Issue 19 · · sent to our list
A big week across Brisbane, the Gold Coast and the Sunshine Coast — with real shifts in AI, productivity data and platform strategy. Here’s what operators need to know.
23–30 Nov 2025 (SEQ Edition)
This week is about platform direction. Google pushed hard with Gemini 3 + Opal + Stitch + Pomelli + Nano Banana Pro, Anthropic and MIT dropped serious productivity/exposure numbers, and Karpathy basically declared AI homework detection dead.
Our job now: pick a platform strategy, build systems on top of it, and train teams to use them well.
Gemini 3 & Nano Banana Pro Google released gemini‑3‑pro‑preview, a new flagship model focused on stronger agentic reasoning and coding. (Google AI for Developers) Early benchmarks and coverage suggest it’s competitive or better on many coding/reasoning tests, and it’s wired straight into Google’s ecosystem (Search, Workspace, Android). (Business Insider)
On top of that, Nano Banana Pro – an image model built on Gemini 3 Pro – can read exam page screenshots and solve questions directly in‑image, which is what prompted Karpathy’s “homework is over” comments.
Opal, Stitch, Pomelli
Together, this is a systems play: models + app builder + design + content, all inside Google infrastructure.
What this means for you
If you’re already in Google land (Workspace, Android, ChromeOS):
If you’re still half‑in, half‑out:
Sitting in the middle with no rules is where teams get slow and messy.
Note: Microsoft has a lot of catching up to do…
Anthropic: Estimating Productivity Gains Anthropic’s new paper uses model‑estimated task times + real data to show that current AI could add around 1.8 percentage points to annual labour‑productivity growth if adopted at scale. Their Economic Index report also shows:
Translation: early adopters are not just “trying tools” – they’re handing over more of the work and building pipelines. So they can spend more time generating revenue or scaling systems.
MIT + Oak Ridge also released research on a similar topic called the Iceberg Index
MIT’s Iceberg Index measures the share of wage value where AI can already perform tasks. They find: (Tom's Hardware)
Key takeaway: if a role is heavy on documentation, coordination, email or spreadsheets, assume AI can already handle a chunk of it.
Karpathy’s message to schools: “You will never be able to detect the use of AI in homework. Full stop.” (Rude Vulture) Detection tools are trivial to bypass; models like Nano Banana Pro solve exam questions from screenshots.
For kids, the metric should become: How well do you use AI?
For teams, the same applies. Don’t reward “doing it manually” – reward sound judgment and ability to design a workflow that uses AI well.
YouTube: Google AI Studio power
Inside Tech Horizon Academy, we’re now running weekly Gemini + Google Workspace sessions with drop in times for support.
The goal is to:
This week’s workshop builds directly on our AI Social Media Workshop. We’re going from “AI writes posts” to “AI runs your content & task system.”
You’ll walk out with:
👉 Join the Academy + workshop: academy.techhorizonlabs.com
You’ll be in a room (live or replay) with other Australian early adopters doing the same thing every week: testing tools, building real systems, comparing what actually works.
Keep it simple and actionable:
This week’s signal is clear: platforms are consolidating and the data now backs what we feel in our day‑to‑day – AI is already shifting productivity and job exposure, not in theory but in numbers.
Google’s Gemini stack is no longer a side option; it’s a serious contender with a coherent app‑building story. Anthropic and MIT show how fast the ground is moving under admin and knowledge work. Karpathy’s classroom warning is really a workplace warning: stop pretending we can police AI; start training people to use it well.
Tech Horizon Academy exists to make your team unstoppable in that environment – not by chasing every tool, but by mastering the systems that sit on top of them.
—
Huxley Peckham Tech Horizon Labs