Tracey Spicer is one of Australia’s most respected journalists and the author of Man-Made: How the Bias of the Past Is Being Built into the Future. In this episode, Georgie sits down with Tracey for a sharp, funny, and occasionally jaw-dropping conversation about what happens when we treat AI like neutral math instead of what it really is: opinion written in code.

They unpack why algorithmic bias is getting worse in the generative AI era, how recommendation engines can quietly radicalise people (from Andrew Tate pipelines to hyper-performative “tradwife” culture), and why “move fast” without guardrails is a dangerous blueprint. The discussion also goes into the weird and unsettling frontier of humanoid home robots, privacy risks in always-on devices, and what Tracey learned researching sex robots, including the disturbing ways consent is engineered out of the product.

Plus: why Tracey’s favourite AI tool is Claude, what she thinks about Grok and the chaos machine of X, why we are not getting a four day work week anytime soon, and her case for “regulatory sandpits” to test AI safely before it hits the rest of the world.

01:10 – Tracey’s TEDx “The lady stripped bare” moment and why it still matters

04:45 – Beauty standards, AI filters, and why expectations on young women have intensified

08:20 – Man-Made and the epiphany that sparked Tracey’s AI obsession

11:10 – The AI arms race, speed, and why we are in the “seatbelt era” of tech

14:30 – Digital natives vs critical thinking: the hallucination blind spot

16:45 – Tracey’s AI stack: why Claude is her daily driver

19:05 – Humanoid home robots: convenience vs surveillance

21:55 – Strength vs security: what actually scares Tracey about robots

24:35 – Sex robots and the consent problem manufacturers do not talk about

28:10 – Algorithms as “opinions in code” and how radicalisation happens

33:10 – Removing bias: conversations, perspective checks, and inclusive design

35:00 – Grok, MechaHitler, and what happens when platforms mirror their owners

36:45 – Deepfake porn, consent, and why regulation is finally catching up

38:10 – No, AI will not magically deliver a four day work week

41:10 – Future jobs: law, AI assistants, and why juniors still need fundamentals

44:15 – Indigenous knowledge, language revitalisation, and the full-circle AI story

46:50 – Rapid fire: brain chips, Waymo, smart glasses, and AI “snog marry avoid”

49:55 – What we should do now: regulatory sandpits and real guardrails

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Enterprise AI is past the hype phase and into the hard part: scaling what works without breaking security, blowing out costs, or shipping chaos into production. In this episode, Georgie chats with AWS technologist Rada Stanic about using AI as a “study buddy” to renew technical certifications faster, and why tools like AWS QuickSight can generate strong first drafts of strategy docs when you provide the right templates and context.

They go deep on AIOps: the operational discipline enterprises need to deploy agents and GenAI reliably at scale. Rada breaks AIOps into five practical pillars: defining agent intent, identity and security boundaries, policy and governance, observability and evaluation, and managing the rapid model lifecycle as new LLMs drop constantly. The conversation also covers why security questions dominate every enterprise AI project, why data quality still makes or breaks outcomes, and why “RAG” is fading as a buzzword even though retrieval is still foundational.

Finally, Rada shares a sharp concern for the next generation: what happens to junior roles when AI fills the entry level work, and why the pace of change itself may become the next generation’s greatest advantage.

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Liam Millward is one of Australia’s most watched young founders, but this conversation goes way beyond the headline of raising a record pre-seed at 17. Liam breaks down how Instant is building an AI powered marketing manager for e-commerce brands, why retention marketing is the real lever for growth, and how personalisation at scale changes the economics of marketing teams.

Georgie and Liam unpack what it actually takes to win in B2B SaaS right now, why “nice-to-have dashboards” are getting crushed, and what young founders should do instead of spending their time posing with VCs. Liam also shares the downside of raising big too early, his bet on Google winning the model race, and the one tool he has mandated across Instant’s engineering team.

Plus: why New York (not SF) is the next chapter for Instant, how Australian buying habits can create painful customers, and Liam’s spicy prediction that AI agents will become the majority of internet traffic shockingly soon.

01:35 – Meet Liam Millward and the record-breaking pre-seed story

03:40 – Using AI to hire better and have deeper interviews

07:55 – What Instant actually does and why retention beats acquisition

12:00 – How AI personalization changes loyalty, margins, and growth

16:30 – Is B2B SaaS dead or just getting ruthless?

20:45 – Raising big too early, age bias, and proving people wrong

28:30 – Teenage founders, VC hype, and why starting small still wins

34:15 – New York expansion, Google vs OpenAI, and Claude Code

43:50 – AI agents, Australia’s talent drain, and what comes next

44:38 – Saying no to customers: Australia’s “buy from friends” trap

45:32 – Structure at Instant: obsession, speed, and a tiny leadership team

46:42 – Australia’s talent drain and what could change it

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Is the next AI breakthrough hiding in robotics, not chatbots?

This week on In the Blink of AI, Georgie Healy is joined by cognitive robotics researcher Colm Flanagan for a grounded look at the next phase of artificial intelligence beyond large language models. While tools like ChatGPT live comfortably in the cloud, robots do not have that luxury. A self-driving car, drone, or warehouse bot cannot wait seconds for an answer. Decisions have to happen instantly, on device. Colm explains why this constraint could force a fundamental rethink of how we build AI, pushing models to become smaller, faster, and rooted in real-world experience rather than just trained on internet text.

