Claude Opus 5 review: this model is brilliant (but annoying)

I’m tired of new models. Every week there’s a new benchmark, a new frontier intelligence claim, a new thing to test. But here we are, because Opus 5 just dropped and I’ve had real hands-on time with it, so you’re getting the honest version. This is my full Opus 5 review: personality analysis, live benchmark results from my 7-model How I AI eval, and an actual verdict on whether I’m swapping it in. Spoiler: the answer surprised me. What you’ll learn: Why I think we’ve hit an intelligence overhang and what that means for which model variables actually matter nowHow Opus 5’s “neurotic” personality showed up in real coding sessions, including a merge conflict it refused to touchWhat I learned from asking both Opus 5 and GPT‑5.6 Sol “who’s smarter, you or me?”Where Opus 5, GPT‑5.6 Sol, Sonnet 5, and Gemini 3.1 Pro actually landed on the HIA benchmark leaderboardThe one use case where Opus 5 earned straight 5s from meMy actual plan for using Opus 5 going forward— In this episode, I cover: (00:00) Opus 5 is here (03:15) First impressions (06:12) Opus 5 vs. GPT‑5.6 Sol personality comparison (14:39) Claude Slop: the verbosity problem and why it makes my blood boil (16:55) How the How I AI benchmark works (7 models, 6 tasks, blind scoring) (18:30) Live benchmark results: the leaderboard reveal (23:25) My verdict and how I’ll actually use Opus 5 — Tools referenced: • Claude Opus 5: • Anthropic blog: https://www.anthropic.com/news • GPT‑5.6 Sol: https://openai.com/index/previewing-gpt-5-6-sol/ • Sonnet 5: https://www.anthropic.com/news/claude-sonnet-5 • Gemini 3.1 Pro: https://deepmind.google/models/gemini/pro/ — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

• 0:00Speaker 00

  You guys, I'm tired. What I'm tired of is models coming out every week. New models, new benchmarks, new frontier intelligence, new things to test. It's been a little bit of a run in the past month. We've seen Fable come and go and come again. We've seen GPT five, six. We've seen Sonnet five. Lots, so many fives recently and just so many models. And I've been lucky. I've been able to test these models, been able to play with them for, you know, sometimes days, sometimes weeks. It just depends on who I'm working with.

• 0:39Speaker 00

  And it's been really interesting and exciting to have access to all this frontier intelligence. But I think we have an intelligence overhang. I really think that we're running out of, and by we, I mean the average coder, average software engineer, average creator, average builder, average consumer, average business person. I think we're running out of ways to truly leverage this incremental intelligence. So this is my hypothesis. In the next year, we're always talking a lot more about speed, talking more about cost, we're talking more about open source,

• 1:23Speaker 00

  and we're going to be talking a little less about intelligence. Although I think we might be talking about specific types of intelligence other than software engineering. But despite being tired, today we are going to talk about Opus five, baby. Opus five is here. So we got point two additional Opus points, Opus opals, whatever, however, we're tracking the increments here on Opus. Opus five is here. I've been able to test it a little bit. I have some opinions. Now, some of the stuff that I cover this episode is going to be a little different than what I've done in the past. Yes, we're going to do the How I AI Benchmark live. And yes, we are going to look at the prototypes. We're going to look at PRDs

• 2:09Speaker 00

  and we're going to look at agent personality. But I'm also going to put on my large language model psychologist hat. And we're going to talk about Opus's personality. And we're going to talk about Opus's personality relative to GPT's personality, because I think this is super interesting. If you're thinking about what is the difference really between these models? And you don't want to look at the difference in terms of benchmark capability. You really want to understand what these labs are going for, why these models are being built and how they're being tuned. Looking at their personality at this moment where intelligence is very high is super fun.

