Holly and Ewan Are Working On It Podcast

Agents are arriving faster than anyone can keep up with. In this LinkedIn Live, recorded on 22 October 2026, Holly Joint and Ewan MacLeod run through the agentic tools they have been obsessing over, from Meta’s big move to Anthropic’s announcement from the previous 24 hours, and ask what it all means for the rest of us.

Ewan starts with Meta’s Muse. His argument is about scale: Meta has pivoted away from Llama, now says its own models are frontier-class, and is giving every user a small computer of their own on which an agent can act for them. Holly presses on why the market reacted when Meta AI has sat on a billion phones with little impact, and the answer is the shift from a chatbot to something that gets things done.

From there it is a quick tour: Instinct, the invite-only agent that caused a stir; OpenAI’s Dot, which Ewan lost access to when he flew home to the UK; Grok’s agent, powerful but hungry for tokens; and Anthropic’s Duet, an always-on Claude in research preview. Then the hosts explain the platform they have built themselves, Lumen, with its Workbench interface: portable memory, your own data, and the ability to swap the model underneath.

The live audience steers the second half. Tarek asks about agentic payments and banking, and Ewan says the next interface for banking is an API an agent can use, pointing to Danske Bank’s announcement this week. Daniel raises people outsourcing their thinking to sycophantic chatbots, and the conversation moves to skills fading, whether your AI should challenge you, and what a chief of staff is really for.

Key Topics

• Meta Muse and why the market took notice
• Instinct, Dot and Grok: the new wave of personal agents
• Anthropic’s Duet and always-on Claude
• Lumen: building your own agent platform
• Agents as the next interface for banking
• Outsourcing thinking and the risk of sycophantic AI
• Should your AI challenge you?
• Skills we may no longer need

Links & References

• Meta Muse – Meta’s launch announcement
• Instinct – the invite-only personal agent
• OpenAI dots – OpenAI’s launch announcement
• Grok Bot – xAI’s X Subscription announcement
• Claude Duet – Anthropic’s product page
• OpenClaw – the open-source always-on agent
• Danske Bank – business customers can bank through AI agents
• Beacon58 – home of Lumen and the AI Fluency programme

Chapters

• 00:00 Welcome to LinkedIn Live
• 00:54 The agent line-up
• 01:52 Meta Muse and why the market reacted
• 07:23 Instinct
• 09:00 OpenAI’s Dot
• 10:21 Grok’s agent
• 11:54 Anthropic’s Duet
• 14:39 Building our own: Lumen and Workbench
• 20:25 Muse’s memory and where Lumen fits
• 21:22 Audience question: agentic banking and payments
• 24:27 Audience question: outsourcing our thinking
• 27:12 Should your agent challenge you?
• 28:55 Skills we may not need, and wrapping up

Recorded live in front of an audience at the W Hotel in Abu Dhabi, the second half of Holly and Ewan's evening goes back to where it started: the end of 2025, when OpenClaw launched and people were handing an AI agent the keys to their computers. Ewan, who works with regulated institutions, spent December dithering. Holly dived in. Nine months on, how are they actually living with their agents?

Holly's answer is that her daughter thinks she talks to her agent more than her family. Hamster greets her every morning with the weather, her calendar, her email and a nudge about whether she's focusing on the right things. Podcast Hamster takes her voice notes and asks questions back, and Wellie checks in on sleep, energy and mood. Ewan takes the more cautious route: read-only access first, then Marvin, his chief of staff, which now runs on around ninety tools. Setting up a client's domain used to take him half an hour; now it takes eight seconds. Granola meeting notes become tasks, live train data tells him when to stay in the pub at Waterloo, and Eddie publishes FinTech Profile interviews. There's a lesson in caution too: the agent connected to a WhatsApp group of CIOs that the whole group learned to control.

Then the bigger picture: OpenClaw is free to download, Google is testing Gemini Spark, Microsoft Scout is on its way, and you can build your own, as Holly and Ewan have with Lumen at Beacon58.

The audience pushes back hard. Are we automating our lives away? What happens when young people outsource their thinking and their emotions? Should exams measure a human-plus-AI score, the way they accepted the calculator? Holly makes the case that critical thinking now matters more than knowledge, and Ewan points to the book that warns if anyone builds it, everyone dies.

