI tool used https://aceshotmovies.com/Idea of Permission less filmmaking The Revolution Happening in Filmmaking and VFX with Nikola | Bad Decisions Podcast #75https://youtu.be/JRXmPbOr9Hk?si=_g3r2SrLumJqzZ_c&t=383Hashtags#AIPlaybookWithRavi #AIFilmmaking #ArtificialIntelligence