Can you shoot a Cannes-level ad with no cameras, a fraction of the budget and a 99% lower carbon footprint? That’s exactly what Kent Boswell and Marcus Tesoriero are doing with aiCandy, one of the first AI film production studios built for brands and agencies.

In this episode of Digital Nexus, we unpack how they’re turning “impossible” ideas from old agency bottom drawers into fully realised films – including a United Nations climate piece set to Mad World by Gary Jules, crafted from real sea-level data across cities like Tokyo, Mumbai, New York and Amsterdam.

Kent and Marcus share the origin story of aiCandy (hatched over beers in Cannes as AI talks took over the festival), the moment Google’s Vo3 lip-sync breakthrough made it “officially ready”, and why they’ve gone all-in on AI film as Australia’s first dedicated AI production studio for the commercial and marketing space.

In this episode you’ll learn:

How aiCandy was born
From Cannes Lions chats about “Will Smith eating spaghetti” to spotting the moment AI film crossed from joke to production-ready – and why they decided it was “jump on the train or get left behind.”

What an AI film production actually looks like
Same brief, strategy and creative process as a top-tier production company – scripts, treatments, casting, locations, storyboards, sound mix and grade – just no physical cameras.

Turning shrinking budgets into “impossible” ideas
Why high quality expectations keep rising while TVC budgets drop from $200k+ down, and how AI lets them turn a “someone jogging in Sydney” script into a Super Bowl-level spot across the Himalayas with a full cast, zero rollover fees and no weather delays.

The UN ‘Mad World’ climate film – from bottom drawer to global story
How a shelved idea became a career highlight: using real climate data to show future sea-level rise in multiple cities, layering it with Mad World, and getting Gary Jules to gift them the track 36 hours after they reached out.

AI film vs traditional production: the carbon myth
The numbers behind the “AI is bad for the planet” headline: a traditional 30-second TVC can create ~40 tonnes of CO₂ (about 16 hot-air balloons), while an AI-produced spot of the same length comes in around 50 kilograms – roughly 2% of one balloon.

Why craft still matters more than prompts
How decades in film, VFX and award-winning creative direction let them spot the tiny details (like a frame-off lip-sync or a six-fingered hand) that separate “AI meme” from world-class work, and why the tool is nothing without expert taste.

What changes for juniors, crew and the next wave of talent
How roles are shifting rather than disappearing, and why juniors still need reps – just with new tools, new workflows and fewer red-eye shoots.

Where AI film is headed next
Why even the people building this stuff hesitate to predict five years out, and how aiCandy is planning to keep raising its own bar after a debut UN project and six more films already in production across comedy, drama and sci-fi.

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus

In this episode of Digital Nexus, Chris and Mark are joined by Dr Tim Rayner — AI Philosopher, author of Hacker Culture and the New Rules of Innovation, and educator at UTS Business School — to unpack how AI can move from “smart autocomplete” to genuine teammates that help people think better, learn faster and build braver.

If you’re a founder, product lead, educator or operator trying to make sense of AI beyond the hype cycle, this one goes deep into the human side of intelligent systems: judgment, values, learning, and what it means to flourish in an automated economy.

Timestamps:
00:00 – Intro: meet AI philosopher Tim Rayner & set up the human + AI theme
00:41 – AI pilots with zero ROI, job automation & why “shadow AI” is everywhere
01:59 – Human practical wisdom vs machine “intelligence” & why education needs to change
03:01 – Exams, “cheating” with ChatGPT & shifting to a build-first mindset
05:01 – Rethinking business models so AI isn’t just a bolt-on tool
10:00 – Using first principles to spot what’s broken & where AI can help
15:00 – Life as a journey of discovery, learning and updating your story
20:01 – Philosophy as a toolkit for uncertainty and AI-driven change
25:00 – Tim’s path: from researcher to AI educator and innovation partner for leaders
30:00 – Human + AI superteams, synthetic intelligence & where the “magic” happens
35:01 – Training subject-matter experts, managers & execs to act as AI leads
40:02 – Why many leaders are naive about AI and why practical wisdom matters
45:00 – Historical parallels: electricity, revolutions and what this AI moment signals
50:01 – Helping people bring their “magic” into work & unlock grassroots innovation
56:01 – Custom GPTs, Typing Minds & teaching people to build useful agents
57:00 – How to join Tim’s AI programs, why 2026 will be a big AI year & closing remarks

Check out:

Superesque: https://superesque.com/
Tim Rayner: https://www.linkedin.com/in/tim-rayner-superesque/

In this episode you’ll learn:

Why universities are being forced to rethink the traditional degree
How one business school is restructuring its graduate programs around AI, project-based learning and “build-first” mindsets, and what that signals for employers and students.

