It is not a secret anymore. Most developers use AI tools now. If you are not using something like GitHub Copilot, Claude Code, OpenAI Codex, or even just pasting problems into ChatGPT, you are probably in the minority. The stigma has evaporated. Nobody is pretending they wrote every line by hand anymore.
Using AI to write code is just what we do now, like using Stack Overflow was ten years ago except the answers are usually better and you do not have to scroll past three people arguing about whether the question is a duplicate.
I have been working remotely full time since 2018. Eight years. That is eight years of not sitting in traffic, inhaling the fumes of a thousand other miserable commuters while some breakfast radio hosts laugh at their own jokes. Eight years of being home. Eight years of being present for the moments that actually matter.
I watched my children take their first steps. Not on a grainy video my wife sent me while I pretended to care about Jira tickets in some open plan office. I was there. In the room. I saw it happen live. That is not a humble brag. That is the point. That memory exists because I was home, not because I got lucky with timing.
I have had more ideas than I can count. A notes folder full of app concepts, half-baked prototypes in forgotten repos, domain names I bought in a fit of optimism at 2am. Over a decade of this. Life gets in the way. Work gets in the way. Kids, mortgages, health, relationships, fatigue. The ideas pile up and the backlog grows.
If you look at my GitHub, you might think I ship a lot. Nearly 200 repositories. Aurelia plugins, blockchain games, CLI tools, a regex battle game, apps for finance tracking and tattoo previews and bedtime stories. From the outside it probably looks prolific. But I know what is missing. The projects that never left my head. The code that never got written. The things I talked about for years and never touched.
I have never been a TDD purist. The whole write-tests-first-no-exceptions religion always felt a bit much. Sometimes you are exploring. Sometimes you do not know what the code should do until you have written it. Sometimes you just need to ship the thing and circle back to tests later. I get it. I have lived it.
But AI assisted coding has changed my relationship with TDD. Not because I suddenly found religion, but because tests solve a very specific problem that AI introduces: you cannot trust the output.
Every morning at 9:15, a dozen developers shuffle into a room or log into a video call to answer the same three questions they answered yesterday. What did you do? What will you do? Any blockers?
We have been doing this ritual for so long that questioning it feels like questioning gravity. Stand-ups are just how teams work. Everyone does them. They must be valuable.
Except they are not. The daily stand-up, as practiced in most organisations, is not a communication tool. It is a surveillance mechanism dressed up in Agile clothing. And in 2025, with distributed teams and async-first tooling, it has become an actively harmful anachronism that we keep doing because nobody wants to be the person who suggests we stop.
I get asked this question a lot. Usually with a tone somewhere between genuine curiosity and thinly veiled accusation. Where do you find the time? You have a full time job. You have kids. You have a wife. You have this blog. You have side projects. You take on contracting work. You contribute to open source. When do you sleep? Are you okay? Is this a cry for help?
The honest answer is that I have an incredibly understanding wife.
In less than a week, Australia becomes the first democracy in the world to ban under-16s from social media. On December 10th, 2025, platforms like TikTok, Instagram, YouTube, X, Snapchat, Reddit, and Twitch will be legally required to boot millions of Australian teenagers off their platforms or face fines up to $50 million per violation.
We are about to run a massive social experiment on an entire generation. And I do not think protecting children is the real goal here.
Every time an AI music app starts feeling like the future, the labels show up with lawsuits and NDAs. This month they skipped the velvet gloves and went straight to taking the keys. The goal is not safety or artist love. It is control, and they are getting it by strangling the very features that made these tools fun.
When Udio slammed the door On October 30, Udio killed downloads without warning while announcing its Universal deal. A few days later it tossed users a 48 hour retrieval window as a peace offering, then shut the chute again. The platform that promised you owned your outputs is now a walled garden where your own songs cannot leave. The angry Discords and refund requests did not move the needle because the settlement terms mattered more than the people who built the hype.
Claude Code fell off a cliff these last few weeks. Anyone actually using it felt the drop: dumber edits, lost context, contradictions, the works. No, we weren’t imagining it.
Well, Anthropic has finally spoken and said what many of us already knew weeks ago. From their incident post on September 8:
Investigating - Last week, we opened an incident to investigate degraded quality in some Claude model responses. We found two separate issues that we’ve now resolved. We are continuing to monitor for any ongoing quality issues, including reports of degradation for Claude Opus 4.1.
I like good tools as much as anyone, but the last couple of weeks around Anthropic’s Claude 4 family have been a reminder that you can’t build your working life on shifting sand. Models change, limits move, and entire features wobble without much notice. Useful? Absolutely. Dependable enough to be your only plan? Not even close.
If you’ve been anywhere near Claude lately you’ve probably felt the turbulence. Some days are fine; other days you’re staring at elevated errors, partial outages, or features that feel half-broken. Claude Code in particular has been hot-and-cold: one session will cruise through a tricky refactor, and the next will cough, forget context, or hit a wall with token and usage limits. That volatility isn’t new in AI land, but the frequency and breadth of issues recently has been hard to ignore.