Why the scientific method is the right foundation for AI adoption, and what that means in practice Most conversations about AI at work start in the wrong place. They start with the tool. Which model should we use? Should we try ChatGPT or Claude? Do we need to build something custom? The questions come fast, and they feel urgent. But they are the wrong questions to be asking first — because they assume the hard part is choosing the technology. It is not. Here is a more useful

Why the rules of the job market feel broken — and what both employers and employees are missing about what actually changed. A post recently circulating on LinkedIn captured something that many graduates feel but rarely articulate so clearly: "Study hard. You will get a higher salary when you grow up." "Be realistic. Lower your salary expectations." "Just because you have a degree doesn't mean anything." The same system that told young people what to aim for is now telling th

The competitive advantage isn't in the tools you buy. It's in the system you build. Two years ago, FYT started doing something most consulting firms weren't: actually using AI in our own work. Not just experimenting with prompts. Not reading vendor white papers. Actually redesigning our workflows around AI tools, testing what broke, fixing what didn't work, and building systems that held up under real operational pressure. What we learned didn't come from the internet. It cam

We have been publishing data-driven articles on questions that Singaporeans genuinely debate — and the response has been encouraging. Some of what we have covered so far: Is HDB resale housing really less affordable today? The data gives a more nuanced answer than the headlines suggest How data literacy changes the conversation — using the HDB debate to show how better questions lead to better conclusions Singapore's religious landscape by the numbers — which groups are large

A data literacy lesson from Singapore’s housing debate Two analyses can examine the same issue and reach very different conclusions. That does not always mean one is dishonest or the other is wrong. More often, it means they are asking slightly different questions, using different definitions, or starting from different assumptions. Singapore’s housing affordability debate offers a useful example. In an earlier article, we examined whether HDB resale housing has really become

A few years ago, if you asked managers what slowed decisions down, most would point to information. The report wasn't ready yet. The analysis wasn't complete. The data still needed cleaning. Someone was still preparing the presentation. The assumption seemed perfectly reasonable at the time. If organisations could get information faster, they could make better decisions. In many ways, the last twenty years of business technology have been built around that belief. We invested

Everyone is training people on tools. Nobody is training them to think when tools break Somewhere in your organisation right now, someone is staring at a report that worked perfectly yesterday and shows nothing today. They have refreshed. They have closed and reopened. They have tried the thing they tried last time, whatever that was. They are about to raise an IT ticket, or call a colleague, or quietly work around it and say nothing. They are not incompetent. They are undert

There’s a moment in many management meetings that feels strangely reassuring, and if you have spent enough time around dashboards, reports, and performance reviews, you have probably seen it before. The dashboard appears on the screen, the KPIs are green, the trends look stable, and within minutes the atmosphere in the room begins to relax. The numbers appear healthy, the charts seem consistent, and there is little evidence that anything requires immediate attention. Someone

Before Deciding What Your AI Agent Can Do, Decide Where Its Authority Ends Everyone seems to be talking about AI agents. Depending on who you ask, they are the next major leap in productivity. They can schedule meetings, process invoices, review contracts, answer customer enquiries, coordinate workflows, and increasingly interact with other systems with minimal human intervention. For organisations constantly trying to do more with less, the appeal is obvious. If an AI agent

Like many businesses, FYT's journey with Generative AI started as curiosity. A few emails drafted by ChatGPT. A LinkedIn post, polished in seconds. And yes — a few colleagues turned into Studio Ghibli characters, because why not. Then we got serious. We paid for licences. We put AI in the middle of our workflows — building proposals, designing custom GPT tools, developing frameworks, creating infographics. We experimented across platforms: ChatGPT, Claude, Gemini, Copilot. Wh