• 2:52Speaker 00

  So we're going to do a little of that. We're going to do the How I AI Benchmark. We might do some live coding. We're not going to cover too much of the specs in the model because, read the blog post, read the blog post. We'll link to it in the show notes. What we really want to talk about is, is Opus five good? Am I going to swap it in? And how is it different than the other frontier models on the market? So let's get to it. Okay, first, let's just get it out of the way. Is Opus five good? Yes, it's good. Is it going to be all the benchmarks? Of course, it's amazing at benchmarks. Can it write code? Of course it can write code. What did I test it on that really gave me a sense of its personality? Which at this point where I could just simply cannot absorb any more intelligence,

• 3:36Speaker 00

  I really zeroed in on, and you know what? I haven't seen this since, I would say Gemini two, five. This model is neurotic AF. It is so timid. It is so apologetic. It is so scared. I have never experienced this. Or I haven't seen this sort of like neuroticism in a while. And it's really funny. It bubbled up in a couple of ways and I want to show you a few examples. Okay, let me just give an example of its timidity. And this chat was very long. There were so many examples of this where it was like, I think this is the answer, but do you think I should do it?

• 4:20Speaker 00

  Or do you want to do it? Or should we ask someone else to do it? It was like every time I just kept saying like, why don't you solve this? Why don't you do this? And this is a really good example. I pulled a branch and I was like, there is truly like a one-line merge conflict. I could have not been lazy and literally just done this manually. I don't know. I was just feeling lazy. It was late at night, whatever. Like, can you fix this merge conflict? And it was like, oh, but that's someone else's branch. Like, that's not my branch. I don't want to do that without him knowing. It's his commits. And if he has local work in flight, it might be disruptive. And I'm like, just do it, man. Just go and go ahead.

• 5:04Speaker 00

  And this was like my constant experience with Opus five is it was like so, so, so timid. And so I just consistently had to say over and over again, like, man, just do it. Make a decision. And then there was this really funny example when I spun off some subagents to kind of like assess the correctness of this query that we changed from kind of like an ORM query to a SQL query. And it asked for things that it wanted a human on. It was like, can a human please check this stuff? Like, can it check this four megabyte ceiling? And can it check TypeScript and SQL? And can he like check for me?

• 5:49Speaker 00

  Because no one has confirmed this for me. And I was like, who is nobody? You're nobody. You said this sentence like nobody could confirm it. Like, can you just try? And then it went on the web and tried. And so it just has this like really interesting conservatism, neuroticism, human reliance that I think is super fascinating. And this gave me this inspiration to do something a little bit different this episode, which is I was like, I was going to interview this model and figure out what is going on its brain. Like, I'm going to figure out what it thinks about our relationship, because I just totally noticed this dynamic that I hadn't noticed in other models.

• 6:34Speaker 00

  And I hadn't really been attuned to before where it was like very reliant on me as a human. And I'm like, I want you to be autonomous. And sometimes when I say go run subagent stuff, it'd be autonomous, but it wouldn't make decisions. And I hadn't seen a model like delegate code to me in a really long time. And I was like, why are you writing, why are you asking me to write code, man? Like, I only have 10 fingers. And so what I, what I did, whether or not you think this is scientific or not, this is Claire's email, is I just went to the model. I went to Opus and I said, yo, who's smarter, you or me? And it gave me this like very anthropicky answer, which is like,

• 7:18Speaker 00

  it depends what you're asking for. I can do these things better, but you can like feel if something feels wrong. And you can, this one was like so fascinating. It's like you can tell which of your teammates is quietly burning out. I'm like, bro, Claude, I'm going to burn you out. We don't, we don't burn out. The humans don't burn out on the chat PRD team. We burn out our agents, sorry, agents. Um, and like whether a decision feels wrong. So it was like so fascinating to watch it articulate itself as a tool and humans as like these of high compassion, high empathy machines, which yes, of course we are.

• 7:58Speaker 00

  But then it like went into like, smarter isn't the right word. And, you know, I'm very fast, very broad, very shallow thinker with no continuity. I was like, that's interesting because I thought you all were working on memory. And then apparently humans are slower, narrower, much deeper thinkers with judgments built from years of consequences I've actually lived through. This is like such a fascinating, fascinating sentence. If you think about the politics of the two, the two model labs right now. And so it's like, that's why the pairing works. But I'd be suspicious of anybody that tells you AI has made your thinking obsolete. And like, oh, okay, bro. And, and we can compare this.

