A Kiwi - Generating, Publishing, and Tinkering - with AI.
Vibe coding, sharing ideas, and building small products. Some are polished; some are gloriously half-built — because life ships as a prototype first.
Imagine asking your policy system a simple question and getting a perfect answer in under a second. Now imagine asking it to analyse fifteen years of reports, submissions, evaluations, and operational metrics. One requires a chatbot. The other requires an engine. Policy teams often reach for RAG because it looks neat and tidy. A chatbot that can trawl internal guidance, regulatory texts, consultation documents and memos feels like a small miracle. And to be fair, a well-tuned Retrieval-Augmented Generation system is a brilliant librarian. It fetches the right paragraph, summarises dense text, and saves you from spelunking through document drives that haven’t been organised since John Key was in office. ...
When the tech world bursts into hype mode, valuations soar, promises multiply, and eventually someone asks: does this actually work? That’s the moment when hype meets the bubble. Artificial intelligence has reached that point — glowing headlines, soaring investments, and a rising hum of scepticism in the background. The thing is, hype isn’t all bad. It’s the spark that gets things moving. Every big leap — from the steam engine to the smartphone — started with an overexcited crowd shouting, this will change everything! And they weren’t entirely wrong. But the danger comes when excitement turns into blind belief. ...
When I was in Year 6, my history homework was supposed to be full of long, serious answers. There were fifty kids in the class, and I remember wondering — does the teacher actually read every word? So, halfway through one answer, I slipped in a few lines from a song. My heart sank when I handed it in, expecting trouble. But when I got the copy back, there it was — a big red tick on that very page. I had, in some sense, hijacked the teacher’s chain of thought. ...
🪷 Dharma and Leadership: Lessons from Krishna and Rama When we think of dharma in Indian philosophy, two figures stand tall: Lord Rama, the symbol of moral integrity, and Lord Krishna, the strategist of divine pragmatism. Both upheld dharma—but in completely different ways. 1️⃣ The Dilemma: Krishna and Bhima vs. Duryodhana At the end of the Mahabharata war, Bhima fought Duryodhana in a mace duel. The rule forbade striking below the waist. Yet Krishna signaled Bhima to hit Duryodhana on the thigh—breaking the rule and ending the war. ...
When we talk about artificial intelligence, we often think about how well it remembers — data, facts, styles, even our writing tone. But what happens when we need it to forget? That’s the tricky challenge of AI unlearning, and a new paper — Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning — offers a smart new angle on how to do it. Why forgetting matters As AI models grow larger, they absorb massive amounts of information — some of it private, copyrighted, or simply outdated. From user data that should have been deleted to training examples that contain bias or sensitive facts, keeping everything isn’t always safe or ethical. ...
Could a large language model act like a sleeper agent — perfectly normal until a secret phrase awakens it? Here’s how LLM Hypnotism might happen, why it’s hard to pull off, and what it teaches us about trust in AI.
Everyone knows The Tortoise and the Hare. But what happens when you hand that story to an AI and ask it to summarise it — again, and again, and again, twenty times in a row? This experiment is the AI equivalent of the childhood game “Whisper Loops” where a message whispered around a circle mutates into hilarious nonsense by the time it gets back to you. Except here, the whisperers are language models. And the message is Aesop’s tidy moral about patience and pride. ...
Long before ChatGPT was caught writing essays or CEOs were bragging about “AI agents,” there was Mickey Mouse — drenched, panicking, and being schooled by a broom. Fantasia’s “The Sorcerer’s Apprentice” isn’t just a cartoon. It’s an ancient warning about delegation without wisdom — or, to put it bluntly, automation without brains. The Old Story, Fresh Eyes 👀 Picture it. The workshop hums with quiet power. The old sorcerer steps out, leaving his apprentice, Mickey, with one boring task: fetch water. Mickey looks at the heavy buckets, looks at the spellbook, and has a brilliant idea — “Why not get the broom to do it?” ...
TL;DR AI is becoming the front door to software: instead of clicking, you ask. Agents (like those built on Model Context Protocol) go further, skipping native UIs to act on your behalf. But not everything should be replaced: old UIs remain best for precision, safety, and learning. For Kiwi companies (Trade Me, Xero, One NZ), the challenge is balancing AI’s magic with trust, transparency, and compliance. What was once only achievable in AWS a decade ago is now democratised. 1. Language as the new input Once, we memorised commands. Then we clicked icons. Now, increasingly, we just talk. ...
A hammer helps you build. A violin asks you to learn a phrase. AI is closer to the violin. We often hear AI described as a tool, a neutral extension of human intent. Something you pick up, point, and apply. But that language downplays its nature. Tools don’t talk back. Instruments, on the other hand, respond. They shape the way you play, reveal new sounds you didn’t expect, and demand practice to master. If we keep calling AI a tool, we miss the more interesting truth: it’s an instrument. ...