I tried to write down how my use of AI changed. It’s from memory, so some dates are fuzzy. Around early 2025 I started using Cursor. My reaction was basically: this is so damn good. I started writing part of my code with it. A few months later I found Claude Code and switched. That was about a year and a half ago. What it couldn’t do back then In mid-2025 I could not get it to write a single unit test for a service I was working on. It just kept failing. Browser use was the other wall. It got confused and the clicks kept missing. I tried all kinds of tricks. My UI was probably part of the problem, but it never really worked. Now unit tests are not a problem at all, and it uses the browser fine for everything I do. I mostly don’t do deploys by hand anymore either. If the repo is simple, most tasks are one sentence and it’s done. Where I still get stuck: design Architecture design is where it still falls short for me. When a problem has a lot of options, it doesn’t have a good sense of which tradeoffs matter most for our situation. On one design, it could give me something that works. But after I had it read a bunch of open source projects, it came back with something huge. Or it said “just use Knative.” Knative is pretty complicated too. Then it designed a complex async setup. It worked. It just didn’t know what mattered for our use case. I went with the simplest option and built a small one myself. It also changes its mind easily. I push one way and it says that’s right. I ask about the other option and it says, if you look at it that way, pick the other one. It doesn’t hold its own opinion very strongly. Some of these decisions are hard, to be fair. But I’ve had design chats go in circles until I was exhausted. What I think comes next Before it was the browser, now it’s design. I think design and taste will catch up too. It’s all intelligence. But I honestly don’t know. Things move so fast I can’t even remember when ChatGPT came out. I think the next step goes past coding. You give it a task, and it implements, tests, deploys, monitors, and keeps iterating on its own. People define the task, and tasks come from business requirements. At some point people may stop reviewing the details. Someone proposes an idea, we check at a high level if the direction makes sense, and decide if the project is worth doing at all. If yes, it goes and does it. One part I don’t think fully closes: people come up with new needs. A lot of products are for people, so people stay the ones asking. For things that don’t face people directly, like two services talking to each other, a few agents could take a new requirement and design and build it together. How much someone gets out of this probably depends on how well they understand the business. So if everyone ends up with that loop, what makes anyone different? I think AI will help science and math a lot. Models will keep getting smarter and cheaper. Next to closing the loop, that feels like a smaller change. Coding already feels mostly solved to me. The question is turning into what people need and what we should build. Hardware is another bottleneck. Software can move really fast, hardware can’t. Intelligence in the physical world looks like a huge area next. I don’t know much about it. But if robots like Optimus actually reach mass production in the next year or two, that could be a first milestone. Could the next five to ten years bring a big jump there? Curious where it still falls short for others who have used it this long. submitted by /u/No_Rub1596
Originally posted by u/No_Rub1596 on r/ClaudeCode
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