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A third of UK workers say their own organisation gets in the way of them doing good work. Four in ten managers would rather not be managers. So why does L&D keep building interventions that ignore the possible situational causes of poor performance? Robin Hoyle is Head of Learning Innovation at Huthwaite International and has chaired the World of Learning conference for about fifteen years. In this conversation he makes the case that training doesn't stick because the system around it is broken, and that the profession measures what is easy to measure rather than what matters. His answer? Focus on transfer, not completions. Robin chairs the World of Learning Conference at the NEC in Birmingham on 6–7 October, closing the second day with a keynote on AI, adoption and agency. LINKS AND RESOURCES Robin Hoyle at Huthwaite International: https://www.huthwaiteinternational.com/blog/author/robin-hoyle Robin Hoyle on TrainingZone: https://trainingzone.co.uk/author/robinhoyle/ "The performance illusion: why training doesn't stick" (23 July 2026): https://www.huthwaiteinternational.com/blog/the-performance-illusion "Why isn't leadership training making leaders better?" (28 April 2026): https://www.huthwaiteinternational.com/blog/why-isnt-leadership-training-making-leaders-better "2026 in L&D: Transfer and transferability" (6 January 2026): https://www.huthwaiteinternational.com/blog/2026-learning-development-predictions "AI isn't coming for your job" (29 October 2025): https://www.huthwaiteinternational.com/blog/ai-isnt-coming-for-your-job World of Learning Conference & Exhibition, NEC Birmingham, 6–7 October 2026: https://www.learnevents.com/birmingham/conference/programme/ Robin Hoyle, Complete Training: From Recruitment to Retirement (Kogan Page, 2013) Robin Hoyle, Informal Learning in Organizations: How to Create a Continuous Learning Culture (Kogan Page, 2015) Geary Rummler and Alan Brache, Improving Performance: How to Manage the White Space on the Organization Chart (Jossey-Bass, 1990) Ipsos Karian and Box, Work on What Matters — survey of 5,000 UK employees, May 2026: https://ipsoskarianandbox.com/report/work-on-what-matters/ Ipsos Karian and Box, "Are we working on what matters? What 5,000 UK Employees told us" (15 May 2026): https://ipsoskarianandbox.com/insights/are-we-working-on-what-matters-what-5000-uk-employees-told-us/ Fifty years of SPIN, Huthwaite International: https://www.huthwaiteinternational.com/fifty-years-of-spin Subscribe to The Learning Hack: https://linktr.ee/learninghack Watch on YouTube: https://www.youtube.com/@JohnHelmerConsulting

Two-thirds of HR professionals say AI is their top development priority. But only a third of organisations offer any AI training – and fewer than one in five think their leaders are equipped to lead in an AI-enabled environment. So where is the gap, and whose job is it to close it? Erica Farmer is co-founder of Quantum Rise Talent Group, host of the AI for the Average Joe podcast and author of AI for People Professionals (Kogan Page, 2026). In this conversation she argues that organisations are rolling out AI the way they rolled out every HR system before it, treating people as tech users rather than as people. She also has a challenge for L&D, which she thinks is waiting for HR to tell it what to do. Along the way: writing a book with AI during a backlash against AI, why the tools push you to work their way, the CIPD skills gap, AI literacy and prompting, and what a self-driving Mustang says about human over-confidence. Also: Are HR and L&D in the same place on AI? Double down on what you're great at Co-writing with AI, and the neurodivergent workflow Slop and the AI backlash The CIPD gap: individual capability or organisational readiness? Leaders as practitioner, communicator and strategist Stress, burnout and AI 'golden time' Why prompting still matters LINKS AND RESOURCES Erica Farmer on LinkedIn: https://www.linkedin.com/in/ericafarmer/ [verify handle] AI for People Professionals (Kogan Page): https://www.koganpage.com/hr-learning-development/ai-for-people-professionals-9781398625990 EricaFarmer.AI (speaking): https://ericafarmer.ai/ L&D Global Sentiment Survey 2026 (Donald H Taylor): https://donaldhtaylor.co.uk/research_base/global-sentiment-survey-2026/ CIPD, AI in the workplace: https://www.cipd.org/en/topics/artificial-intelligence-workplace/ Erica's Training Journal piece on writing the book: https://www.trainingjournal.com/2025/content-type/features/my-book-ai-for-people-professionals-was-a-human-first-experiment/   CONNECT WITH LEARNING HACK LinkedIn: linkedin.com/in/johnhelmer YouTube: www.youtube.com/@JohnHelmerConsulting X: @johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Website: learninghackpodcast.com

