The Programming Podcast

• "It's a simple JavaScript fix!" (Spoiler: IT WASN'T)

  You know that “it’s a simple fix” task that eats your entire sprint? If you liked this episode or if this saved you a sprint: like, subscribe, and share with your team. Comment your worst “simple fix” story! We’ll feature a few next episode!This episode is about going from “just parse the RSS” to a real system with cron jobs, a database, SSR, caching, pagination, title-matching pain, and a YouTube Data API gotcha where deleted videos still show up and break your counts. We unpack the technical rabbit hole, the product/process mistakes that made it worse, and the practical fixes you can ship today.SITE https://www.programmingpodcast.com/Stay in Touch:📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!Danny Thompsonhttps://x.com/DThompsonDevhttps://www.linkedin.com/in/DThompsonDevwww.DThompsonDev.comLeon Noelhttps://x.com/leonnoelhttps://www.linkedin.com/in/leonnoel/https://100devs.org/📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!Highlights- Why YouTube RSS only returns ~15 items, and when to switch to the Data API-The sneaky “deleted video” entries that broke episode matching (and the 4-line filter that fixed it)- Cron + DB to avoid on-request parsing delays, with lazy loading/pagination for perf- Levenshtein vs. AI scraping for cross-platform title matching (and tradeoffs)- SSR for SEO: hydration pitfalls, view-source reality checks, and caching strategy- Process: ticket sizing gone wrong, sprint rituals that would’ve saved weeks, and a fallback plan when APIs fail- Career bit (Huntober): the highest-ROI job-hunt moves—ask directly for referrals and quantify your wins so AI can actually write a good resumeWhat You’ll LearnWhen RSS is fine—and when you must use YouTube Data API v3Designing a resilient ingestion path (cron triggers, rate limits, cost control)Secure API key handling and avoiding accidental exposureConcrete heuristics for matching episodes across platformsThe “fallback first” mindset when upstream services go downStack & Tools MentionedNext.js/SSR, Tailwind/CSS (retro radio UI), cron + DB ingest, YouTube Data API v3, Spotify RSS, Levenshtein distance, AI/LLM parsing workflow, lazy loading/pagination, caching.Chapters00:00 It’s “simple”… until it isn’t (cold open)02:00 50 episodes milestone + data-driven intros03:20 New personal site goals (personas, UX, content routing)06:04 Rotary-dial content hub idea07:42 Plan A: “Just use Spotify/YouTube RSS”08:56 Parsing delays → cron + DB ingest11:00 Release cadence (Thurs AM CT) & autosync plan12:07 YouTube RSS ≈ 15 items?!13:19 Enabling YouTube Data API v3 (the missing step)14:22 Title matching fails; publish vs. upload date mismatch16:31 AI scrape workflow vs. deterministic pipelines17:13 Levenshtein distance for fuzzy matching18:53 The painful bug: deleted YouTube videos still in API20:20 Security considerations for API keys21:08 Retro CSS “radio” UI + Tailwind23:01 From 2 points to full sprint (scope creep lessons)24:03 Rate limits, CORS, and API cost control24:54 SSR for SEO, hydration errors, caching26:24 Web creativity is back (experimentation talk)27:29 Sprint Zero / refactor time that saves real sprints28:24 Resilience: API fallback to RSS29:18 Perf: lazy loading & pagination30:01 Tests vs. cowboy deploys (real talk)31:20 Takeaways: when to keep it simple vs. do it right36:01 What is Huntober?37:41 Highest-ROI job hunt move: ask for referrals39:07 Make AI useful: quantify your work41:15 Outro

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• Why 95% of Enterprise AI Projects FAIL! CEO of Apollo GraphQL, Matt DeBergalis

