I tried copilot in VS Code sometime in 2025 and was thoroughly disappointed with its ability. It felt like a really bad auto-complete at best, making plenty of mistakes and generally being utterly irritating to actually use with its need to constantly pop in as I was typing with long form coding suggestions that were often wrong. I was already predisposed to being negative about AI due to the usual mix of reasons and wrote off all the AI coding tools as useless. All the AI-pilled people shouting about how good the AIs were were clearly just novice programmers who didn’t understand enough about programming to know they were generating rubbish.

Over December I noticed an uptick in people that I highly respect using Claude Code 4.5 in particular, and this got me curious. I knew the AI was rubbish. These are people I have a huge respect for (I worked with a fair few of them and knew first hand how good at programming they were). What the heck were they seeing in the AI that I wasn’t?. So I got the cheapest Claude Code plan and started messing around.

I wanted to evaluate it against something that wasn’t on the internet already that it could find or have seen, and something that I wrote and knew intimately. That way I could judge its ability and compare what it produced against what I had. I have a little Rust project that scrapes a bunch of financial data on the various stocks I’m invested in, and gives me fundamentals so that I know at a glance that the companies are still in as good as a shape as I expected.

I explained to Claude Code what I wanted at a high level (write it in Rust, get the data from here, calculate these metrics). I was pleasantly surprised when it came back to me asking me follow-up questions to check it understood what I wanted (remember - I hadn’t used Claude Code before nor seen it in use, so I was discovering how it worked as I went!). It went off and burned a bunch of tokens from my plan and then it was done. I ran the program, compared its output to my own. It matched. Huh I thought. I looked at the code. Well commented, laid out nicely, it had even optimized a few of the async http request queries in a way I hadn’t thought to do. Huh.

Then Claude Code 4.6 came out with the new models. And oh boy they are better. I pointed it at my previous blog post I [[musttail]] You About a Tokenizer and asked it to flesh that out into a fully fledged programming language with a few tips here and there of how I wanted it to look. And it just smashed through it, writing lots of unit tests on its way. Huh. I upgraded to the Max plan.

I’ve since recommended to many people, who were of varying degrees AI-sceptical, that they try Claude Code. The conversation has roughly went like this:

  • Me: “You should try Claude Code.”
  • Them: “Nah AI is rubbish.”
  • Me: “No seriously give it a go and tell me what you think.”
  • Them: tries Claude Code “Ok its pretty good.”
  • Me: “Isn’t it?”
  • Them: “I’ve just upgraded to the Max plan.”

This has happened multiple times now, with a similar flow.

My best description of what is happening to our industry now is that we’re collectively going through the Five Stages of Grief for the craft we all love:

  • Denial: I was telling everyone how crap the AI tooling was.
  • Anger: I was getting angry at all the AI lovers telling me how good the models were.
  • Bargaining: I was realising the AIs could do something but not my job.
  • Depression: I got really down that the thing I’ve made a huge part of my identity, coding, was being affected.
  • Acceptance: I’m now realising that I can use these tools to magnify what I want my code to do by using all the knowledge and taste I’ve accumulated to craft more software of the ilk I desire.

That’s my journey with this, but I’ve seen many many people across the industry who seem to me to be in the various stages. It sucks to be a craft furniture maker when IKEA just showed up in town.

Now don’t get me wrong - there are problems with the models. They are not perfect. They are like a super eager beaver intern and need a good set of rules to follow to make software you like. But once you start using them you realise how you can craft these rules so that the models produce quality code that meets your quality bar.

But it’s starting to feel essential to my future employment, perhaps all future employment in our industry, that I learn how to do this scaffolding.