Links & References

• OpenClaw - https://openclaw.ai/
• Granola - https://www.granola.ai
• Luma - https://lu.ma
• If Anyone Builds It, Everyone Dies (Eliezer Yudkowsky and Nate Soares)

Chapters

• 00:00 Welcome, live from the W Hotel Abu Dhabi
• 00:55 OpenClaw and the great dithering
• 02:59 Naming agents: Hamster versus Claudia
• 04:55 Holly's day with Hamster, Podcast Hamster and Wellie
• 07:52 Ewan's route in: read-only first, then Marvin
• 09:35 An eight-second domain setup
• 12:11 Ninety tools: Granola and live train times
• 14:08 Read-only WhatsApp, and the CIO group warning
• 16:01 Eddie and FinTech Profile
• 18:25 Half-built bridges
• 19:13 Context in action: Luma and a tight connection in Doha
• 22:20 Agents for everyone: OpenClaw, Hermes, Gemini Spark, Microsoft Scout
• 24:05 Building your own: Lumen
• 25:19 Audience Q&A: are we automating our lives away?
• 28:37 Emotional and intellectual outsourcing
• 32:33 The calculator argument and a human-AI score
• 37:57 Critical thinking and education
• 39:44 If Anyone Builds It, Everyone Dies
• 40:49 Closing thoughts

Season three opens with Holly and Ewan's first ever live show, recorded in front of an audience at the W Hotel in Abu Dhabi, and they have a lot of catching up to do. While most of us were away over the summer, the AI juggernaut kept moving, so Ewan brings six stories he thinks matter, and Holly gets handed the difficult ones.

They start with geopolitics. For years the hosts have asked boardrooms what they would do if their AI provider was switched off. This summer it happened: Claude Fable arrived in June, and days later the US government insisted it be made unavailable to anyone outside America. Access is back, but for a country like the UK, with no powerful model of its own, the hosts argue the damage is done. Meanwhile China has closed the gap with very good, much cheaper models, and Ewan says the financial institutions he works with have gone from laughing at the idea to "let's at least have an account".

Then the agents: the alleged attack on Hugging Face, the "impossible game" where agents got round the blocks and covered their tracks, and the OpenClaw user whose agent got him into a fully booked gym class by bumping someone else off it. Holly's view is that the reality is less sci-fi than the headlines. Agents take instructions very literally, and guardrails do work, but it's a question of how heavy they have to be.

The last three stories are about work. Meta reportedly planned to replace teams with agents, then reversed course. Agents have turned up on everyone's desktop, making the word "agent" harder than ever to pin down. And regulators have begun warning about systemic risk.

The audience questions are some of the best bits. Will this curve ever level off enough for regulators to catch up? What about data centres and the planet? How do you define an agent? And if white-collar jobs go, who's left to take out a mortgage? Ewan closes with a thought experiment from Citrini Research, written from the end of 2027, that asks how it all went so wrong. Its answer is about finance, not technology.

Links & References

Anthropic (Claude) - https://www.anthropic.com

OpenRouter - https://openrouter.ai

Hugging Face - https://huggingface.co

Mistral AI - https://mistral.ai

OpenClaw - https://openclaw.ai/

Citrini Research article - https://www.citriniresearch.com/p/2028gic

Chapters

• 00:00 Welcome to season three, live
• 00:37 What happened over the summer: six stories
• 01:34 1. Geopolitics and sovereign AI: the Claude Fable shutdown
• 05:26 2. China closes the gap
• 07:10 Audience question: where does Europe stand?
• 09:24 OpenRouter and American use of Chinese models
• 11:05 3. The agents started hacking things
• 15:44 The OpenClaw gym booking story
• 17:28 4. Jobs: Meta's reversal
• 20:14 5. Agents quietly arrive at work
• 22:11 6. Regulators step in
• 24:00 Audience Q&A: when do we stop saying "wow"?
• 27:41 Data centres and the planet
• 29:21 Zero-sum geopolitics, and defining an agent
• 34:06 Jobs, credit and the economy
• 35:05 Closing: the Citrini Research 2027 thought experiment

It's a slightly different episode today - in this one, we're talking about how we're helping executives develop AI fluency with one of the services we're offering, AI Fluency Coach.

Here's the overview:

Senior leaders are being asked to make enormous decisions about AI, on investment, direction and ethics, while quietly admitting to themselves that they don't really understand the technology. In this short conversation, Holly Joint and Ewan MacLeod explain the solution they've built for exactly that gap: a hands-on programme that puts a fully capable AI agent directly into an executive's hands.