  AI is writing more code than anyone expected. Some of it is great. A lot of it is just okay. In this episode, Danny Thompson and Leon sit down with Matt DeBergalis, CEO of Apollo GraphQL, to unpack what it will take to move from a gold rush of mediocrity to production-grade agentic experiences that users can trust.Guest Co-Host: Matt DeBergalishttps://www.linkedin.com/in/debergalis/https://www.apollographql.com/ @ApolloGraphQL SITE https://www.programmingpodcast.com/Stay in Touch:📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!Danny Thompsonhttps://x.com/DThompsonDevhttps://www.linkedin.com/in/DThompsonDevwww.DThompsonDev.comLeon Noelhttps://x.com/leonnoelhttps://www.linkedin.com/in/leonnoel/https://100devs.org/📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!We dig into the real gap behind AI project failures and it is not the models. Matt explains why agentic development stalls inside enterprises, how microservice sprawl blocks useful AI, and where GraphQL functions as the control plane that unifies data, streaming, and context so agents can actually do work. We cover the early hype around MCP servers, why many of them ship without OAuth, and a concrete checklist for securing costs and credentials before you flip the switch.You will hear where shopping, search, and SEO are headed as prompt boxes replace search boxes. We get into the gravity that pulls models toward stacks with the most public code, what that means for React, Rust, Python, and the long tail, and how developers can future proof their careers by mastering fundamentals like orchestration, context control, and system design instead of chasing every weekly model benchmark.We wrap with a practical path for job seekers. Breadth over tool loyalty. Weekly small projects. Use AI for the first 75 percent, then own the last 25 percent with clear prompts and better workflows.Who this episode is for- Engineering leaders trying to turn AI prototypes into products- Senior and staff engineers learning agent orchestration- Devs curious about MCP, GraphOS, and secure tool callingYou will learn- Why 95 percent of agentic projects fail and what capability is missing- How GraphQL unifies fragmented systems for agents, including streaming and precise context selection- A security and cost control checklist for MCP style tool calling- How hiring rubrics are shifting toward communication, systems thinking, and curiosity- A weekly practice plan to build portfolio proof fastHighlightsGold rush of mediocrity and what to do about itFrom REST to stateful agents and why the old web stack creaksEvery search box becomes a prompt boxThe 75 and 25 rule for productive AI assisted codingTool breadth over tool loyalty for career advantageChapters00:00 Cold open. Why most agentic projects fail01:00 Theme setup. The gold rush of mediocrity01:30 Host and guest introductions03:00 MCP excitement vs reality. From laptop tools to real products06:15 Security and spend. OAuth gaps, scoped keys, rate limits, audit logs09:00 Distribution shift. Generative SEO and agentic checkout13:10 Centralization gravity. Why models favor stacks with more public code18:00 Foundations. Unifying services with GraphQL and streaming tokens24:10 Controlling the context window with field selection26:30 Should developers learn this now31:30 Fundamentals over benchmarks. MCP, RAG, evals42:00 Hiring in the agent era. Communication, systems thinking, curiosity48:00 Prompt quality and the last mile53:00 Audience question. Tools to explore and a weekly practice plan59:30 Closing recap and CTA

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• How GREAT Senior Software Engineers Think! (Steal these 9 TIPS!) Kent C. Dodds