Did science fiction predict AirPods? Neuralink? The death of God? For this final episode of Season One, John Helmer and Ezri Carlebach give you what hacks call a listicle: three transcendently significant things prefigured in science fiction that definitely came true — and three that didn't. Or haven't yet. Prediction, as Niels Bohr said, is very hard. Along the way: Thirteenth-century flying machines Victorians watching live war coverage on flat-screen TV elearning before there was elearning Verne, Wells, jetpacks, flying cars, prediction markets, transporter beams, universal nudism and Octavia Butler's uncannily detailed vision of the Age of Trump. That's a wrap on season one. Let us know what you've enjoyed — and what you'd like to hear in future episodes. All suggestions considered. Connect with The Learning Hack: LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Substack: @learninghack Instagram: @tech.imaginarium Website: learninghackpodcast.com Listen and watch: https://linktr.ee/learninghack Music by Nick Dwyer recording as Flintet. The Tech Imaginarium is a Learning Hack podcast, produced and hosted by John Helmer and written by John Helmer and Ezri Carlebach.

How a teenage girl's waking dream birthed what is (probably) the first science fiction novel – and in the process gave the world its most enduring image of technology gone wrong. This time we're coming for the myth, the curse, the cliche that is Frankenstein. John Helmer and Ezri Carlebach climb up the tower, point the lightning conductor to the heart of the storm, and attach electrical cables to the neck-bolts of that fearful thing on the slab. Yes, it may be 200-years old but ... it's alive! They walk through the original 1818 plot — stranger and bleaker than the films — weigh the long-running argument over whether it really counts as science fiction, and trace the monster's afterlife from the 1910 Edison short and James Whale's 1931 classic to Boris Karloff, Mel Brooks, Eddie Van Halen's "Frankenstrat", Guillermo del Toro ... and beyond. In this episode: What really happened at the Villa Diodati in 1816? The radical parents and a childhood shadowed by death that made Mary Shelley Born in the age of revolutions: Enlightenment values battles alchemy and the occult How two Brits, James Whale and Boris Karloff, created a look for the creature in their famous 1931 film that resonated through a thousand sequels, rip-offs and pisstakes Did Mary Shelley predict the death of God? Connect with The Learning Hack: LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Substack: @learninghack Instagram: @tech.imaginarium Website: learninghackpodcast.com Listen and watch: https://linktr.ee/learninghack Music by Nick Dwyer recording as Flintet. The Tech Imaginarium is a Learning Hack podcast, produced and hosted by John Helmer and written by John Helmer and Ezri Carlebach.

Can the future of an entire civilisation be calculated like the behaviour of gas molecules? In the second of two episodes on Isaac Asimov, John Helmer and Ezri Carlebach turn from his robots to his other great franchise — the Foundation saga — and the seductive idea at its heart: psychohistory, a fictional science that claims to predict the fate of galactic empires. From a Gilbert and Sullivan libretto opened at random to Apple TV's billion-dollar adaptation, this is a conversation about how one pulp idea grew into a cornerstone of science fiction and why its questions about prediction, determinism and power feel uncomfortably current. In this episode: The origins of Foundation — Asimov, his editor John W. Campbell, and the Gilbert and Sullivan operetta that inspired a galactic empire The original trilogy (Foundation, Foundation and Empire, Second Foundation), Hari Seldon, psychohistory and the Mule How Asimov was pushed by Doubleday into the prequels and sequels — and how he retrofitted Foundation into his robot universe Two adaptations compared: the 1973 BBC Radio dramatization and Apple TV's contemporary series The ideas behind the saga — Gibbon, Spengler, Toynbee, and the long-running argument over Marx and Hegel Prediction as power — from Carissa Véliz's work to prediction markets and accelerationism Asimov the man: his later fame, his legacy, and his failings Connect with The Learning Hack: LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Instagram: @tech.imaginarium Website: learninghackpodcast.com Listen and watch: All links: https://linktr.ee/learninghack Next time: Frankenstein — Mary Shelley's fever dream and the most enduring image in tech