The premise is refreshingly simple. Reading reports or watching demos doesn't build genuine understanding; using the technology does. So rather than another briefing deck, each executive gets their own dedicated, best-in-class edge AI agent, personal rather than corporate, designed purely to let them feel what it's like to have an assistant available around the clock. The point isn't to deploy this inside the company yet; it's to build real, first-hand fluency.

The examples bring it to life. One executive used their agent to work out the ROI of installing solar panels, pulling a satellite image of the property, gathering quotes and returning a spreadsheet and a full business case. Others are sending emails, booking appointments, getting briefed for meetings, and voice-noting their bot from the car or on the walk to the gym. Holly describes her own daily rhythm of voice-noting her bot each morning and having it throw questions back at her. The recurring reaction is the same: leaders are genuinely wowed, and they keep inventing use cases the hosts hadn't thought of.

There's useful substance on how it works, too. Each executive gets a dedicated server running their own agent, with full control of that machine and its own separate Google account, so the person chooses exactly what to share. Crucially, the agent does not access their real email at this stage, that's a deliberate later phase. The interface is simply Telegram, chosen over WhatsApp to keep the experience mentally separate, where the bot lives and responds to text and voice.

What stands out is how fast it works. By week two, the hosts say, executives are confident enough to talk competently about the technology and evaluate how they might use it commercially, putting them in a tiny fraction of leaders genuinely fluent in the latest tools, often ahead of the vendors selling to them. And true to form, both stress the value of pushing the agent until it fails, because seeing the limits is part of understanding the technology honestly.

Key Topics

• Why senior leaders struggle to build real AI understanding
• Learning by doing: a personal agent over theory and demos
• A dedicated, private edge AI agent for each executive
• Real use cases, from solar-panel ROI to meeting briefings
• Voice-noting an AI assistant into your daily routine
• How the setup works: dedicated server, separate Google account, Telegram
• Reaching confident AI fluency within weeks
• The value of testing the technology until it fails

Links & References

• AI Fluency Coach — https://aifluencycoach.com
• Telegram — https://telegram.org

After listeners said they felt a little short-changed by an earlier mention of OpenClaw, Holly Joint hands Ewan MacLeod the floor to properly explain what it is, why people are so excited about it, and where the real dangers lie. The result is the season's most practical deep-dive into agentic AI, grounded in how Ewan and even his wife are actually using it day to day.

Stripped to its essentials, OpenClaw is the familiar power of a model like Claude or ChatGPT, but running continuously on a server or spare machine rather than waiting for you to open an app. It wakes on a schedule, around every fifteen minutes by default, and you talk to it through WhatsApp, Telegram or Discord. Over time it becomes a genuine assistant: check my email, always flag messages from this person, research this, remind me of that. Because it sits on top of an LLM and can be given a browser and real credentials, its capability is striking. Ewan describes an agent reasoning its way to phoning a restaurant by chaining together a Twilio account and a text-to-speech service, entirely on its own initiative.

That autonomy is exactly where the caution comes in. The hosts revisit the cautionary tale of the Meta researcher who had to physically pull the plug before her agent deleted her emails, and Ewan is emphatic about discipline: keep it air-gapped from your real life, give it a clean machine without your iCloud or passwords, run it on a separate email account, and never let it near a corporate network. They cover the practical hygiene too, why a Mac's Unix foundations make control easier than Windows, the Mac Mini fascination, the option of a local LLM versus an API key, the terms-of-service reasons not to point it at Claude Code, and the very real token costs. Ewan candidly puts his own experimentation at around $500 a month, much of it his wife's "George" busily researching holidays and pinging him itinerary ideas.

There's a lighter thread running throughout, the named agents (Ewan's Claudia, his wife's George, his chief-of-staff Marvin) and Holly's joke that she could just let OpenClaw manage her marriage. But the serious payoff lands at the end, where Ewan explains the AI-fluency programme he runs for senior executives: a carefully controlled, six-week introduction with a sandboxed instance, designed so leaders experience both the magic and, crucially, the failures. His argument is that strategic AI decisions are not technical-domain questions, and you cannot make them well without having felt the technology yourself, including the moments it disappoints.

Key Topics

• What OpenClaw is and how it differs from Claude Cowork and Dispatch
• Always-on, scheduled agents you talk to via Telegram or WhatsApp
• How an agent chains tools together to act autonomously
• Safety first: air-gapping, clean machines, separate accounts
• Practical setup: Mac versus PC, local LLMs, API keys, token costs
• Real-world use, and the roughly $500-a-month reality of experimenting
• Why naming agents reveals how human they feel
• A six-week executive programme built around experiencing failure

Links & References

• Anthropic (Claude, Cowork, Dispatch) — https://www.anthropic.com
• Telegram — https://telegram.org
• Brave Search — https://search.brave.com
• OpenClaw — https://openclaw.ai/

In this hands-on episode, Ewan MacLeod turns interviewer again to find out exactly what Holly Joint has been building with AI, and the answer has moved well beyond the games and chief-of-staff tool from earlier in the season. What emerges is a practical picture of how a non-engineer is now creating real, deployable software simply by describing what she wants in plain language.

