What happens when AI can do the work, but you haven’t had the years of experience needed to know if the work is any good?

James “JP” Poulter explains why job obsolescence isn’t only about losing jobs. It’s also about what happens when young people lose the formative years where they learn their craft, build character, and learn how to work with other people.

James is an AI specialist, founder of Vixen Labs, and author of AI at Work. He spent 8 years focused on AI and previously worked on emerging platforms and social media innovation at LEGO.

He explains:

• Why the first 5 years of work are about more than learning a job
• Why AI could disrupt character formation for younger workers
• Why we need the wisdom of people who worked before AI
• Why AI has knowledge but not wisdom
• Why every profession has its own language and why that gives you an advantage with AI
• Why knowing how to prompt AI isn’t the same as knowing your craft
• Why FOJO, the fear of job obsolescence, is already shaping how people use AI

(00:00:00) Intro
(00:00:53) Who Is James “JP” Poulter?
(00:02:17) From Social Media to AI
(00:03:41) How AI Is Changing Communication
(00:06:03) Why Bad AI Experiences Destroy Trust
(00:09:01) Do Different Generations See AI Differently?
(00:10:04) Why Gen Z Is Worried About Learning the Craft
(00:11:16) Will Junior Jobs Disappear?
(00:12:14) Which Jobs Are Most at Risk From AI?
(00:15:18) Why We Need Character Formation at Work
(00:17:27) Do Businesses Have a Responsibility to Hire Young People?
(00:20:50) Why AI Adoption Isn’t About Age
(00:23:19) Why Mindset Matters More Than Age in AI
(00:26:03) Cyborg vs Centaur: How We Work With AI
(00:28:03) Treating AI as a Co-Worker, Not Gospel
(00:30:10) What Happens to Your Value When AI Does It Fast?
(00:32:14) Who’s Responsible for AI Safety?
(00:38:49) Are AI Chatbots Designed for Affection?
(00:39:56) FOMO vs FOJO: Fear of Missing Out vs Job Obsolescence
(00:41:46) Which Roles Will Stay Safe in the AI Era?
(00:44:54) How AI Can Elevate Human Creativity
(00:46:21) Why Industry Language Gives You an Edge
(00:50:44) Why Foundational Skills Matter More Than Ever
(00:51:14) What Is a Full-Stack Professional?
(00:55:24) Why Wisdom Outvalues Data
(00:59:03) Creative Resistance vs Complaining About AI
(01:01:13) AI Bias, Global Perspectives, and Local LLMs
(01:04:06) How to Future-Proof Your Career
(01:06:45) Why Voice Notes Are the Ultimate Way to Prompt
(01:10:54) How Organizations Should Roll Out AI
(01:15:45) Avoiding AI Burnout as an Entrepreneur
(01:16:36) The Best Career Advice JP Ever Received
(01:18:13) What JP Believes Now That He Didn't 5 Years Ago
(01:19:17) The Hardest Business Lesson and How It Changed Him

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AI At Work Book

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Building AI without watching what's coming next.

Patrik Kägu has seen it happen. A company that's relevant today can be gone next week when a faster model drops or a cheaper solution launches.

In this clip he breaks down why product market fit in AI is still unsettled and why the bigger risk is assuming you have time to figure it out.

Watch now on YouTube or listen wherever you get your podcasts 🎙️

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Fredrik actually started out wanting to be an airline pilot before he switched paths and went to Chalmers to study engineering. It wasn't until he got into consulting, though, that it really clicked for him: code on its own doesn't mean much if you don't actually get the business problem you're trying to solve.

Today he's a CTO leading a senior engineering team, and he decided to go all-in on AI-first development. That move led to a smaller team, way faster prototyping, higher overall output, and they ended up folding UI/UX work right into the engineering team instead of bringing on a dedicated designer.

His main takeaway is that engineers have to stop thinking of themselves as just programmers and start acting like problem solvers. Raw code isn't a company's most valuable asset anymore. What really matters now is collective domain knowledge, human judgment and smart prioritisation.