In 1942, a 22-year-old chemistry student and part-time writer set down three short rules for how a fictional robot ought to behave. His aim was to kill off the lazy "robot-as-Frankenstein-monster" cliché. More than eighty years later, real engineers, real ethicists and real lawmakers are still arguing about them. This is the first of two episodes on Isaac Asimov — one of the "big dogs" of science fiction whose output ran to some five hundred books. John Helmer and Ezri Carlebach take on the most enduring part of that legacy: the Three Laws of Robotics. The Laws went on to power nine linked short stories in I, Robot, several films, hundreds of academic papers, and an argument about AI safety that shows no sign of ending any time soon. In this episode: The man and the output Robots before Asimov I, Robot as nine thought experiments Susan Calvin — one of SF's first great female scientists The Three Laws and the trolley problem Coming next: Foundation Links and resources: Website: techimaginarium.co.uk Instagram: @tech.imaginarium Watch on YouTube: https://www.youtube.com/@JohnHelmerConsulting Music by Nick Dwyer recording as Flintet. The Tech Imaginarium is a Learning Hack podcast, produced and hosted by John Helmer and written by John Helmer and Ezri Carlebach.

Every genre has a shadow canon — the writers who don't make the syllabus, don't sell out on Amazon, and rarely get the Netflix series. In science fiction, that shadow canon is where some of the most intellectually adventurous, politically serious and formally daring work of the twentieth century was done. Having opened the series with the big names — Wells, Verne, Poe, the Mount Rushmore of the genre — John and Ezri jump forward to the late 1960s and 1970s and turn to five authors most listeners won't know: Kate Wilhelm, Joanna Russ, John Sladek, John Brunner and Christopher Priest. Feminist SF, satirical SF, dystopian SF set in a Britain going to the dogs. The thread that connects them is "prescience", a word that keeps coming up. Were these writers really predicting the future – or just paying close enough attention to the present? In this episode: Why 1969 makes such a strange hinge point — Apollo 11 and the realisation of Goddard's cherry-tree dream, set against the assassinations of 1968, Vietnam, Prague, Altamont, and the first wave of environmental science Kingsley Amis, New Maps of Hell, and the New Wave: Moorcock's New Worlds, Ballard's "inner space", and SF's discovery that it could not avoid politics Kate Wilhelm — Hugo, Nebula and Locus winner for Where Late the Sweet Birds Sang, a co-founder of the Clarion Writers' Workshop who is now better known as a mystery writer Joanna Russ — The Female Man, written in 1970 but unpublished until 1975, and How to Suppress Women's Writing; a Westinghouse Science Talent Search finalist who chose literature as her weapon John Sladek — the satirist whose robot in Tik-Tok has had its "asimov circuits" go on the blink, and whose hoax book on a thirteenth sign of the zodiac proved people will believe anything stated with enough confidence John Brunner — the "Club of Rome Quartet", the novel that coined "worm" for self-replicating code, and Stand on Zanzibar, set in 2010 and unsettlingly familiar by the time we got there Christopher Priest — Fugue for a Darkening Island and A Dream of Wessex, the racial framing Priest himself later grappled with, and The Prestige (with David Bowie as Tesla) The big question under all of it: what is the difference between prescience and prediction — and is it significant that "prescience" contains the word "science"? Links and resources: Website: techimaginarium.co.uk Instagram: @tech.imaginarium Watch on YouTube: https://www.youtube.com/@JohnHelmerConsulting Music by Nick Dwyer recording as Flintet. The Tech Imaginarium is a Learning Hack podcast, produced and hosted by John Helmer and written by John Helmer and Ezri Carlebach.