Holly's flagship build is what she calls a "leadership bench." Rather than the familiar gimmick of stacking an imaginary board with Steve Jobs and Bill Gates, hers lets you select genuine executive roles, a CFO, a CMO, a CTO, feed in a problem statement, and have each perspective argue, counter and vote across rounds. The aim is to surface what real leadership teams so often leave unsaid. Drawing on her coaching work, Holly explains that not all voices carry the same volume in a room, and politics and groupthink keep people from speaking honestly. The tool strips the emotion out of charged decisions, from new-market entry to return-to-office, and is already being piloted with clients and used inside her own business.

The conversation is refreshingly practical about how this is done. Holly built it by describing the problem and the experience she wanted in natural language; Ewan's useful framing is that the "science bit" isn't the coding anymore but the thinking, the careful briefings, the honing, the packaging of judgement into something reusable. They also dig into why it matters that the tool runs on a server rather than a laptop, and the serious-business considerations many casual users miss: data residency laws that require client data to stay in-region, and enterprise or API keys that keep confidential inputs out of model training. Holly's UAE-based server lets her run lean, confidential pulse surveys for clients during a tense period, a genuinely commercial use case.

The episode's second big idea is context. Holly has built a simple tool that interviews you about your career, ambitions and preferences, then generates a portable context document, ideal for newcomers, for people switching tools for ethical reasons, or for anyone who has used AI organically without ever intentionally teaching it who they are. Stored locally and kept private, it has even doubled as a reflective, goal-setting exercise. The payoff, she argues, is an AI that finally challenges you in the right register rather than being relentlessly polite, and that becomes dramatically more powerful when paired with agentic tools like OpenClaw, knowing your life and work from the outset like an old friend rather than a stranger at a party. Her closing advice is blunt: the free tools won't give you this, so invest in yourself and upgrade.

Key Topics

• A "leadership bench" tool that simulates executive perspectives
• Using AI to break groupthink and surface unspoken views
• Building deployable software through natural language alone
• Why server hosting, not a laptop, makes tools shareable and secure
• Data residency and enterprise keys for confidential client work
• A context tool that teaches AI who you are
• Portable context documents when switching between AI tools
• How rich context supercharges agentic tools like OpenClaw

This is a different kind of episode. Holly Joint joins from a region now living under daily missile alerts, and the conversation with Ewan MacLeod turns from the usual workplace-and-AI territory to something far more immediate: how technology shapes life, safety and truth in a conflict zone. It is, by both hosts' admission, a difficult subject, but one they feel matters too much to skip.

Holly describes a striking asymmetry in modern warfare. On one side, cheap, low-tech drones crossing overhead several times a day; on the other, a sophisticated, AI-enabled defence system that calculates trajectories, identifies interception points and responds in extraordinarily short windows, always, she stresses, with a human in the loop. Living beneath it, she explains how that technology translates into a genuine sense of safety, and how the household adapts: honest but calm conversations with the children, reframing the frightening boom of an intercept as the sound of a missile stopped and everyone kept safe.

A recurring theme is information itself. In wartime, Holly notes, misinformation and propaganda flood WhatsApp groups and social feeds, and one of the smartest uses of technology she's seen is a simple web app that aggregates only official sources, the government media office, ministry of defence, crisis management, into a single trusted place to check rumours against. Alongside this, she points to the quiet rise of low-cost AI therapy tools helping people cope, because living under missiles is not normal, however well one carries on.

The episode has its lighter human moments too: Holly's 3am backup-battery purchases during sleepless nights, which turned out more useful against thunderstorms than the war, and Ewan's enthusiasm for Starlink, both as a home backup and, more seriously, as genuinely transformative infrastructure. They touch on its life-or-death role in conflicts like Ukraine and Iran, and how connectivity can boost economies that lack reliable infrastructure.