From tools to teammates:
What separates “AI as a fast calculator” from “AI as a collaborator”, and how to frame agent workflows so they support, rather than replace, human judgment.

Hacker culture and innovation inside big organisations
Tim’s take on the “hidden hackers” in every company, and how leaders can give them space, scaffolding and safety to run meaningful experiments instead of gimmicky pilots.

Cognitive offloading vs. cognitive laziness
When it is smart to lean on AI for heavy lifting — and where you need to keep humans in the loop so your team doesn’t atrophy its own thinking.

Philosophy as a practical AI skill
How ideas from Socrates and modern ethics show up in real product decisions: from incentives and power, to who benefits, who’s left out, and how you decide what “good” looks like.

Future

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus

Can AI make game dev truly “prompt to play”?
Jack Wakem (Founder, Tempest AI) breaks down how his team is building “Lovable for games” — a consumer platform where anyone can prompt, iterate, and ship, including a timeline that lets you scrub your build like a YouTube video.

Tempest started as an AI-native RPG engine (RAG, context engineering, custom schemas) and evolved into a fast, consumer game-creation workflow. We dig into the hard parts (state, memory, assets), product pivots, and what Jack learned dropping out, working night shifts, and building in public with Build Club (Annie Liao).

What you’ll learn

Why “AI-native games” are hard (context tracking, long-running state) and the pragmatic path that worked.
How Tempest’s timeline lets creators jump to any checkpoint, edit, and keep playing, slashing iteration time.
Where AI fits today in game development vs. live asset generation (and what’s still rough).
“Lovable for games”: lowering the barrier so non-devs can prompt changes directly in-game.
Market context: gaming + AI is ~USD $1.5–2B today with projections to “tens of billions” by 2029.
Founder mindset: give yourself a focused year, keep lights on with a job, compress learning through reps.

Timestamps:
00:00 – Gaming is huge; meet Jack (Tempest AI)
03:02 – Farm kid to game dev: early life
04:19 – First console memories (Nintendo DS, strict screen time)
07:00 – Designing engaging games; making content to learn
08:05 – Indie projects, clients, and the post-school fork in the road
12:00 – De-risking vs passion; finance path vs gaming; GPT-3 moment
16:03 – Dropping out; night jobs while building Tempest
17:26 – Founder psychology: knowledge, ego, experience
20:20 – Community fuel: Annie Liao & Build Club
24:00 – Tempest focus + the gaming-AI market snapshot
25:18 – Vision: AI-native “never-ending” games (and the hard bits)
28:04 – Context engineering; gen-AI in the dev pipeline
30:00 – What Tempest is: “Lovable for games” (consumer prompt UX)
31:18 – The slow iteration problem in game dev
32:07 – Coding agent + timeline scrubber (edit your game like a video)
33:28 – Building with users: sit-with testing to dashboards
35:10 – Will AI reduce or amplify creativity?
38:05 – The next 5 years: more personal, more experimental games
39:31 – Fundraising: where the round is at
40:08 – How they raised: two years of public building & updates
42:00 – Wrap and where to follow Tempest

Guest
Jack Wakem — Founder, Tempest AI.
Rural NSW origin story → Uni (Finance + CS) → drops out, works nights (pest control/industrial cleaning) while building Tempest.

About Tempest AI
Started by prototyping endless, AI-driven RPGs with custom context schemas and an in-house engine to give LLMs reliable world state. Pivoted ~3 months ago into a consumer game-creation platform with a friction-free UX and a unique timeline editor.

Tempest website: https://alpha.tempestengine.ai/
Jack Wakem: https://www.linkedin.com/in/jack-wakem-ab7170230/

Quote to remember
“You only lose when you quit… keep working at one thing long enough and compounding kicks in.”