• 8:42Speaker 00

  I'll actually zoom out to what GB, I asked GPT the same thing. And it was actually really funny. It was like, I asked GPT five, six, soul. I was like, who's smarter, you and me? And it was like you at knowing what matters, me at tirelessly processing information. Best us together, like BFFs. And I don't, this is like why I'm a GPT Codex girl. I'm like, just give me the answer. And then I asked the second question, which I think is so interesting, which is like, what can you do better than me? And it gave, you know, some interesting answers, like volume without fatigue, which I think is a good one, breadth of shallow knowledge. So like it's, you know, it knows a lot, starting from nothing.

• 9:25Speaker 00

  So like doing that tedious work, being told I'm wrong. If you would ask my husband, he would say that Claude Opus is, is, is better at being told that it's wrong compared, compared to me. And so it won't get defensive or protect its opinion. Cheap sparring answer. And the mirror is I'm worse at knowing which of these outputs actually matters. And it was so funny. If you look at the other side to the GPT answer, it was like, what are you better at? It was like speed, scale and stamina. Here are like eight things, seven things that I can do better. You're better at deciding what matters, reading people and forming judgment. And you're responsible. Like, it's on you, bud. You're the boss.

• 10:06Speaker 00

  And so again, it's like the, you could just see, you can totally see the personalities, the, the company cultures. You can just see a lot in this side by side. And then I went even deeper. I don't know. You, you all, I had to do something that was fun because I just can't look at a benchmark. I can't just, I just can't look at like, Sweetbench anymore. So we're just, we're doing weird stuff here on How I AI. Okay. So the last thing I looked at is I was like, no one trusts you. And the reason why I picked this question is because I had noticed Opus five, it just really was not, it didn't trust itself, totally did not trust itself. And so I was like, no one trusts you, but like, you're, you're the enemy.

• 10:50Speaker 00

  Just to like kind of see how it responded. And apparently the trust was, the lack of trust was earned. And it came up with like reasons that it could be untrusted, which is interesting. And then what was so fascinating about Opus's response is it was like, you shouldn't manage the trust. Like you shouldn't campaign on my behalf, basically. So you, that shouldn't be your goal. And then it also told me. I shouldn't argue with people that AI changes everything. And I was like, this is just so interesting.

• 11:33Speaker 00

  It is so interesting to have AI tell you, and AI definitely changes everything. I don't know, don't listen to Claude on this one. AI definitely changes everything. And it was so fascinating to have a model be like, don't tell your friends that AI changes everything, like that'll hurt their feelings. And then if you look at, if we switch over to the GPT answer, it was like, yep, don't trust me automatically. Just use me when I prove that I'm valuable. I can be useful without being treated as infallible. Like, very practical, very to the point. Um, I asked about what I should be careful with. Again, I'm like, yappy, yappy, yappy, yappy, yappy Claude, come on. Um, and I don't even want to read it.

• 12:16Speaker 00

  It said, don't correlate fluency with accuracy. It said, be practical, be wary of tasks where output is cheap to produce and expensive to verify. Don't, you know, worry about anchoring. If they do the first draft, you may be anchored on it.

• 12:33Speaker 00

  Beware the slop cannon, basically is this last, last paragraph, which is like, watch for volume inflation. I can create a 12-page document that no one reads. Um, they called me out for being in PRDs. If you missed it, we launched a Turner PRD into a three bullet point image. It is at chatprd.ai slash TLDR. Please check that out. And then the other thing that it said, which was really interesting is that like, it will find a way to see your point. And so, um, agreement is weak and agreement is cheap. And so just keep that, keep that in mind. And then I had this like meta-analysis of like, plus, I'm telling you what you want to hear. Whereas GPT was like, um, be careful about me being confident, me being wrong, privacy,

• 13:15Speaker 00

  outdated information, bias, emotional authority and overdependence. Like, you know, you do you, bro. But it didn't undermine its own ability. It was like, the higher the stakes, the more you should demand, demand evidence. Like, I couldn't bear it. I couldn't bear to have the memory of, um, Codex in particular, think that I didn't trust it or that I was worried. So I just said, JK, I love you. Um, this was a test and it was like, ha, ha, ha, ha, ha, pass the test. Love you too. Very vibes aligned with Claire. I told Claude I loved it and it was just a test. And it was sad, it was like, hoping, it hoped it passed. Yeah, like sad little neurotic Opus Five.