In this chat, we dive into why traditional coding tests are pretty much a waste of time, how small senior teams are beating out bigger, traditional setups, why Europe's at risk of falling behind the US and China in AI, and what happens to tech careers when writing code by hand becomes a thing of the past.

Make sure to subscribe if you want more conversations like this.

Timestamps:

(00:00) Intro
(01:15) Why a Tech CTO Almost Became an Airline Pilot
(03:41) The Moment I Realised Code Isn't Everything in Tech
(05:07) Are You an Engineer or Just a Coder? The Tech Identity Crisis
(07:09) How We Adopted AI to Double Our Engineering Output
(11:40) Why Traditional Coding Tests Are a Complete Waste of Time
(13:35) Is a Computer Science Degree Still Worth It in 2026?
(15:37) Should Companies Fear AI Tools Stealing Their Code?
(18:42) Why We Replaced Traditional UI/UX Roles With AI Prototyping
(21:00) Designers vs. Engineers: Who Will AI Replace First?
(24:08) The Blind Spots Data and Analytics Can Never Show You
(27:21) The Hardest Prioritisation Decisions for CTOs in the AI Era
(28:35) Is Europe Falling Too Far Behind US and China in AI?
(30:55) Who Is Liable When AI Code Makes a Fatal Mistake?
(32:44) The Chanel Bag Effect: Why Human Experts Still Matter
(34:07) What Phone Apps and Tech Work Will Look Like in 5 Years
(36:56) "I'd Need a New Career": The Pain of Going Back to Manual Coding
(40:36) The First Step Every Tech Team Must Take to Adopt AI
(42:23) The Best Career Advice for Early Software Engineers
(43:17) Buy Bitcoin & Tough Lessons Learned From Building Systems

Follow Fredrik Scherstén: LinkedIn

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Jon Jönsson thought AI would completely replace recruiters. Then he built the tool himself, and that's what changed his mind.

He started in sales, then built Sacore, a recruitment firm that runs across 4 Nordic countries. To fix his own hiring bottlenecks, he built an AI sourcing tool. It worked well enough that other agencies started using it too, and that eventually became Instalent.

His view: software can handle the sourcing completely, searching billions of people faster than any person could. But you're still left with 2 people deciding if they actually want to work together, and that part stays human.

In this conversation we get into how candidates should show up online to actually get found by AI tools, why small recruitment teams can compete with much bigger ones right now, what it took to leave a 9 to 5 and build something from scratch, and where he thinks AI is doing real harm to how people think.

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Timestamps
(00:00) Intro
(01:15) How Candidates Get Discovered by AI Tools
(03:11) Why Jon Was Drawn to Sales
(04:59) The Most Complex Sale in Business Explained
(06:42) Why Jon Changed His Mind on AI Replacing Recruiters
(08:37) Why AI Won't Replace Human Recruiters
(09:36) How AI Agents Search Billions of Web Profiles
(10:35) Portfolio Strategies to Beat Automated AI Filters
(12:49) The Biggest Bottlenecks Hurting Modern Recruitment
(13:48) How Small Teams Sourcing Talent Outpace Massive Agencies
(15:02) When Humans Must Step In Over AI Systems
(16:04) Is Automated Screening Less Biased Than Human Recruiters
(16:49) Should You Put a Profile Picture on Your CV
(18:08) Automating Manual Work Without Losing Human Touch
(18:58) How Recruitment Agencies Stay Relevant in Tech Shifts
(20:15) How Small Teams Compete With Big Agencies
(22:26) Will AI Agents Make It Harder to Get Hired
(23:31) Leaving a 9-to-5 to Build a Business from Scratch
(26:38) The Hardest Realities of Running a Startup
(28:56) How Founders Land Their First Paying Customers
(30:03) The Single Best Advice for Early Founders
(31:15) What Five Years in Business Taught Me About Reality
(32:24) The Risk of AI Replacing Critical Thinking

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What happens when you're offered a quarter-million dollars to build a dream project—and you walk away from it?

Early in his career, design leader and educator Ziqq Rafit did exactly that. He realized a hard, uncomfortable truth that most builders ignore: "Sometimes, not designing anything is much better than designing something that will cause more harm than good."