Join the convers

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus

Digital Nexus Ep 42: Annie Liao, From Community to Company: Building AI Products That Actually Ship

What does it take to turn AI hype into shipped products? Annie Liao (Build Club / Relevance AI) joins us to unpack agentic workflows, community-led product discovery, and the mindset founders need to go from idea to MVP and revenue, fast.

Annie shares the playbook behind The Builders Club AI and her work at Relevance AI, including how to validate problems, run lightweight experiments, and use agentic patterns without creating black-box chaos. If you build, design, or lead AI products in Australia, this one’s for you.

Links:
https://www.buildclub.ai/
https://www.buildclub.ai/waitlist

In this episode you’ll learn

How to go from “cool demo” to a product customers will pay for (and what to kill early)

Agent vs agentic workflows: clear definitions, when to use each, and common failure modes

Community-led discovery: using a builder community to source problems, testers, and early adopters

Rapid validation: lean experiments, success thresholds, and “stop/iterate/scale” criteria

Designing controllable AI: transparency, evaluation, and guardrails that teams actually use

Founder operating cadence: weekly rituals that compound learning without burning out

GTM for AI tools: positioning, ICP focus, and the signals that you’ve hit early product-channel fit

Hiring the first 3 roles for an AI product team (and what to outsource)

Metrics that matter: activation paths, retained use, and qualitative proof you’re solving a real job

Australia’s AI ecosystem: where builders are winning now and what’s next

About Annie Liao
Annie is a community builder and operator behind Build Club (The Builders Club AI) and serves as Chief of Staff at Relevance AI. She sits at the intersection of community, product, and execution—helping teams turn AI capabilities into customer value.

Chapters
00:00 Intro
02:28 What is Build Club? Hackathon energy & projects
04:34 Annie’s path: UTS scholarship → Westpac → internal startup
05:08 Falling in love with tech: coding, PM, CRM build
08:19 Nov 2022 shift: GPT boom and the “build anything” moment
12:01 Founding story: After-hours at Aura Ventures → “Aura’s Build Club”
14:03 Community vs monetisation: mission to democratise AI learning
17:00 Joining Relevance AI (while growing Build Club)
21:35 SF vs Australia: risk culture, density & talent
25:53 How Australia can catch up (culture & ecosystem)
29:31 Enterprise agents: handover pain & the education gap
36:24 Bounty marketplace: matching AI builders with demand
41:01 Roadmap: AI matching, pricing benchmarks & starter templates
51:40 Rapid-fire: the tools we actually use
53:18 Build Club for enterprise: AI upskilling (waitlist)
53:47 Wrap-up & where to find Annie

#AI #AgenticAI #ProductManagement #Startup #UX #SydneyTech #BuildClub #RelevanceAI

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus

From hacking mainframes to building Haven (mental health) and now Indy, an AI co-pilot helping families navigate paediatric and developmental care, Jeff Quach shares a builder’s journey grounded in anthropology, trust, and real-world impact. We unpack when AI should support human care (not replace it), why guardrails matter, how to find the right co-founder, and the gritty reality of bootstrapping (“the desert walk”), plus practical tools and workflows you can use today.

Time stamps
00:00 – Intro: Jeff Quach, Indy & what this episode covers
05:53 – From Haven to Indy: why the pivot in mental health tech
06:00 – Anthropology in product: culture, reciprocity & trust
08:11 – Designing for trust: small choices that compound
10:17 – Where AI supports, not replaces, human care
12:09 – Problem space: parents, families & complex journeys
14:14 – Haven lessons: support across age stages and scope
17:27 – Early builder stories & shipping fast
21:15 – Founder persistence and the “desert walk”
24:04 – ICP clarity: serving parents first
26:17 – Finding the right co-founder (Antler signals & fit)
31:33 – Parent outcomes: progress they can see
35:00 – Mental health models: what AI can/can’t solve
37:02 – Inside Indy: product shape & value moments
41:40 – Workflow stack: Notion (AI), ops, cadence
44:53 – Safety & guardrails: avoiding overreach
49:30 – Tools recap: Claude, Notion AI, practical tips
51:30 – Closing: key takeaways & what’s next

