Claude Opus 4.7 is Anthropic’s most advanced generally available AI model, built for complex reasoning and agentic coding. It handles long-running tasks, follows instructions precisely, verifies outputs, and delivers high-quality results across coding, research, and workflows.
Claude Opus 4.7 looks like a serious leap forward for AI-powered development and knowledge work. It tackles a key problem: handling complex, long-running tasks that previously required constant human supervision.
With stronger instruction-following, better multimodal vision, and improved reasoning consistency, it enables users to confidently delegate harder workflows.
Why it stands out:
Verifies its own outputs for higher reliability
Maintains coherence across long, multi-step tasks
Improved high-resolution image understanding
Better memory across sessions for ongoing work
Key features:
Advanced coding + agentic task handling
`/ultrareview` for deep code reviews
Effort control (high → xhigh) for better reasoning vs latency tradeoff
Available across API, Claude apps, and major cloud platforms
Who it’s for & use cases:
Developers building AI agents and automations
Analysts working on finance, research, and modeling
Teams handling complex docs, workflows, and long-running tasks
If you’re building AI agents or scaling complex workflows, this feels like a meaningful upgrade.
P.S. I hunt the latest and greatest launches in tech, SaaS and AI, follow to be notified →@rohanrecommends
I've noticed a regression in 4.7's intelligence to the point that I wanted to revert to 4.6. I don't know what I'm missing, and maybe it's because it seemed to rollout while I was mid-session, but it was like it forgot all of my established sources and processes, and then it started to make factual claims that were completely hallucinated when 4.6 would have grounded in my knowledge based. Felt very odd. Seems to be okay today, but a strange anecdote I thought I'd share.
been running Opus 4.7 in Claude Code for the past couple days and the agentic stuff is noticeably better than 4.6. it actually follows through on multi-file refactors without losing context halfway through which was my biggest complaint before. the effort control slider is nice too — i keep it on high for architecture work and drop it down for quick fixes. only gripe so far is the adaptive thinking sometimes skips reasoning on queries it probably shouldn't, but overall it's a solid step up for daily coding work
I love how it leaves little notes for clarity on what has been done and what is yet to be done. I think it helps to align the model with the users vision and contributes to the amount of time you can spend in one session. With a million tokens it truly feels like the conversation gets easier and easier the more tokens you use. Scary how human it feels after ~ 500k tokens
Multiple people here mention token consumption being brutal. What's the rough token count on a typical multi-file refactor compared to Opus 4? Trying to figure out if the quality jump justifies the cost jump before committing to it for longer sessions.
the agentic coding benchmarks look wild — curious how it handles really long-horizon tasks in practice vs. the SWE-bench numbers. anyone tried it on multi-hour agent workflows yet?
Opus 4.7 sounds impressive for complex reasoning tasks. I'm curious about the agentic coding capabilities - when Claude is running long-running tasks autonomously, I'm wondering how others find it handling decision-making any better when it encounters ambiguous requirements or edge cases. Does it ask for clarification or make intelligent assumptions any better?
I've Been testing 4.7 both coding in Terminal CLI and chatting about my projects on Claude.ai and at least it feels like there is a great leap in understanding of complex dynamics. 4.6 was already Impressive but this seems to be yet on another level.
On the Claude.ai chat side I feel like Opus is now pushing me even more towards getting things done and ready for my launch and this is the first time that it took the iniative to really hash out all the angles about what we've been developing, and for the first time I didn't had to ask it to read the project files and am actually impressed in the way it understood some intricacies that I've been explaining again and again to 4.6 even when those small details have been saved in the project memory several times. Now we got straight to the point without me having to explain where we are.
Would be great to know how the awareness of the context between a project's chats has changed and how it's managed? Now some chats with old details that have changed in later chats didn't become a problem that I'd have to address. Impressive.
On the coding side especially with the complex code base and interactions that I'm working on, for the first time I had the same experience as with the chat side of Opus actually remembering the small details and priorities we've set and actually serving me with choises that are really toward the goals we've set and it pulled from the code base stuff that I've previously had to hash out every time to get to a proper plan.
Unfortunately the update nuked my terminal chats from the past 7 months but I got over it fast because when I continued the work with Opus 4.7 and had to start hashing out some stuff that were ready to implement in serveral different chats before the nuke, we actually got those done in one go without any spoon feeding and hand holding.