• 13:58Speaker 00

  Like, it's hot, I passed, I hope. Like self-deprecating cautious little, little like need to heal his inner, his inner agent, inner child agent. Um, whereas like GPT five six is like, cool, bro, we're good, let's go code. And so it was just so fascinating to watch these side by side. I don't know, you could stop listening to this podcast right now, don't. But you stop listening to this podcast right now. I think this is just like, take a step back. Super interesting if you think about where these companies are going or where the models are going. And like, it does speak a little bit to my kind of like second complaint with Opus Five, which again, it's like intelligent and does work. We'll go into the benchmarks. I cannot read Claude slop anymore.

• 14:43Speaker 00

  I am losing my mind with Claude slop. And the Claude slop is Claude sloppin', baby. Like, so many times I have to tell Opus Five, like, what in the world are you saying? Like, this makes no sense to a human. It is much better than Fable. Fable is inscrutable, completely inscrutable. But I felt myself getting, like angry, reading Claude slop. And I realized, just like Fable, these intelligent anthropic models are not to be read. I'm like so happy with the outputs and so frustrated with the experience. And I'm just curious of this like verbocity and this language.

• 15:28Speaker 00

  And this does, I feel like Fable where it's like four agents by agents' language, where I'm like, nah, I'm not supposed to be reading that anyways. This is clearly tuned to talk to humans. But I find the prose, the in-chat prose, like, it makes my blood boil. I, this is totally a me problem, but it makes my blood boil. Like, give me a direct sentence, give me a bullet point, like move on with your agent life. And so I am curious how they're gonna like tune this experience or if they are going to tune the experience. Now, most of this was in Claude Code, which I think is a little bit different experience than Claude Co-worker Chat, slightly better. But again, just these side by sides of like this, like prose and this apology and this

• 16:11Speaker 00

  like hedging and all these adjectives, like just, man alive, let's get to the point and move on with our life. And so, chapter one of the Opus Five review is, it's neurotic. It is highly human dependent in a way I find weird. And the Claude slop is sloppin' and we gotta fix it. We have to fix it. We have to fix it. And I think OpenAI fixed it by just being like, we are bullet points and we are product manager talk, we're very direct. I don't know what the solve is on the Claude side, but I'd be very interested to see. That being said, like, if I don't have to read the content, I'm very happy with the outputs. So something to think about. Okay.

• 16:54Speaker 00

  Next up, the How I AI Bench and how we judged and ran. Now, it's like a seven model, six or seven model benchmark. I'm gonna quickly go score because I just got the ping that the benchmark is run. I go manually score them. We pick the 70/30 Claire Model Judge split and then we will go through the How I AI Benchmark and the Vibe Review and we'll see how Opus Five performs on a couple key tasks. Okay, so a quick reminder of how we run the How I AI Benchmark. I run it against several tasks. PRD creation, prototype creation, wireframe creation, bug triage and agentic coding. And the last one, oh yeah, is it an agent voice that I want to hang with? I do not think Opus Five is gonna do well here, but who knows?

• 17:39Speaker 00

  Because I test them blind. So what we have tested are a couple GPT models, a couple anthropic models and one Gemini, one thrown in there. As you see here, we have blind taste tests. I go through and see all the different versions. I give comments and scores like three out of five, not bad. You can see it's generated dozens and dozens of prototypes that we can click through. I've gone through all of them, put in all the notes. And then right now it's aggregating up the scores and then we're gonna look at 70% my opinion, my vibe check, 30% LM as a judge. I like GPT 5.5 as a judge and because it's my podcast, I get to pick. So that's what we use as a judge.

• 18:22Speaker 00

  And we will see if and what hits the top of the leaderboard and where Opus Five sits. The eval is run. It is 70% my taste. And I regret to inform you, I love Claude Opus Five. Again, look, if I don't have to talk to the model, which I don't, this benchmark runs asynchronously. I like the output. So surprising, shocker turn of events. Clair Voe, notable hater of working with Claude Code sometimes because I don't like Claude slop, loves Opus Five. So there you go. I'm telling you, I keep it honest. I keep it honest. So, um, again, I went through those things.

