Claude Opus 4.8 is here. Is it as good as they say?

Welcome back to How I AI. I'm Claire Vo, product leader and AI obsessive here on a mission to help you build better with these new tools. Today, we have a very special mini episode because Anthropic just dropped Opus 4.8, their latest state of the art coding model. And I got a few hours of early access, and I'm here to share my very early thoughts about where this model is intended to perform well, where it did a great job and totally impressed me, and where there's still a little bit further to go. Let's get to it. As you can tell, I am not in my regular How I AI studio, and that's because I am so excited to give you my early thoughts on Opus 4.8 and couldn't wait between meetings to share what I thought. So to get started, I wanna talk about what this model is, what Anthropic has told us about its benchmarks, performance, and what it's good at. So Anthropic is shipping Opus 4.8. It is supposed to be their step change model for agents, and there's a couple things they've called out that this model does particularly well. It's supposed to be more honest, a less design flop, longer horizon autonomy on long running tasks, and enterprise ready. So it means it follows its instructions. And they're saying that Sweebench Pro, they're hitting 69.2%, which is almost five points higher than Opus 4.7, almost 10 points higher than GPT 5.5, and 15 points higher than Gemini 3.1. Now this model is not cheap. It's $5 per input tokens and $25 per million output tokens. And then same as 4.7, effort defaults to high and fast mode can be a lot faster. This is what they say. This is what you're gonna read on the blog post. And so on paper, this is a very exciting model. But I wanna tell you my personal experience using this model and where I thought it did a really good job and, again, where it did not do a perfect job. And so when I was getting feedback to the team, I said, surprise, surprise, LOL, it's a good coding model. In that when I opened up plot code and asked it to do a fairly complex one shot brand new surface area task, it did a pretty good job. So I asked, in Cloud Code, Opus four eight to build a prototyping capability in chat PRD. So we make PRDs. I said, let's just go whole hog. Let's, compete with the big boys. Let's make an entire prototyping tool. And I gave it some architecture decisions I wanted to make, what platforms I wanted to use, how I wanted it to function. It went through plan and then it autonomously coded for, I would say, about twenty minutes and shipped it. And when I pushed this live to my preview branch, it worked. And so I would say from a one shot feature, it …