How have people felt about this change and am I imagining this? 😂👍
Ps. I had to change the effort level to max and token limit to 200k in terminal CLI. The json got cleared on the update so the thinking got a downgrade and at first I was disappointed
It’s a powerhouse for design. Been using it since the launch. But it consumes mad tokens
I’ve been using Claude pretty regularly for coding and problem solving, and one thing I’ve really appreciated is how well it handles longer, more complex tasks compared to most tools.
There have been quite a few times where I didn’t have to keep re-explaining context, which made a big difference when working through multi-step problems. Curious how much further 4.7 pushes this, especially around maintaining context and reasoning across longer workflows. Excited to try it out.
to quote@leerob: "I really like this model for general agentic work outside coding. It is definitely expensive though."
a product like @Edgee might be a great combo in this context imho
I tried a quick brainstorm on some strategic direction, but didn't really like the response. It was not challenging me, even with explicit instructions to do so. Curious to what others are experiencing. Could it be that this model is even more tailored to e.g., coding than Opus 4.6?
Going to start today 4.7, I have been using Opus 4.6 and have been very happy with its output and performance!
BIG STEP UP, have used it so far!! Watch out though!! Will eat your tokens LOL
The jump from Opus 4 to 4.7 in agentic coding is massive. I've been using Claude Code daily and the difference in how it handles multi-file refactors and complex debugging chains is night and day. The extended thinking really shines when you give it architectural decisions to reason through.
I‘m super excited to test it out! Do you know what the date of knowledge database is? Especially if MacOS / iOS 26 Liquid Glass code is natively supported? With 4.6 I always had to use several mcps to get the right look of my implementations…
Thx!
the verification step is interesting. most models just output and hope for the best. how does Opus 4.7 actually verify its own code outputs - static analysis, test generation, or something else?
The session memory improvement is the feature I've been waiting for. Working on a large codebase with Claude Code, the biggest pain was re-explaining architectural decisions every new session. If Opus 4.7 actually retains context across multi-session projects, that alone justifies the upgrade. Curious how the new tokenizer affects costs in practice — 1.35x more tokens on the same input is worth watching.
First impression was very, very positive! As I was preparing for my launch yesterday, it pretty much saved the day! It caught errors that 4.6 was ignoring for long time, helped me design some really valuable scripts and designed some really cool graphics & flows for me.
Maybe I'm just hyped and excited, but I felt like I couldn't do it without this. Came exactly on the right time!
About Claude Opus 4.7 on Product Hunt
“Claude’s most capable model for reasoning and agentic coding”
Claude Opus 4.7 launched on Product Hunt on April 17th, 2026 and earned 493 upvotes and 22 comments, earning #1 Product of the Day. Claude Opus 4.7 is Anthropic’s most advanced generally available AI model, built for complex reasoning and agentic coding. It handles long-running tasks, follows instructions precisely, verifies outputs, and delivers high-quality results across coding, research, and workflows.
Claude Opus 4.7 was featured in API (98.1k followers), Artificial Intelligence (467.7k followers) and Development (5.9k followers) on Product Hunt. Together, these topics include over 104k products, making this a competitive space to launch in.
Who hunted Claude Opus 4.7?
Claude Opus 4.7 was hunted by Rohan Chaubey. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Claude Opus 4.7 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Claude Opus 4.7 looks like a serious leap forward for AI-powered development and knowledge work. It tackles a key problem: handling complex, long-running tasks that previously required constant human supervision.
With stronger instruction-following, better multimodal vision, and improved reasoning consistency, it enables users to confidently delegate harder workflows.
Why it stands out:
Verifies its own outputs for higher reliability
Maintains coherence across long, multi-step tasks
Improved high-resolution image understanding
Better memory across sessions for ongoing work
Key features:
Advanced coding + agentic task handling
`/ultrareview` for deep code reviews
Effort control (high → xhigh) for better reasoning vs latency tradeoff
Available across API, Claude apps, and major cloud platforms
Who it’s for & use cases:
Developers building AI agents and automations
Analysts working on finance, research, and modeling
Teams handling complex docs, workflows, and long-running tasks
If you’re building AI agents or scaling complex workflows, this feels like a meaningful upgrade.
P.S. I hunt the latest and greatest launches in tech, SaaS and AI, follow to be notified → @rohanrecommends