  Senior engineers don’t “wing it.” They use mental models to turn plans into production—faster, safer, and with less drama. Danny Thompson, Leon Noel, and Kent C. Dodds break down the exact models they use: decision docs, second-order thinking, reducing cognitive load, Occam’s Razor, leaky abstractions, feature flags vs. staging, chaos engineering, AI context windows (and rot), MCP, onboarding docs, blind code reviews, and more. If you’re pushing from mid → senior (or trying to sound senior in interviews), steal these.Guest: Kent C. Dodds!https://kentcdodds.com/https://x.com/kentcdodds @KentCDodds-vids SITE https://www.programmingpodcast.com/Stay in Touch:📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!Danny Thompsonhttps://x.com/DThompsonDevhttps://www.linkedin.com/in/DThompsonDevwww.DThompsonDev.comLeon Noelhttps://x.com/leonnoelhttps://www.linkedin.com/in/leonnoel/https://100devs.org/📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!You’ll learn→ How to communicate invisible work like a senior (impact vs activity)→ Decision documents: making tradeoffs explicit→ Second-order thinking to prevent “future bugs”→ When to ship fast with flags vs. slow with staging→ Designing for onboarding—humans and AI assistants→ Using AI without nuking your circle of competence→ Local job tactics (Memphis example), recruiters, and “entry-level” framingIf this helped, hit 👍 and subscribe. Drop your favorite mental model in the commentsChapters00:00 Cold open — “When plans break in prod”00:36 Why mental models matter for seniors02:45 Define “mental model” (map vs. territory)05:22 Intros + episode setup07:05 Decision documents & guiding principles10:48 Coaching moments: easy vs. right solutions12:56 Second-order thinking (caching, short links, spam)15:58 Occam’s Razor in real engineering decisions18:12 Onboarding for Future-You (and your AI)20:44 Tests as guardrails for humans + LLMs22:18 AI context windows, “context rot,” and structure24:55 Circle of competence in the AI era27:18 Should juniors use AI? The real risks30:06 Shipping fast vs. learning deep: when to limit AI31:55 Interviews are changing: system design vs LeetCode33:42 Confidence traps: getting gaslit by your prompts36:00 Too many abstractions → leaky abstractions38:40 Blind code reviews & cross-team learning41:20 Google-style anonymous reviews (tradeoffs)44:00 Feature flags vs. staging (the spicy debate)46:52 Chaos engineering & safe rollouts in prod49:10 Pragmatism over dogma: what actually ships50:58 Kent’s Epic AI cohort & MCP primer54:20 Listener Q&A: local vs. remote, .NET vs. Node1:00:45 Ask Danny, Leon, And Kent!

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• The World's Most Popular Teacher Reveals The Secret to Learning ANYTHING.

  Are you studying for hours but still not retaining anything? 🧠 It's probably not your fault, you've likely been taught to learn all wrong.In this landmark episode, we sit down with the legendary Dr. Barbara Oakley, a Distinguished Professor of Engineering at Oakland University, a globally recognized expert on the science of learning, and the creator of the world's most popular online course, "Learning How to Learn," which has reached millions worldwide. Dr. Oakley shares her incredible journey from flunking math and hating school to becoming a world-renowned expert on the neuroscience of learning.Get ready to have your mind blown as Dr. Oakley debunks the biggest myths about studying, reveals the simple, science-backed secrets to mastering any subject, and explains how to beat procrastination for good. You'll walk away with actionable techniques to unlock your brain's true potential.She is best known for making complex concepts from neuroscience and cognitive psychology accessible to a mass audience, empowering millions to learn more effectively. Her own life story is a testament to her core message: anyone can learn anything.Dr. Oakley is most famous as the co-creator of "Learning How to Learn: Powerful Mental Tools to Help You Master Tough Subjects," one of the most popular massive open online courses (MOOCs) in the world. Hosted on Coursera, the course has enrolled millions of learners from every country, teaching them practical, science-backed strategies for learning.Her work has been featured in major publications like The New York Times and The Wall Street Journal. She is also the author of several books, including the bestseller "A Mind for Numbers," which serves as a companion to her course.Places you can follow Dr. Barbara Oakley📚 Dr. Oakley's Book | A Mind for Numbers: https://barbaraoakley.com/books/a-mind-for-numbers/🎓 The "Learning How to Learn" Course: https://www.coursera.org/learn/learning-how-to-learnStay in Touch:📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!Danny Thompsonhttps://x.com/DThompsonDevhttps://www.linkedin.com/in/DThompsonDevwww.DThompsonDev.comLeon Noelhttps://x.com/leonnoelhttps://www.linkedin.com/in/leonnoel/https://100devs.org/📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!Chapters0:00 - A Teacher's Powerful Introduction to Dr. Barb Oakley4:05 - From "I Will Never Learn Mathematics" to Distinguished Professor5:42 - The Single Most Critical Skill in the Age of AI8:12 - How Learning a Language Unlocks Your Brain for Math & Science9:58 - The #1 Mistake We All Make When Learning a Difficult Subject14:30 - The Unconventional Path to Becoming a Professor23:11 - The 2 Brain Modes You MUST Understand (Focused vs. Diffuse) 🤯29:22 - A Modern, Scientific Twist on the Pomodoro Technique32:38 - WARNING: This Popular Study Method is a Waste of Your Time34:18 - The Surprising Problem with "Student-Centered" Classrooms40:12 - Proof That Your Phone is Destroying Your Ability to Focus45:35 - The Neuroscience of Dyslexia & Autism: Your Brain's Secret Superpower51:11 - The Emotional Side of Learning: Dealing with Fear, Shame & Procrastination56:33 - Why Impostor Syndrome is Actually a GOOD Thing1:07:28 - How to Use Sleep to Supercharge Your Memory 😴1:15:17 - The Future of Learning: How AI Will Change Everything1:23:36 - How to Use AI to Learn (Without Cheating Yourself)1:32:32 - Q&A: The Best Way to Create a Daily Structure for Learning1:44:52 - Dr. Oakley's Final Inspiring Message