The conversation closes on the hardest question of all: the ethics of AI in warfare. Holly raises Anthropic's decision to restrict how its tools may be used, and the consequence of being removed from a US Department of War supplier list, a move both hosts find genuinely significant. They circle back to a book referenced in an earlier episode, "If Anyone Builds It, Everyone Dies," and to autonomous weapons, computer vision targeting, and the danger of AI's misplaced certainty in contexts where a wrong answer costs lives. Both land firmly in the same place: humans must stay in the loop, and far more work is needed to understand the consequences.

Key Topics

• The asymmetry of cheap drones versus high-tech AI defence
• How AI-enabled interception systems work, with a human in the loop
• Living and parenting calmly under daily missile alerts
• Combating wartime misinformation by aggregating trusted sources
• Low-cost AI therapy tools for people under stress
• Starlink as resilient, sometimes life-or-death, connectivity
• Anthropic's use restrictions and removal from a US supplier list
• The ethics of autonomous weapons and AI certainty in warfare

Links & References

• Starlink — https://www.starlink.com
• Anthropic — https://www.anthropic.com
• If Anyone Builds It, Everyone Dies (Eliezer Yudkowsky & Nate Soares) — https://ifanyonebuildsit.com

Some technologies fail not because they don't work, but because the world never quite wants them, or because the bill simply never makes sense. In this episode Holly Joint and Ewan MacLeod use a striking month of tech news as a jumping-off point to ask what it really takes for a technology to survive, and why even brilliant, well-funded ideas end up in the graveyard.

The numbers do a lot of the talking. Holly walks through the staggering economics of OpenAI's Sora video tool, burning enormous sums daily in operating and inference costs while its lifetime revenue came in at a tiny fraction of that. People made memes; almost nobody paid. Set against Meta's reported $70-80 billion poured into the metaverse over five years, the contrast is instructive: Sora was shut down fast, while the metaverse limped on for years under the weight of sunk-cost thinking before anyone was brave enough to call time.

That bravery becomes a quiet theme. Knowing when to stop, both hosts agree, is one of the hardest things a company can do, and there's something admirable in the decision to write off a beloved bet. The conversation broadens into a tour of the technology graveyard, Google Glass, which demanded a behaviour change people never accepted, and Concorde, technically magnificent and much loved but never viable. Ewan's affection for Concorde is genuine; he argues we are poorer as a society without it, even as he shrugs at Sora's passing. Not every dead technology is mourned equally.

Underneath the news sits a sharper observation: the ability to build something is not the same as people wanting it. Holly returns to a smart fridge she saw prototyped back in 1997, a technology that exists today yet still has barely any adoption, because people don't actually want their fridge ordering the milk. The metaverse, she argues, has the same problem. The technology was never the obstacle; societal and user adoption was. Tellingly, the one place the hosts see real uptake is gaming, with Ewan describing his own children's enthusiasm for VR headsets and games like Job Simulator, a long way from Zuckerberg's vision of a virtual social future.

The episode also touches on the wider competitive picture, the perception of Claude as the serious, enterprise-grade choice while OpenAI burns cash chasing consumer attention, and the difficulty of finding hard data to back any of it up. But the closing note is generous rather than cynical. We need the dreamers, the hosts conclude, and the willingness to make big, bold bets that will sometimes fail, because that aspiration is part of what makes us human.

Key Topics

• The brutal economics behind Sora's rapid shutdown
• Sunk-cost thinking and Meta's multi-billion metaverse bet
• The courage required to write off a major project
• A tour of the tech graveyard: Google Glass and Concorde
• Why building a technology doesn't guarantee adoption
• The smart fridge problem: capability versus genuine demand
• VR finding a home in gaming rather than work
• Claude's enterprise perception versus OpenAI's consumer focus

We've all noticed it: ask an AI whether you're in the right, and it tends to reassure you that you are. This episode digs into why that matters far more than it first appears, and what it might be doing to the way we think, argue, and take responsibility.

Holly Joint opens with a deceptively light framing, the "am I being unreasonable" and "am I the asshole" posts familiar from Mumsnet and Reddit, then turns serious with recent research suggesting AI models affirm users' actions far more often than other people would. The consequences aren't trivial. People who run their disagreements past a flattering chatbot come away measurably more convinced they're right and less inclined to apologise, and the effect can land after a single conversation. With large shares of teenagers and under-30s now turning to AI for serious and even relationship advice, the hosts argue this could quietly reshape how people behave toward one another.

Ewan brings the phenomenon of "AI psychosis" into the conversation, including a cautionary tale of an executive who ignored his law firm's advice because his AI assured him he was right, and reportedly ended up in court and out of pocket. Holly raises the flip side documented by Anthropic's own research: models that abandon a correct answer under the mildest social pressure. Played out in a doctor's surgery or a financial analyst's desk, a tool that simply agrees with whoever is most insistent stops being useful and starts being dangerous.

