Frankly speaking ...

A Puzzle Without a Picture Genome sequencing faces a fundamental physical constraint: modern instruments cannot read a long chromosome continuously from end to end. Instead, they synthesise or capture millions of short sequence fragments called reads. These range from 150 base pairs in high-throughput short-read chemistry to tens of thousands of base pairs on long-read instruments—and well over a million base pairs with Oxford Nanopore ultra-long protocols. Reconstructing a complete genome from these fragments is like solving a multi-million-piece jigsaw puzzle without the picture on the box top. To tackle this challenge, I turned to graph-theoretical assembly frameworks. The Overlap-Layout-Consensus (OLC) paradigm is one of the classic, most intuitive ways to stitch fragments into continuous sequences called contigs. While building reconstruct-strings —a pure and total Haskell implementation of a greedy OLC assembler—I set out to explore sequence reconstruction from first princ...

AI-First Operating System I've spent the past month with Omarchy , and the short version is this: it is a fresh, lightweight Linux distro built for an AI-native workflow. Created by David Heinemeier Hansson (DHH) , Omarchy is unapologetically opinionated. Instead of a blank canvas, it offers a curated 'omakase' experience designed for the age of AI. The premise is simple: if you can use AI to generate an app quickly, you should be able to shape your entire operating system around the same workflow. I recently revived a 12-year-old ThinkPad X1 Carbon with Omarchy, and the difference was palpable. The machine felt notably snappier, more coherent, and more useful. All the hardware was fully recognised, including the fingerprint scanner. That is not a scientific benchmark, but it is exactly the sort of result that matters to a real user. Installation as a Speed Run One of the most striking things about Omarchy is how fast it gets you from power-on to a usable desktop. Th...

Globalisation gets blamed for almost every modern headache: hollowed-out factory suburbs, flatlining wages, and angry politics. At the same time, mainstream economists often speak about open trade as an unqualified miracle that lifted millions out of poverty. The truth sits in the middle. Global trade creates immense wealth, but it comes with a catch: the perks are spread thin across millions of shoppers, while the costs slam into specific suburbs, factories, and working families. To understand the political backlash tearing through Western democracies, we need to look past the talking points and audit who actually won, who lost, and what it cost. The Economists' Promise Mainstream economists have championed open trade since David Ricardo introduced comparative advantage in 1817. The basic logic is simple: when countries specialise in what they make best, overall output surges and prices fall. Bigger markets allow businesses to scale, capital flows to where it works hardest,...

The Fragility of Modern Foundations Almost everything in our modern world runs on software stacks that are terrifyingly fragile. From medical infusion pumps and power grids to autonomous vehicles, the systems we trust with our lives routinely depend on operating system kernels containing tens of millions of lines of code. In that kind of monolithic architecture, a single misplaced pointer or buffer overflow in a peripheral driver can compromise the entire machine. For decades, we have treated software security as an endless game of whack-a-mole: patch a vulnerability, ship an update, and hope attackers do not find the next hole first. The seL4 microkernel takes an entirely different path. Rather than trying to make a sprawling code base slightly less vulnerable, it strips the kernel down to a minimal core of roughly 10,000 lines of C. More importantly, it replaces wishful thinking with mathematical proof. It is not just another operating system; it is a demonstration of what soft...

Anyone following the AI boom will have heard two arguments pulling in opposite directions. The first says hardware and algorithms are improving so fast — chips getting quicker per watt, models shrinking through quantisation and distillation, software stacks tightening at every layer — that energy use should eventually level off. The second says the opposite: tech giants are signing multi-gigawatt power deals, bringing retired nuclear plants back online, and forecasting demand curves that only go up. I wanted to work out which story actually holds, so I went through the industry data myself. My conclusion is that the second camp has it right. Efficiency keeps improving, but it is not enough on its own. Total demand is going to keep accelerating for the rest of the decade. Why Efficiency Doesn't Mean Less Energy The reason the efficiency argument falls short has a name: Jevons' Paradox . Back in 1865, the economist William Stanley Jevons noticed something counterintuitive ab...

Linux is celebrating its 35th birthday , and commentators are once again asking if 2026 will finally be the "year of the Linux desktop". For the broader industry, that phrase has been a running joke for decades. But for me, the answer is much simpler: Linux has been the right environment for my work for years, and I have never really looked back. My own journey with Linux began in 1999, when I set out to build an open source development environment. That was a decision driven by my professional work. In those early days, I was focused on development tools and machine performance. I tuned kernels, adjusted desktop settings, and stripped systems down to maximise the performance of my modest hardware. I moved between RPM- and DEB-based distributions, and I even spent a rewarding period on FreeBSD. It was a good learning experience, and it was fun. That sense of fun is often overlooked, but it matters. As a developer, having access to a broad range of command-line tools and...