The conversation explores whether LLM progress is starting to plateau, what a “data ceiling” really means, and why chasing AGI might be the wrong goal altogether. From robots that form memories like humans to the privacy tradeoffs of machines that watch and learn from us, they unpack the technical limits, the hype cycles, and what actually matters for builders today. If you want a clear-eyed take on where AI is genuinely heading, and why the next breakthroughs may be physical rather than digital, this episode connects the dots.

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Josh Vinson works at the edge where AI meets the human brain. With a background in psychology and machine learning, he is part of a growing group of engineers exploring neural decoding, the emerging field focused on translating brain signals into meaningful insights about thought, intent, and experience. While the idea of “reading thoughts” still sounds like science fiction, Josh explains why parts of it are already real, and why recent advances in large language models have quietly accelerated progress in this space.

In this episode of In The Blink of AI, Georgie Healy sits down with Josh to unpack how brain computer interfaces actually work, what separates invasive implants like Neuralink from noninvasive approaches such as EEG, and why the hardest challenges are not ethical or philosophical but technical. They explore the twin problems of noisy hardware and radically different brains, and what it would take for neural decoding to become reliable enough for clinical and everyday use.

The conversation stretches beyond medicine into the future of communication itself. From experience transfer and lucid dreaming headsets to brain wearables that could track attention, presence, and mental fatigue, Josh shares a clear-eyed view of what might be possible and what should give us pause. If you’re curious about where human cognition and artificial intelligence truly begin to blur, this episode offers a grounded look at what’s coming and why it matters.

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Tom Newby, Head of AI and co-founder at Procure Pro, joins Georgie Healy for a fast, candid tour through the most useful, controversial, and surprisingly human parts of the AI wave.

They start with Tom’s favourite under-the-radar tool in Australia, Hex, and its new “AI data analyst” agent that can actually do analyst work, not just answer simple queries. Georgie shares her own weekend hack: using AI to redesign a very average rental outdoor area with photo-based before-and-afters.

From there, the conversation turns to the bigger questions: whether using LLMs makes us “lazy”, why the blank page problem is real (and how AI helps you get to a wrong answer fast so you can refine), and what it takes to build AI features that actually matter inside a product. Tom breaks down Procure Pro’s mission to save a billion hours of construction admin and explains “bid leveling”, the messy PDF-to-spreadsheet reality that procurement teams face every day.

Georgie also brings the headlines. They unpack Australia’s surge in commercial data centre construction (and why the export narrative might not hold), plus Tom’s spicy take on OpenAI’s recent cadence, model naming chaos, and why distribution and “apps” could matter more than raw model gains.

They finish with rapid-fire stories: Tom’s accidental three-hour job, a 7-Eleven game exploit turned Slurpee rewards, a surprisingly thoughtful answer on ADHD and LLM workflows, plus a practical trust framework for everyday AI users.

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Australia has a new AI strategy, but does it match the speed of the moment? Dr Tom Kelly, CEO of Heidi Health, and Anish Sinha, founder of UpCover, sit at the coalface of deploying AI in two of the most regulated industries in the country: healthcare and insurance. They have both built companies where safety, compliance, and real-world adoption are not optional, and they bring that builder perspective to a frank assessment of the government’s latest plan.

In this episode of In The Blink of AI, Georgie sits down with Tom and Anish for a practical conversation on what Australia’s AI strategy gets right, what it completely misses, and what it would take to move from vague principles to measurable outcomes. They argue the plan needs sharper priorities, clearer success metrics, and a more decisive approach to accelerating adoption in industries where AI can lift productivity quickly.

Tom unpacks why Australia is non-competitive on energy and compute, why chip availability and latency matter if we want world-class AI experiences locally, and what policy levers could make Australia a serious data centre and infrastructure contender. Anish explains why tech-neutral regulation is a relief for startups, why government should focus on long-term market-making rather than short-term accelerators, and why Australia should look to Canada for inspiration instead of trying to copy the US or China.

This is a sharp, builder-led episode for anyone trying to understand what Australia should actually do next in AI, from infrastructure and sovereignty to education, public sector productivity, and stopping bad actors without slowing innovation.

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Heidi Health has quietly become one of the most widely used AI products in Australia, powering nearly two million clinical visits a week and transforming how doctors document care. In this re-release of the year’s most downloaded episode, Georgie sits down with Heidi cofounder and CEO Dr Tom Kelly to unpack how this runaway success was built, why clinicians trust it, and what the rise of medical agents means for the future of healthcare.

Tom shares the technical decisions that shaped Heidi’s accuracy advantage, including the surprising reason they ditched live transcription, how batch processing boosts note quality, and why a two percent gain in transcription accuracy can unlock a forty percent jump in adoption. He also breaks down what non technical founders absolutely must understand about LLMs, how he evaluates off the shelf models, and why compliance and regional infrastructure shape every product decision.

The conversation stretches far beyond medical notes. Tom dives into why rag is failing many real world use cases, how giant context windows could reshape patient care, and which AI startups may struggle as models get faster and cheaper. There are hot takes on personal branding, the attention hacking era, and the types of B2B SaaS companies he believes will not survive. Plus, Georgie and Tom play Late Stage Startup Bingo and share two very usable AI hacks.

This episode is a sharp, founder friendly deep dive into building AI products people rely on in the real world. A perfect refresher as we head into a huge 2026 for Australian AI.

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