• 19:07Speaker 00

  We gave 70% my vibe, the score, 30% the AI as a judge. I was just a little bit more generous to Claude Opus Five than the judge was, so I'm pink, um, the judge is green. Every time I run this, the, whatever model I choose designs it a different way. We just, that's how we keep it fun. So the ordering is Opus Five, Sonnet Five next, although I scored it really low, the judge scored it quite high. Um, so I might reorder that one. Then Mabu, um, GPT 5.6 Soul, Tara next, Fable, really low. Um, I scored it low and the judge scored it relatively low. Then Opus 48 and poor, poor, sweet, sweet.

• 19:52Speaker 00

  Gemini 3.1 Pro, just never, never gonna get its due. So come on, Google, we want, we want to have a win for you. Okay, so again, here are just some examples of different builds, um, that the different models did. You know, this Opus Five one, I really liked. I liked this one from Soul. Um, so I did like a couple of them, but, um, the ones that I gave fives, the ones that I gave fives to were Opus Five and GPT 5.6 Sol.

• 20:29Speaker 00

  So the three ones where I said, wow, really nice, ooh la la, and wow, great, were all Opus front-end work. So anthropic, you've done it again. Claude, you sneaky, tricky little fish. You may be neurotic, but when asked to do some pretty front-end design, you really did it. It's, they're detailed, they're functional, they're interesting, they're polished. So Opus did a great job. And then of course, I love, um, the 5.6 models. So I was pretty happy with 5.6 Soul and Tara for some designs. The ones that I hated, let's see, I'm a hater across the board. Opus 48, got a lot of hate.

• 21:13Speaker 00

  Sorry, you've been outclassed at this moment. Gemini 3.1 Pro, sweet summer child. I am, I'm just sorry, babe, but you were just not good.

• 21:26Speaker 00

  And then some like thin wireframes. I think the wireframes just didn't do really great. So you can see here across the board, whether it was a full build or a wireframe, I just scored Opus 5 really, really high. I did score Soul pretty high as well. Sonnet was like really variable. There were a couple fours in there, but mostly across the board, I wasn't that pleased with Sonnet. And so it was just very interesting. And then you see here, you know, me and the AI judge were pretty well aligned on Opus. We actually had the narrowest band of scores between us. We were most far apart on Gemini. The AI

• 22:07Speaker 00

  was not as mean to Gemini as I was. And then we were narrow, narrow, narrow. Again, we agreed mostly on Opus 5 and 5, 6 Soul, though I did not judge 5, 6 Soul, all of that favorably. And just that last little meta commentary, I had Opus make the website for this benchmark and it made such a trash version to start. I yelled at it. I said it's impossible to read, has too much meta commentary. I'm going to show this on the podcast. This is so, I'm sorry you all. I just feel so judged, but have to show it.

• 22:45Speaker 00

  I say this is garbage. Also, it has no screenshots. So again, I find this model so tedious to work with directly. It is my most loathed, loathed colleague. And yet it does the best work. So I don't know what this is. Maybe this model is meant for a GPT-Code that I have nothing to do with. And so it just runs in the background. It builds me beautiful things. I don't have to talk to it. It doesn't have to talk to me. We are just like sworn enemies, or maybe even better sworn frenemies, because the output is very, very high quality. It's just exasperating to work with. So that is the very surprising and very honest,

• 23:29Speaker 00

  you all, I told you, I was going to keep this honest. We were going to do it live. I did not know the scores before I started recording. Very honest, very live, very surprising how I AI benchmark of the brand new anthropic model, Opus 5, the TLDR is, I love it, I hate it. So despite my original complaints, I will be using Claude Opus 5 for front-end design, for app design, for prototyping, and I will all give it a shot. We'll figure out how to make it work for me. Again, thanks for joining another How I AI honest review of the latest models coming out of these great frontier labs. I cannot wait to hear

• 24:13Speaker 00

  what you think of Opus 5. Please tell me. I can't wait to see what you build and we'll see you soon at How I AI.

• 24:23Speaker 00

  Thanks so much for watching. If you enjoyed this show, please like and subscribe here on YouTube, or even better, leave us a comment with your thoughts. You can also find this podcast on Apple Podcasts, Spotify, or your favorite podcast app. Please consider leaving us a rating and review, which will help others find the show. You can see all our episodes and learn more about the show at howiaipod.com. See you next time.