The full schedule for AI Engineer Melbourne is now live.The grid view is the most useful way to scan it. There’s also semantic search, and a recommendation system as well to find related talks to ones you’re interested in. We’ve also shipped an agent-friendly view with MCP endpoints, llms.txt, and other interfaces designed for agents — the conference about […]
How a recurring rhetorical move keeps proving the wrong thing There is now a recognisable pattern in AI commentary. It runs roughly as follows. A paper appears on arXiv. It contains real mathematics — definitions, lemmas, a theorem, sometimes several. The theorem establishes that a particular formal object, under a particular set of assumptions, has […]
DGX Spark & Sovereign AI: Architecting Air-Gapped Agents There's a historical pattern worth noting: computing power that was once centralized tends, over time, to get distributed. Mainframes belonged to institutions. Personal computers put computing in homes and offices. Mobile devices put it in pockets. Each shift democratized something — access, speed, the ability to build […]
Agentic Self-Healing in Production It's 2:47 AM on a Tuesday. Your data pipeline fails. A sensor stops reporting, a database connection is dropped, an API that your system depends on starts returning errors. In the old world, this is when an engineer gets paged. They wake up, SSH into the server, run some diagnostics, fix […]
Who Needs a LoRA? There's an assumption embedded in how people work with image generation models: if you want the model to do something new or specific, you fine-tune it. You get the pretrained model, you gather a dataset of examples of what you want it to do, you run a training process, and you […]
Having Your Cake and Eating It: An Implementation Guide for Privacy with AI There's a fundamental tension at the heart of modern AI deployment: the models that work best require the most data, and the data that makes models work comes with the steepest privacy costs. The larger the model, the more examples it needs […]
A few months ago I sat down to work through some thoughts about the different ways developers are working with AI. The list seemed straightforward enough at the time. There was the spicy autocomplete you got in your IDE. There was the turn-by-turn chat with Claude or ChatGPT. There was the Git-integrated agent — Codex, […]
Beat Burnout, Find Flourishing: The AI Edition The pace feels relentless. A new AI tool arrives on your team's desk every few weeks. Code completion assistants, autonomous agents, generative models for everything from design to documentation. There's genuine excitement about what's possible, but underneath it runs a current of exhaustion. People are burning out not […]
Get a GRASP: How to Create Real Risk Visibility for AI Agents If you deploy an AI agent into production, it will make decisions with real consequences. It might approve a loan, schedule critical infrastructure maintenance, route emergency services, or allocate resources worth millions. And yet, most organisations have almost no systematic way to understand […]
Beyond Silicon Valley: Building AI Governance on the Fair Go Principle AI governance looks the same everywhere because the AI industry looks the same everywhere: concentrated in Silicon Valley, shaped by American values, and exported globally as though those values are universal. But they're not. The assumptions baked into American AI development—individual liberty over collective […]
Not Everything Needs an LLM There's a gravitational pull in AI right now: when you have a hammer called GPT-4, everything starts to look like a nail. A support ticket router? Obviously you need an LLM. A text classifier? LLM. A data extraction problem? LLM. It's understandable. Frontier models are impressive. They work across domains […]
Your Engineers Aren't Afraid of AI. They're Afraid of Becoming Junior Again. The conversation you'd expect when rolling out AI coding tools is straightforward. Your engineers are worried about job security. They're concerned about workflow disruption. They want to understand how this affects their career trajectory. These are legitimate concerns, and you plan to address […]
AI After an Apocalypse There's an unexamined assumption that has quietly become load-bearing infrastructure for entire categories of software: the internet is always on. This assumption used to matter mostly to mobile apps and remote workers. Now it matters to AI. An unreliable connection doesn't just interrupt your browsing. It interrupts your development workflow. You […]
Constitutional Prompting: Making AI Coding Agents Reliable Without the Iteration Tax AI coding agents are impressive when they work. They generate code that's functional, sometimes elegant, often exactly what you needed. But they often don't work on the first try. Getting them to generate the code you actually want usually requires iteration: generate, review, reject, […]
Spec Driven AI Development: A Real World Perspective on Getting Reliable AI-Assisted Code The difference between an AI system that generates useless code and one that reliably produces production-quality work often comes down to something surprisingly unglamorous: the specificity of the specification. When you give an AI agent a vague request—"build a user authentication system"—it […]
Web Directions South is the must-attend event of the year for anyone serious about web development
Phil Whitehouse General Manager, DT Sydney