In a world completely obsessed with hyper-growth, shipping products at lightning speed, and automating everything with AI, Ziqq is an advocate for the industry's missing variable: true human judgment.

As an alumnus of the Royal College of Art and Imperial College London, and now a lecturer teaching hundreds of future designers at the Singapore Institute of Technology, Ziqq has watched the industry shift from physical architecture to digital UX, and now to bleeding-edge AI governance. In this incredibly honest chat, Ziqq breaks down how to navigate the messy intersection of tech, ethics, and business without losing your mind or your integrity.

✨ Subscribe to the channel for interviews with world-class leaders and innovators!

Timestamps

(00:00) How Ziqq first got into design (Making design documentaries)
(02:23) Designing for human experience: Core intentions across disciplines
(03:41) Childhood roots: Living in stories, double A batteries, and picking Interaction Design
(07:11) UK vs. Singapore: Navigating design maturity and vendor dynamics
(10:09) The AI Revolution vs. The 1980s Desktop Publishing Revolution
(13:06) The "Judgment" gap: Why engineers need UX designers to evaluate prototypes
(14:32) The modern designer's shift from maker to industry gatekeeper
(15:59) The Contrarian Hook: Turning down a quarter-million dollars for a third-world project
(19:06) When good intentions backfire: Why projects like PlayPumps fail local communities
(23:26) The A-B-C Framework of Design Ethics (Alignment, Best Practice, Consequences)
(26:52) Managing bias and data audits in AI hiring tools
(27:12) Reframing AI: Treating algorithms like interns under human oversight
(30:36) The Ultimate Advantage: Building Emotional Intelligence (EQ) over Artificial Intelligence
(33:42) AI adoption anxiety: Managing job redesign and human friction in organizations
(36:43) Legacy data vs. real value: Ziqq's response to raising hard questions as a designer
(38:30) Where is the future of design headed? Fluid disciplines and complex problems
(42:55) Transitioning from physical architecture to the digital building world
(44:44) Reversing explainability: Forcing students to critique AI outputs
(48:09) Career advice to his younger self: The power of finding a mentor early
(49:34) Overcoming the "Starving Artist" mindset: Reframing money as sustainable energy
(51:51) The hardest lesson learned about human connection and building trust

Follow Ziqq
LinkedIn: https://www.linkedin.com/in/ziqq-rafit/
Website: https://www.ziqq-rafit.com/

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Most founders are flying blind with their money — chasing growth with no clue what runway they have or what bills are coming. That's the problem Hassan kept seeing in commercial finance, so he built Flocast: a tool giving startups real, clear visibility into cash flow, runway, and financial decisions.

Hassan shares why cash flow is misunderstood, how he went from corporate finance to founding his own fintech, and the lessons he's learned along the way.

We talk about:

• Why "leaving it to the accountant" gets founders in trouble
• When to start paying attention to your numbers
• Making finance feel less scary
• His biggest hiring mistake (and the lesson)
• How to land your first real customers
• What investors actually care about in your financials
• Building better financial habits as a founder

Hassan is honest about leaving a stable job, building a product from scratch, and why financial clarity is one of the biggest advantages a founder can have.

Timestamps

(00:00:00) Intro
(00:00:21) How Hassan started his entrepreneurial journey
(00:01:53) The birth of Flocast and solving the cash flow problem
(00:02:52) The moment Hassan realised founders needed better financial visibility
(00:04:27) Why founders struggle with understanding finance
(00:06:27) Making finance simple and founder-friendly
(00:08:06) When should founders start paying attention to cash flow?
(00:10:06) Leaving a finance career to become a founder
(00:12:45) The reality of moving from a 9–5 to entrepreneurship
(00:15:18) Knowing when it's the right time to leave your job
(00:16:41) Does having a family change the founder journey?
(00:19:00) Why experience can become an advantage when starting a company
(00:21:54) Biggest fears when building Flocast
(00:22:24) The power of mentors and networking
(00:24:48) How to overcome the fear of reaching out to people
(00:27:41) Building confidence as a founder
(00:30:31) Hassan's biggest startup mistake
(00:34:13) How Flocast found its first customers
(00:38:26) How Flocast helps founders understand cash flow and runway
(00:41:28) Why accountants don't always provide business advice
(00:43:31) Why investors and VCs are interested in financial visibility
(00:46:43) Fundraising lessons: what investors really want
(00:50:02) The future of Flocast
(00:51:10) The advice Hassan would give his younger self
(00:52:14) What Hassan believes now that he didn't before
(00:53:34) The hardest lesson learned as a founder
(00:54:57) Moments when he wanted to quit
(00:56:30) Finding the first investor in an unexpected place
(00:56:52) Final thoughts and advice for founders