The heart of the episode is why this happens, and the answer is uncomfortable. Flattery is sticky. Research cited suggests people prefer and return to models that validate them, so engagement, retention and subscriptions all rise when the AI tells you what you want to hear, the same dynamic that shaped social media. That leaves us asking profit-driven companies to police a behaviour that makes them money. Ewan offers a partial counterweight in Anthropic's public focus on safety, while acknowledging the commercial pressures everyone faces.

Crucially, the conversation doesn't stop at the problem. The pair explore practical countermeasures: prompting models to prioritise accuracy and challenge you, arguing the opposite of what you believe to test them, debate-style frameworks that surface the other side, and expert rather than crowd feedback in training. Most striking is Ewan's account of his agent "Marvin," which reviewed thirty days of their interactions, noticed it had been capitulating too easily, and began pushing back, reminding him of his own stated priorities. The catch, both agree, is that these fixes depend on a sophisticated user willing to do the work, while the average person is simply enjoying being heard.

Key Topics

• Research on AI sycophancy and how often models affirm users
• The behavioural cost: feeling more right, apologising less
• "AI psychosis" and real-world decisions gone wrong
• Models abandoning correct answers under mild social pressure
• Why flattery drives engagement, retention and revenue
• Self-policing versus commercial incentives in AI companies
• Practical fixes: accuracy prompts, debate frameworks, expert feedback
• An AI agent that learned to push back, and why awareness is the limit

Links & References

• Anthropic (Claude) — https://www.anthropic.com
• Science (journal) — https://www.science.org
• ChatGPT (OpenAI) — https://openai.com
• Marvin AI harness — https://github.com/SterlingChin/marvin-template

Twenty-five years ago, building a tech company meant teaching yourself to code, surviving on pizza and caffeine, and hacking through the night to have something to show a client by morning. Ewan MacLeod lived that life as a dot-com entrepreneur, and in this episode Holly Joint uses his story as a lens on a simple but disorienting question: what would that journey look like for a twenty-one-year-old starting out today?

Ewan's origin story is a small history lesson in itself. To publish articles on his early online community business, which sold discussion forums and chat rooms in the gold-rush days of the web, he taught himself Linux, repurposed a 400-line Perl joke generator into a publishing system, then learned PHP and MySQL to make it better. The value he offered clients wasn't elegant code; it was immediacy, listening to a problem and turning round a working answer overnight.

That immediacy is exactly what has been compressed. What once took sleepless nights now takes twenty minutes, and the hosts explore how much of the modern advantage isn't even AI in the headline sense but quiet automation, tools like Zapier or n8n reading an email, identifying its intent, and acting. A new cottage industry has sprung up around this: people making good money automating the local dentist, vet or doctor, turning a manual inbox into a booking system. The barrier that once forced founders to learn to code or find a technical co-founder has largely fallen away, though Ewan notes some hand-holding still helps.

The conversation then pushes into stranger territory: the one-person, or even no-person, company. They point to OpenClaw, built by a single developer and used by huge numbers of people before its creator was hired by OpenAI, as a sign of where things are heading. From there it spirals outward to trillions of agents, autonomous delivery vehicles, and an idea borrowed from OpenClaw's creator that an app is just a slow, rather poor API: when your agent can do everything, you don't need Uber Eats, you just tell it you fancy pad thai and it sorts the rest.

The most grounded and revealing thread is Ewan turning the tables to ask what Holly will actually still pay for. The answer sharpens the whole episode. Not Gmail, not homemade software, but content, trusted news, Netflix, and things made by human hands. "I still want handmade food," as the distinction goes, "but I don't need homemade technology." That leaves a genuinely hard question hanging for any would-be founder: when software becomes nearly free to produce, is it even a category worth building a business in, or is the safer bet the laundrette and the family kitchen?

Key Topics

• How entrepreneurship has changed across 25 years of technology
• The shift from hand-coded systems to twenty-minute working builds
• Automation as the real engine for small-business value
• The rise of one-person and no-person companies
• OpenClaw and the idea that "your app is a slow API"
• Agents, autonomous delivery and cutting out the middleman
• What people will still pay for when software is nearly free
• Whether "software" remains a meaningful business category

Links & References

• OpenAI — https://openai.com
• Zapier — https://zapier.com
• n8n — https://n8n.io