A hundred years ago this spring, a magazine called Amazing Stories hit the newsstands and — almost by accident — gave a name and a shape to the genre we now call science fiction. Its publisher, Hugo Gernsback, was an immigrant electrical engineer, visionary and relentless self-promoter. He wanted his magazine to delight and enthrall – but also to educate. In this opening episode of The Tech Imaginarium, John and Ezri go back to 1926 to ask why this peculiar pulp magazine matters — and why its mix of techno-optimism, prophetic vision and dystopic warnings still echoes through the way we talk about technology today. In this episode: Hugo Gernsback: Luxembourg-born inventor, publisher of Amazing Stories, and author of stories under at least seven anagrams of his own name The strange scientific weather of 1926 — electrification, mustard gas, Einstein, Schrödinger and Hubble — and why it primed the public for "scientifiction" The first issue's contributors: Wells, Verne and Poe in one corner; George Allan England, G. Peyton Wertenbaker and Austin Hall in the other Robert Goddard, H.G. Wells and the through-line from pulp magazines to the Apollo Moon launches Why Gernsback's reputation was contraversial — paying writers poorly, exaggerating circulation, etc. The tropes Amazing Stories planted that we're still living with Links and resources: Website: learninghackpodcast.com Instagram: @tech.imaginarium Watch on YouTube: https://www.youtube.com/@JohnHelmerConsulting Music by Nick Dwyer and Flintet. The Tech Imaginarium is a Learning Hack podcast, produced and hosted by John Helmer and written by John Helmer and Ezri Carlebach.

In 1983, Isaac Asimov predicted that computers would let every person learn what they wanted, in their own time, at their own speed. Forty years on, that vision is more or less the world we live in. So what else might science fiction have to tell us about the future we're already inside? Welcome to The Tech Imaginarium — a new six-part series exploring how science fiction made the modern world. Co-hosts John Helmer and Ezri Carlebach introduce the season ahead, the texts and authors they'll be reading as "skewed mirrors" of our technological present, and why now is exactly the right moment to be paying attention to SF.   In this episode: Asimov's startlingly accurate 1983 prediction about computer-aided learning Why science fiction is a form of learning, not just entertainment — Stephen Baxter's "skewed mirror" A first look at the six-episode season: Amazing Stories at 100, five foundational SF authors, two episodes on Asimov, Mary Shelley's Frankenstein, and the awkward question of whether SF predicts the future   Links and resources: Website: learninghackpodcast.com Instagram: @TechImaginarium Watch on YouTube: https://www.youtube.com/@JohnHelmerConsulting   Music by Nick Dwyer and Flintet. The Tech Imaginarium is a Learning Hack podcast, produced and hosted by John Helmer and written by John Helmer and Ezri Carlebach.

Augmented Workforce, Learning at the Frontline and the Destiny of L&D. For a long stretch, you could skip Learning Technologies for a year and miss almost nothing. Not this year. AI has stopped being something L&D is piloting and started being something the field is rebuilding around — and the conversation at LT26 had a sharper edge for it. In this season finale, John brings back five voices from the show floor and the studio to map what's actually changing: the augmented workforce, the 80% of workers L&D has long ignored, the readiness question nobody wants a straight answer to, the maturing of content into context, and the generational lens of a 30 Under 30. The destiny of L&D, in other words — sketched from five different angles, while the ground is still moving. Guests, in running order Giovanni Giamminola — AI advisor and author of The Augmented Manager; opening keynote speaker at LT26. The augmented workforce thesis: humans plus AI plus AI agents, and the cognitive shift that demands of management. JD Dillon — Founder of LearnGeek; former CLO at Axonify; author of The Frontline Enablement Playbook (out the week the episode airs). On the 80% of the workforce L&D conferences forget about. Alicia Sanchez — Chief AI Officer at MPF Federal LLC; LT26 panellist on future-proofing L&D. On AI readiness — organisational and workforce — and the failure modes at both extremes. Cheryl Clemons — CEO and co-founder of StoryTagger. On the show's themes from a vendor's chair: content to context, evidencing impact, and whether storytelling has had its day as a learning modality. Matt Caldwell — People Experience and DEI at Axon; LT26 30 Under 30 cohort. The generational lens: privacy, data, bias, and what younger workers actually feel about giving themselves to AI tools. In this episode The augmented workforce — humans, AI, and AI agents working together, and what that means for management itself Why 80% of the global workforce is frontline or deskless, and almost no L&D budget reflects it The two-track AI readiness question — organisational and workforce — and the trap of "we're getting ready" as a permanent excuse Content to context: AI maturing the L&D conversation at both ends of the learning programme A generational read on AI, privacy and bias from inside the workforce that grew up with the technology The destiny of L&D, sketched from five angles while the ground is still moving Links and resources Giovanni Giamminola — The Augmented Manager: How AI Makes Management More Effective, Creative and Strategic (2025) JD Dillon — The Frontline Enablement Playbook (2026); LearnGeek; the enabled newsletter Alicia Sanchez — Why Readiness Is Shaping the Future of Work (Learning Guild) Cheryl Clemons — StoryTagger Matt Caldwell — Axon; LT26 30 Under 30 cohort (Nigel Paine)   CONNECT WITH LEARNING HACK LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Website: learninghackpodcast.com Coming next on this feed The Learning Hack returns for a new season in September. But the feed isn't going quiet over the summer — John launches a brand-new podcast on Tuesday 26 May 2026: The Tech Imaginarium — How Science Fiction Made the Modern World, co-hosted with writer and consultant Ezri Carlebach. Six episodes, weekly, into this same feed. More at learninghackpodcast.com/tech-imaginarium.