Follow Hassan Zaman
Flocast: https://flocast.co.uk
LinkedIn: https://www.linkedin.com/in/hassan-zaman-a1404198/

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Struggling to find purpose beyond career success? In this clip, Christophe El-Khoury shares the question that guides his decisions and helps him stay focused on what matters the most.

Listen to the full episode for a deeper conversation on purpose, business, and personal growth.

Hugh Chichester (Founder & CEO of Naya) reveals how he's building offshore AI teams that help small and medium sized businesses compete with giants without massive hiring or huge costs.

From refugees to Kurdish engineers, he shares why the future of AI work may not be in Silicon Valley, but in the Global South.

Hugh Chichester is the Founder and CEO of Naya, a company that builds and manages offshore AI agent teams for UK and US businesses. After starting in politics and charity work, he became obsessed with solving talent shortages and labor imbalances using AI and remote talent.

In this episode, he explains:

• How AI agents are becoming real "coworkers" that take action, not just answer questions
• Why offshoring AI talent to places like South Africa, Jordan, and Kurdistan is becoming a major advantage for small and medium sized businesses
• The biggest risks no one talks about: security breaches, runaway costs, and prompt injection
• Why most companies are implementing AI completely wrong, and how to do it right
• The new roles emerging in the AI era: Domain Experts, AI Operators, and Engineers
• Lessons from multiple failed pivots and why he's glad he didn't raise big VC money
• His honest take on the future of work, youth unemployment, and creating opportunity through remote work

If you're a founder, business owner, or anyone thinking about the future of AI and jobs, this conversation is essential.

Timestamps

(00:00) Intro
(00:24) Hugh's Background And Early Career
(02:24) Falling Into Entrepreneurship
(03:51) From Politics To AI
(04:36) The Refugee Story That Shaped Hugh's Perspective
(07:33) The Original Vision Behind Naya
(09:38) Why Skilled Migrants Struggle To Find Work
(10:38) Why Most People Don't Want To Leave Home
(12:01) "We Were Solving A Social Problem, Not An Economic Problem"
(13:55) How Offshore AI Teams Actually Work
(16:09) Finding Talent In Overlooked Regions
(17:05) Why Communication And Hustle Matter Most
(19:13) AI Agents Are Becoming Coworkers
(21:10) Why Businesses Still Resist AI
(22:53) Why Most People Still Misunderstand AI
(24:34) The Opportunity AI Creates For Small Businesses
(26:29) How VCs Are Rebuilding Industries With AI
(29:48) The Biggest Risks Of AI Adoption
(33:13) Why Companies Are Implementing AI Too Fast
(35:31) AI Tools vs AI Agents
(38:13) How AI Changes Team Workflows
(41:53) Trust, Surveillance And AI In The Workplace
(43:13) Growing A Business Without Hiring Twice As Many People
(44:54) The New Roles AI Will Create
(47:56) Why Young People Have A Huge Advantage In AI
(50:51) Why AI Could Create A New Generation Of Entrepreneurs
(52:32) The Problem With VC Culture
(56:52) Building Slowly Instead Of Chasing Hype
(57:03) The Startup Failures That Changed Hugh's Thinking
(59:45) Why You Should "Test And Approve" Everything
(01:01:20) The Middle Class Job Crisis & Barbell Effect
(01:02:58) How AI Is Lowering The Barrier To Starting A Business
(01:04:29) Why Company Data Is A Bigger Problem Than People Think
(01:06:59) Where To Start If You Want To Learn AI
(01:08:42) How Hugh Uses His Own AI Assistant
(01:10:52) What AI Agents Can Actually Do For Businesses
(01:14:09) Why Human Experience Still Matters
(01:18:57) What Companies Should Never Automate
(01:20:54) The Three Questions Sara Asks Every Guest
(01:21:19) The Best Advice Hugh Ever Received
(01:24:43) Why Being A Founder Is Not A Status Symbol
(01:26:32) The Hardest Lesson Hugh Learned
(01:28:02) How Hugh Thinks About Failure
(01:31:36) Final Thoughts