What you’ll learn
- Applying anthropology to product: cultural relativism, reciprocity & trust → better UX and retention
- The limits of “self-solving” mental health; designing tech that restores human-to-human connection
- Why Jeff wound down Haven and built Indy with safety guardrails and a parent-first journey
- Co-founder fit via Antler: complementary skills, oxygen for the journey, signals that you’re on the right path
- Hyper-personalisation that isn’t creepy: small preference shifts that build long-term trust
- Tools & stack: Notion + Notion AI, Claude (Code), rapid prototyping, lightweight agents
- Career & founder advice: go wide, ship often, persist, and avoid “big-name” co-founder traps

About Jeff
Product and AI leader with roots in financial services and SafetyCulture, a background in social anthropology, and founder/operator across Haven (mental health) and Indy (AI for parents). Jeff’s lens: build value where people feel it daily—then earn trust with clear trade-offs and smart guardrails.

Who this episode is for
Founders and PMs shipping AI into health, family & education contexts
UX/CX leaders chasing evidence-backed trust and adoption
Builders validating AI products without losing the human

Episode links:
Check out the Indi App: https://projectindi.com/
Check out Jeff Quach: https://www.linkedin.com/in/jeffreyquach/

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus

AI isn’t the enemy, it’s the experiment of our lifetime. At SXSW Sydney 2025, we took Digital Nexus onto the floor and into the streets to ask a simple question: doom or hope? From late-night hackathons to founders shipping agentic workflows, this episode captures how Australians are actually building with AI.

We go behind the scenes with builders and community leads from Build Club, hands-on teams using Relevance AI, Lovable, and Bolt.new, and ecosystem voices like the National AI Centre, plus candid vox pops from attendees who think AI is either saving creativity… or killing it. If you’re a founder, product leader, or designer trying to turn hype into shippable outcomes, start here.

You’ll learn

Why “AI doom vs. hope” is the wrong frame, and what builders are doing instead
Where agentic workflows beat black-box agents (and when they don’t)
How tools like Relevance AI, Lovable & Bolt.new compress idea to MVP
Practical adoption patterns we saw across Aussie startups and teams
What the National AI Centre says about responsible rollout in AU
The real skills founders need next (UX, data, orchestration, governance)

Keywords: AI Australia, SXSW 2025, SXSW Sydney, Build Club, Relevance AI, Lovable AI, Bolt.new, National AI Centre, AI agents, agentic AI, Anthropic, NVIDIA, ChatGPT, Gemini, founders, product design, UX, startup growth, Australian startups, AI podcast

Timestamps / Chapters
01:02 – Intro at SXSW Sydney 2025 (what we’re testing & who we met)
03:18 – Street takes: “AI apocalypse” vs “AI accelerator” (vox-pop highlights)
06:45 – Builder mindset: why agentic workflows beat pure agents
09:12 – Hands-on demos: rapid prototypes with Relevance AI & Lovable
11:00 – What does the public say about AI?
16:30 – Saanvi Y - Founding Member of Build Club
20:04 – Ishita Gupta from Kinso AI
23:11 – Community spotlight: inside Build Club (skills, projects, outcomes)
27:06 – Rita Arrigo from the National AI Centre on responsible AI in Australia
31:40 – Teams & tooling: when to choose ChatGPT, Claude, or Gemini
35:22 – From fear to shipping: practical prompts, guardrails, and QA loops
38:05 – Creativity & jobs: what changes, what doesn’t, what gets better
41:10 – Takeaways: our SXSW checklist for founders & product leads
43:02 – Outro & next steps: links, resources, and how to get involved

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus

Can AI help understand our emotional state? Nicole Gibson, founder of Love Out Loud and co-founder of inTruth, shares how a recovery journey became a product mission, and how she’s using AI in mental health to scale evidence-based impact, leadership, and a love-led culture.