Your organisation has probably spent years building a learning library. Courses, videos, SCORM files, PDFs — hundreds of them, living in the LMS or scattered across SharePoint. You can enrol in them. You can sit through them. What you can't do is ask them a question and get an answer in seconds, at the moment you actually need one. The knowledge is there. It just isn't retrievable. That's the problem Mike Alcock, founder of Talvi, has set out to solve. In this episode, Mike takes John through how Talvi works. They also cover Mike's own unlikely route into learntech: a Civil Engineering degree at Sheffield, a detour through an insulation factory in Newcastle, and three successive software businesses each arriving ahead of the market. And they have a searching conversation about what tools like Talvi mean for the LMS and for the instructional designer — neither of whom emerges entirely unscathed. Is the technology now genuinely good enough to make learning in the flow of work a practical reality, rather than a conference agenda perennial?.   TIMESTAMPS 00:00 - Start 02:14 - Intro 04:15 - What is Talvi for? 16:20 - What's the journey for a learning leader adopting Talvi? 20:47 - Mike's story: from civil engineering to learntech 30:19 - What will tools like Talvi do to the LMS? 39:50 - Explanation of terms: RAG, vector databases… 49:01 - End   CONNECT WITH LEARNING HACK LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Website: learninghackpodcast.com

What does it take to change how an industry works — and what happens when it doesn't change fast enough? Lars Hyland has been asking that question for thirty years, from the early days of interactive multimedia through nearly a decade leading EMEA for Totara Learning, and now at Enlytning, an AI-powered platform helping small businesses close the gap between policy and practice. In this conversation, John and Lars go back to the beginning — to the Epic days, when the e-learning model that now dominates the industry was taking shape around them — and trace a career-long argument about the one thing L&D keeps getting wrong.   They cover the founding of Retenda in 2010 — a learning reinforcement platform built on spaced repetition, a decade before the category existed — and why good timing isn't enough if the market isn't ready. They get into the Totara years, open source as a power relationship, and the honest tension in spending nearly a decade championing infrastructure you know is being misused. And they dig into AI: not the conference version, but the harder question of whether the industry is using it to fix a broken model or just to run the broken model faster. Lars's phrase for the latter — faster garbage in, garbage out — is both a provocation and a diagnosis.   Lars has a view on what he thinks good actually looks like. The question is whether the industry is willing to build it.   TIMESTAMPS 02:12 - Intro 05:05 - The formative years of elearning 17:59 - Why did he found Retenda? 21:35 - The Totara years 25:53 - What happens to open source tech when it goes commercial? 30:21 - Enlytning 40:26 - Compliance & HR 52:17 - Does the SaaS model still have a future? 57:51 - A way to cut down duplication in course catalogues? 01:08:51 - End   CONNECT WITH LEARNING HACK LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Website: learninghackpodcast.com