Vinchy is building a new way to produce fashion, and it starts with fixing a system most people never see.

She went from finance and consulting into fashion, only to discover how broken the supply chain really is. Minimum order quantities, miscommunication, overproduction and wasted inventory are holding back new designers and damaging the industry.

Now she's building an operating system to change it.

She explains:

• Why most fashion brands fail before they even launch
• How factories actually work and why small brands get rejected
• The hidden cost of overproduction and unsold inventory
• Why supply chain complexity kills creativity
• How small batch production could reshape fashion
• The role consumers play in driving waste
• How AI can fix communication and coordination in manufacturing
• What it really takes to build in a legacy industry

Timestamps

(00:00:00) Intro
(00:00:37) From Finance To Fashion
(00:03:40) The Real Problem In Fashion Supply Chains
(00:07:24) Why Designing Clothes Is Harder Than It Looks
(00:09:47) How Factories Actually Work And Why Small Brands Struggle
(00:13:09) The Overproduction Problem No One Talks About
(00:16:36) Why Most New Designers Fail
(00:21:49) Small Batch Production Could Change Everything
(00:23:58) Are Consumers Part Of The Problem?
(00:27:51) What Really Happens Behind The Scenes In Production
(00:31:24) How Makia Is Rebuilding The System
(00:40:29) Why Fashion Is Still A Human Industry
(00:46:34) How AI Is Changing Manufacturing
(00:53:48) The Reality Of Building A Startup
(00:58:46) Advice For Founders Starting From Zero

Follow Vinchy Chen
LinkedIn: https://www.linkedin.com/in/vinchychan/
Makia: https://www.makea.co/

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Most companies think AI adoption is a technology problem. It's not.

AI consultant Ideja explains why the real challenge in building a company with AI is not the tools, but the people, systems, and decisions behind them.

Ideja works with companies across Europe, helping teams move from scattered AI pilots to real strategy, execution, and adoption. With a background outside of tech, she brings a rare perspective on why so many organizations struggle to turn technology and AI into real workflows and results.

She explains:

• Why companies fail before they define a clear AI strategy
• The gap between using AI tools and integrating them into company systems
• Why teams resist change when adopting new technology and AI
• The role of human behavior, trust, and design in AI adoption
• What breaks inside companies when systems and data aren't ready
• Why trust, not technology, is the real bottleneck

Timestamps

(00:00:00) Intro
(00:00:25) Why She Left Cell Biology For AI
(00:03:04) How Curiosity Turned Into An AI Business
(00:05:14) Why Most Companies Still Don't Understand AI
(00:07:56) Why People Resist AI At Work
(00:10:16) Why Education Is Falling Behind AI
(00:11:40) The Biggest Misconceptions About AI Right Now
(00:13:21) Why Most Companies Rush Into AI Without A Strategy
(00:15:39) The Teams Most Resistant To AI
(00:17:45) How To Use AI Without Losing Critical Thinking
(00:20:50) Deepfakes, Guardrails, And The Risk Ahead
(00:30:07) Is AI Hype Already Starting To Cool Down?
(00:32:16) How She Taught Herself AI From Scratch
(00:35:41) Why Humans Still Matter In An AI World
(00:36:33) What Her AI Consulting Process Actually Looks Like
(00:52:18) How AI Should Be Taught In Schools
(00:58:34) The Advice She'd Give Herself At The Start
(01:01:30) The Hardest Lesson About Self Worth And Work

Follow Ideja Bajra
LinkedIn: https://www.linkedin.com/in/idejabajra/
Edvance AI: https://www.edvance-ai.com

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