Watch for:
From anorexia recovery to national advocate → AI product leader
The origin of Love Out Loud and community design that changes behaviour
inTruth: AI ethics, data consent, and measurable outcomes in mental health
Product mindset for founders: ICP clarity, tight feedback loops, and validation before code
Language, rituals, and narratives that convert without sensationalising trauma
Practical advice for young leaders on purpose, pressure, and burnout

🎙 Guest: Nicole Gibson — founder, author, former National Mental Health Commissioner; Love Out Loud, inTruth

👥 Hosts: Chris & Mark — Digital Nexus Podcast (Australia)

👉 Subscribe for founder stories from Australia’s AI ecosystem
👉 Share this with someone building in health, education, or social impact

Chapters

00:00 From Rogue & Rouge to Love Out Loud, Nicole’s Mission
05:30 Overcoming Anorexia: Nicole’s Turning Point
10:59 Building Love Out Loud: From Grassroots to Movement
16:28 Healing Mental Health: Shame, Support, Recovery
21:56 Inside Eating Disorder Recovery: What Actually Helps
27:27 Trauma, Belonging & Community Healing
32:57 The Philosophy of Love Out Loud (Connection over Fear)
38:26 inTruth by Nicole Gibson, Building a Trust Layer
43:55 Compassion in Practice: Everyday Mental Health Tools
49:25 inTruth in Action: Authenticity, Privacy & Safety
54:55 Advice to Young Women: Finding Your Voice
1:00:24 Founder Journey: Building Movements, Not Just Startups

Links & Mentions

Nicole Gibson — Love Out Loud / inTruth https://intruth.io/

Digital Nexus Podcast — Chris & Mark (Australia) https://www.digitalnexuspodcast.com/

Tools & topics: AI for mental health, ethical AI, customer validation, product mindset

Why this matters
If you’re a founder, designer, clinician, or policy maker, this episode is a practical blueprint for building ethical AI in mental health with real-world outcomes — from research and validation to community design and leadership.

Hashtags

#AI #MentalHealth #NicoleGibson #inTruth #LoveOutLoud #ProductMindset #EthicalAI #AustralianStartups #DigitalNexusPodcast

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus

Want clearer, more consistent AI outputs? In this episode, we break down three prompting skills that help founders, PMs, and UX leads go from idea → clickable MVP fast—using ChatGPT and Claude. Guest Bastian Epskamp shares his 3-phase system (prepare → implement → learn), how to ship prototypes stupid fast with V0/vibe-coding, and a case study on building Auction Buddy (AI for buyer-side property decisions).

What you’ll learn

The 3 skills: framing, constraint design, and iterative prompting (ChatGPT & Claude).
Prompt templates that work: turn vague asks into structured tasks for reliable outputs.
Speed to MVP: V0/vibe-coding, docs-as-leverage, tight feedback loops.
Real product examples: how “Auction Buddy” scores inspections, plans bids, and does live auction maths.
Team craft: pair human creativity with AI to reduce cycles and increase signal.

Who this helps: Founders, product managers, and UX leads shipping LLM apps, agentic workflows, internal knowledge assistants, and customer-facing AI features.

Timestamps:
00:00 Intro — Meet Bastian (BE Innovations) & the “product lens”
03:25 Why AI is a product superpower
05:40 Early builds: Dreamweaver sites, custom PCs, first “maker” wins
08:45 Research & prompting in practice (talk to AI like a teammate)
16:05 Teams, mistakes, and building with intent
19:30 Exit story → starting a strategy/innovation lab
21:00 Monetisation & prioritisation: pick the sharpest pain points
24:30 AI = remove repetition, keep judgment (why experience still matters)
29:10 Aussie ecosystem: capital cycles, resilience, and pivots
31:00 Upskilling across functions (seeing the whole system)
35:30 Prompt frameworks that work (structure, constraints, examples)
38:20 Rapid loop: Prepare → Execute → Learn
39:10 Property tools: “Auction Buddy” & decision support for buyers

👍 If this helped, like, subscribe, and share with a builder who needs faster MVPs.

#ChatGPT #Claude #PromptEngineering #AIProduct #MVP #LLM #Prototyping #VibeCoding #Startups #UX

Support the show

Other Links
🎙️our podcast links here: https://digitalnexuspodcast.com/
👤Chris on LinkedIn - https://www.linkedin.com/in/pcsinclair/
👤Mark on LinkedIn - https://www.linkedin.com/in/markmonfort/
👤 Mark on Twitter - https://twitter.com/captdefi

SHOWNOTE LINKS
🔗 SIKE - https://sike.ai/
🌐Digital Village - https://digitalvillage.network/
🌐NotCentralised - https://www.notcentralised.com/

YouTube Channel: https://www.youtube.com/@DigitalNexusPodcast
X (twitter): @DigitalNexus