I have spent a lot of years writing documentation, first for Aurelia 1 and more recently for Aurelia 2 at docs.aurelia.io. The scale taught me a few things that travel beyond any framework. Good docs are not marketing. Good docs help someone ship. That is the bar I write to.
I built a new thing: Hive Ships. It lives at https://hive-ships.com and it turns the classic Battleship idea into a turn based, competitive game on the Hive blockchain. You place your fleet, you face another player, and the winner earns HIVE. Simple rules, quick rounds, real stakes.
WordPress is underrated. If you only hang out in framework circles you would think it is old, clunky, or not serious enough for modern work. I keep finding the opposite. For many projects it is the most practical path to a high quality site that real people can edit, host and keep running without drama.
I write code for a living, but more and more I feel like my job is designing systems. Some of those systems include code I type. Some include services, models and tools that I orchestrate. The biggest shift is mental: stop thinking in files and start thinking in flows, boundaries, feedback and failure. If you have solid fundamentals, this moment can multiply your impact. If you treat every new tool like magic, it will waste your time and your client’s money.
I like boring technology. Not because I am against progress, but because most projects are not auditions for a conference talk. Clients want results they can afford, host, edit and keep running when I am not around. That means choosing tools for outcomes, not for hype.
Let’s get one thing straight: the only people demanding a return to the office are executives who still think “synergy” happens in fluorescent-lit conference rooms and that “collaboration” requires smelling someone’s tuna sandwich from three desks away. Spoiler alert: it doesn’t. Forcing employees back to offices isn’t about productivity or culture. It’s about power. And companies clinging to this delusion are about to get left in the dust by those smart enough to embrace reality.
Welcome to the main event: an AI free-for-all where OpenAI, Google, and Anthropic swagger into the ring with their trillion-parameter hype machines—then promptly lose their cool when a ragtag Chinese startup named DeepSeek R1 strolls in, spending less than Sam Altman’s annual hoodie budget. While OpenAI and Google play SimCity with billion-dollar compute clusters, DeepSeek’s crew apparently cracked the code using ramen money and a Costco pallet of export-controlled GPUs.
Let’s rewind to 2010. Barack Obama was president, Instagram hadn’t yet convinced us to ruin our meals with Valencia filters, and I, a bright-eyed blogger armed with a domain name and a dream, installed WordPress. Fast-forward 15 years, and here we are: my blog is old enough to start asking for the car keys, and I’ve finally thrown WordPress into the retirement home. Let me tell you why—and why you might want to, too.
When OpenAI announced Operator this week a ChatGPT-powered AI that can supposedly autonomously book flights, shop online, and manage your life, I immediately envisioned Jarvis from Iron Man casually ordering me artisanal croissants while I nap. Instead, after using it for a few hours, I feel like I just watched a self-driving car get confused by a stop sign. It’s… adorably underwhelming. The Hype vs. The Reality Operator’s core pitch is seductive: an AI that can take over tedious digital tasks by using a web browser to do things like a human would. But right now? It’s less Tony Stark’s butler and more that one coworker who takes 45 minutes to figure out how to mute themselves on Zoom.
For years, the AI frontier has been dominated by a handful of players: OpenAI, Google, Anthropic, and Meta. Armed with seemingly infinite resources, these companies have dictated the pace of innovation, releasing model after model while driving the narrative that only colossal budgets and exclusive datasets can produce cutting-edge AI. But the release of DeepSeek R1 has shattered this illusion—and it’s putting the old guard on notice. Let’s break this down. DeepSeek R1, developed by the relatively unknown Chinese startup DeepSeek, cost just $5.58 million to train. This figure is peanuts compared to the estimated hundreds of millions poured into training GPT-4, Claude 3.5, and other flagship models. Yet, in terms of performance, DeepSeek R1 is standing toe-to-toe with OpenAI’s o1 and beating Google’s offerings (including the new 2.0 and experimental models) in areas like advanced reasoning, math, and code generation.