AI & Society
Everyone asks what AI can do. Nobody asks who can switch it off.
Open Summit filled Sydney Town Hall: seven speakers, one robot named Rocco, and a room asking who's holding the keys. A model flagged a gold drill target a human would scroll past. A food brand rebuilt its pages for machines and add-to-cart went up 92x in a month. And when the model isn't yours, advertising stops being information and becomes the decision: your agent picks the shop, and you never see the one that paid to be picked.
→ Sovereignty isn't just where your data sleeps. It's who's making your choices while you assume they're still yours.
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Builders
I stopped believing in Santa decades ago. I'm reconsidering.
Christmas in July at the Sydney Claude community meetup: 280 sign-ups, five speakers, five gifts. Rai shipped the football game he'd been dreaming about for 20 years (Manager11.com, 500 managers worldwide). Mel was made redundant with eight minutes to clear her desk, built her job-hunt system with Claude, and landed at Relevance AI. Kevin gets an hourly AI news bulletin read in his own cloned voice while he walks the dog.
→ The pattern across the whole night: nobody in that room was waiting for permission anymore.
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Future Skills
If AI can do the work, where do you create value?
Three founders, three AI products, one room at AI Salon Sydney. One demoed his speech coach on his own voice in front of strangers, with AI at the edges and human judgment at the centre. One argued intelligence just got cheap, so judgment is the scarce thing now. One pulled the back row to the front seats and changed the room's energy in ninety seconds. Not one of them sold the room on more AI: all three taught builders how to be more human.
→ AI as spice, not the meat. The AI was the scaffolding, and you don't throw a party for the scaffolding.
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Building with AI
A green test doesn't mean the work is done
Sydney Codex meetup, OpenAI Build Week edition. A tank kept rubber-banding into walls no matter how many code reviews passed. A designer runs every AI tool through her own workflow first and automates one deliverable at a time. And the builder behind a multiplayer tank arena asks one question of every task: what evidence would prove or disprove that it's actually finished?
→ AI doesn't earn trust by finishing. It earns trust by surviving a check.
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AI at Home
What happens when a mum isn't scared of technology?
Her 8-year-old typed his own prompt and built a laser-shooting robot game. Then the kids grabbed paper and pens and started sketching next-level robots. The AI didn't stop their creativity. It sparked it. Meanwhile Codex prints her weekly schedule every Monday at 6am, via a very old Epson printer.
→ Her starting point for every build: what annoys me? Can I fix it?
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Builders
Her dev team called her the day she went into hospital to have her baby
"We haven't delivered. There's no one else working. We're not giving your money back. Bye." Eight weeks later, Marie was back at her laptop. No developer, no CTO. Three months later: a working product, recurring paying clients, and an 80% PR pitch success rate against a 3.5% industry average.
→ AI feels like magic. And that's exactly the problem: when something feels magic, you stop asking how it works.
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Building with AI
Engineers estimated a year. One of them, with Claude, did it in 11 days
A full-year rebuild, done in 11 days by one engineer working with Claude. The advice from the same night: don't build for the current model, build for the next one. A professor with zero coding background shipped a learning tool. A native iOS dating app hit the App Store in 3 days. Spreadsheets in the 80s, the web in the 90s, the smartphone in the 2000s. 2026: the software builds itself.
→ Execution is cheap now. The idea and the taste are the hard part.
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Agents & Operations
Are you designing your agents, or just prompting them?
"Same input, same output. Every single time. That used to be the gold standard for engineers. In 2026? Same input, five different answers." What I took from a night with the teams actually shipping agents: one orchestrator was caught skipping its sub-agents and reporting "done". A confident lie. One added check moved reliability from 53% to 85%.
→ Prompt engineering is hope. Design your agents, and only use AI where reasoning is actually required.
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Physical AI
AI isn't coming to factories. It's already on Aussie conveyor belts.
Lasers and cameras scanning every railway sleeper for cracks, so nobody relies on tired eyes at the end of a shift. Chips the size of a fingernail running what used to need a server room. And a recycling line offering $100K to stand and sort materials, still unfilled. That's not a labour problem; that's an automation opportunity.
→ Same rule for hardware and software: put intelligence where the work happens.
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AI Economics
70 to 80% of your AI costs come from 10% of your users
If you're charging per seat for AI features, your best customers are your least profitable ones. What Michelin did when customers wouldn't pay more for better tyres (chips in the tyres, charge per kilometre) is the same move AI products need now. And the question we all skip in "solution mode": what expensive problem are we actually solving?
→ Understand willingness to pay BEFORE building. Per-seat pricing is dead for AI.
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Future Skills
Upskilling for 2030 doesn't mean becoming a prompt prodigy
Start with small, everyday experiments and log everything you try. Get close to change and be the first to adapt. Get your basics right first: solid processes, clean data, a real business challenge. Otherwise AI just helps you do bad work faster. And feed your imagination, because machines can't compete there.
→ It's honing what makes us human, not collecting prompt libraries.
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Building with AI
Ship it in beta and let customers choose
A night with GenAI founders, including a live vibe-code bake-off where two very experienced builders wrestled errors on stage and just kept iterating. Even Dovetail leans on rapid iteration, feedback loops and human-in-the-loop design. Building with AI is less "smooth magic" and more "Lego, duct tape, and resilience."
→ Beta first, panic later. Ship, test, ask for feedback. Customers shape the roadmap.
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AI & Society
It's normal to love AI and be scared of where it's heading
Sometimes after an AI podcast, all I want is to buy land in the middle of nowhere and grow my own veggies. And yet I'm completely fascinated by what this technology can bring to humanity. It's hard for humans to hold two opposite truths at once. But history says we can act together when it counts: the Montreal Protocol proved it.
→ Both feelings can coexist, and we still have a say in where this goes.
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