What if the ideas that L&D has been nodding at for thirty years are finally about to become unavoidable? Bob Mosher has spent his career arguing that training and performance are not the same thing — and that building courses, however well-designed, only meets two of the five moments when people actually need to learn. The other three happen in the workflow, at the point of need. Most of the profession has agreed with him in theory. Rather fewer have changed what they do.   In this conversation, John and Bob catch up on how generative AI is changing that picture. Bob describes what AI is actually doing inside live workflow learning projects right now — including a headline figure on development time that stopped John in his tracks — and explains why the digital coach, not the course, is becoming the central deliverable. They also dig into the risks: what happens when AI accelerates the wrong thing, why L&D needs a seat at the IT table before it's too late, and what it means to be a performance architect rather than a training order-taker in an AI-assisted world.   The boulder, Bob says, has been going uphill for a long time. He thinks it's about to roll back. This episode is about what happens when it does.   TIMESTAMPS 00:00 - Start 01:55 - Intro 04:27 - The five moments of need 08:14 - How has AI changed the conversation about workflow learning? 10:44 - How does AI save time? 24:07 - Risks to workflow learning from AI 31:42 - Has AI caused a rethink in practice? 40:19 - Workflow learning impact 53:38 - End   CONNECT WITH LEARNING HACK LinkedIn: https://linkedin.com/in/johnhelmer X: https://x.com/johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Website: https://learninghackpodcast.com

Does L&D know where it's going? What separates the L&D functions that genuinely move organisations forward from those that stay busy but never quite shift the dial? That question has driven Laura Overton's research for over two decades — and it sits at the heart of The L&D Leader, the new book she co-authored with Michelle Ockers. Their answer, drawn from more than ten thousand L&D professionals and two hundred learning leaders, points not to new tools or models, but to something older and harder to teach: the ability to read the organisation, sense its currents, and navigate your own way to somewhere that matters.   In this episode John talks with Laura and Michelle about the ideas behind the book, which opens with the extraordinary story of the ancient Polynesian navigators — people who crossed 2,500 miles of open ocean without a compass or a clock. They discuss the lasting legacy of the pandemic for L&D, why two decades of research on workplace learning strategy show surprisingly little change in how most functions operate, and the risk that chasing the latest tool or model is actually damaging L&D's ability to drive real value.   And then there's the question that sits underneath all the talk of L&D maturity and business alignment: when we talk about driving value through learning, who exactly is that value for?   TIMESTAMPS 00:02:44 - Intro 00:05:55 - What was the genesis of the book? 00:10:04 - The collaboration — how Laura and Michelle came to write together 00:13:29 - Legacy of the pandemic for L&D 00:16:10 - Was the pandemic a 'golden period' for L&D? 00:19:42 - What are they telling people in The L&D Leader? 00:30:00 - The Polynesian navigators — and what they mean for L&D leadership 00:39:09 - Is technology causing 'skill fade' in L&D? 00:41:42 - How has the L&D community changed over two decades? 00:50:55 - Who gets the value from workplace learning — the learner or the stakeholder? 01:02:58 - End   CONNECT WITH LEARNING HACK LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Website: learninghackpodcast.com

The results of the 2026 Global Sentiment Survey are out — and the mood in workplace learning is uneasy. In this episode, John speaks with Donald H. Taylor about AI's "hangover moment," rising pressure on L&D teams, diverging regional trends, vendor anxiety, and what showing value really signals this year. Is this a temporary wobble — or a structural shift in what L&D is for?   Timestamps 00:00 - Start 02:21 - Intro 04:14 - Overview of this year's GSS 12:50 - Metaverse and virtual environments 21:59 - Opportunities and Challenges of AI 26:49 - More US respondents this year? 28:33 - Global differences in vibe? 33:46 - Personalisation and individualism 36:09 - New vs returning respondents 41:04 - The challenge of technology 52:47 - End     Connect with Learning Hack LinkedIn: linkedin.com/in/johnhelmer X: @johnhelmer Threads: @jphelmer Bluesky: @johnhelmer.bsky.social Website: learninghackpodcast.com