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• AI That ACTUALLY Ships: JSON, Voice Agents, MCP, and Software Developer Real-World Pitfalls

  What do JSON and conversational AI have in common? They are the glue behind ordering coffee, booking flights, and talking to support. In our tests, about 1 out of 3 replies missed the intent until we enforced structured JSON outputs. In this episode, Danny Thompson and Leon Noel break down how to move from “cool demo” to production systems that route, escalate, and self-audit reliably.SITE https://www.programmingpodcast.com/💡 Sponsor: Level Up Financial PlanningChanging careers or increasing your income? Get financial clarity with Level Up Financial Planning—helping early and mid-career tech professionals secure their financial future. Visit LevelUpFinancialPlanning.com for a free consultation!https://www.levelupfinancialplanning.com/Stay in Touch:📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!Danny Thompsonhttps://x.com/DThompsonDevhttps://www.linkedin.com/in/DThompsonDevwww.DThompsonDev.comLeon Noelhttps://x.com/leonnoelhttps://www.linkedin.com/in/leonnoel/https://100devs.org/📧 Have ideas or questions for the show? Or are you a business that wants to talk business?Email us at [email protected]!What you’ll learn- Why freeform paragraphs fail backends and how JSON fields fix routing- A simple schema pattern: department, sentiment, confidence, reply- Confidence floors that trigger automatic retries before users ever see a response- Context windows: why rules are read every call while context gets dropped- MCP basics and how domain context avoids bad translations and metaphors- Where voice agents work today (predictable conversations) and where they do not- Practical tool choices for text, code, and voice workflows- Real labor impacts, retention insights, and reskill advice- Salary negotiation quick hits: the two lines that matterChapters0:00 JSON as the glue + the 1-in-3 miss0:30 Intro & episode promise1:10 Quick defs — JSON / NLG / NLU / MCP3:00 Why structured JSON beats paragraphs7:36 Confidence scores & auto-retries9:02 Sponsor11:34 Prompts for image/video models that actually work15:01 Context windows & durable rules16:32 Repo trees, PRDs & dev logs to reduce spin20:02 MCP in practice, local dialects & domain knowledge26:03 Voice agents, predictable vs unpredictable conversations32:43 Voice mode as a research partner & model picks33:01 Jobs impact, retention stories & reskilling37:10 Conversational AI 101, coffee shop flow to backend40:05 Connectors & phone/drive-thru stacks (Agora, 11 Labs)46:04 Real-world rollouts, employee retention boost48:13 Call centers & debt collection case study51:27 Predictable vs messy conversations — where AI fails53:24 Career CTA, learn JSON, MCP, voice stacks57:01 Ask Danny And Leon A Question1:07:10 The Developer's Guide To AI

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