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> ..you’ve run into a problem that you’ve spent days trying to get Opus to solve

do you have an example of this? If i can't get an agent to do something in a couple hours i do it myself.

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Many, but I think that the model delta is only meaningfully convincing when experienced firsthand.

Here’s an example of improvement when trying to solve the label placement problem (NP-hard):

https://imgur.com/a/kCUZxPi

It’s also an example of something that I could not (and would not bother trying to) code up a solution / heuristic for.

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I had a 300k LOC game that needed refactored and segmented into DAG assemblies for a composable engine to reuse in a few other similar games our studio is prepping to build.

I tried holding Opus's hand over a week trying to get it done with a ton of in-depth planning and manual course-correction, but it never got it to a state where it was "done" (kept struggling to differentiate between game content specific to that game versus game systems we'd want to reuse, and how to cleanly separate systems vs content when extracting).

Fable needed a little bit of hand holding but got it done in less than a day.

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Not the OP, but I had Fable orchestrate this project.

https://github.com/ByteTerrace/Puck

It has required constant hand holding, and there was the outage to deal with, but I can't argue with the end results. A fully deterministic recursive engine within an engine framework that includes a rendering VM, emulators, custom ROMs, and an in-game editor? Insane. Sure, it's nowhere near primetime but this kind of thing was unimaginable just a year ago.

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Build a distributed system using raft groups. You will see Opus fail.
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Funny how the two top comments are contradictory. We need better than anecdotes to understand what the new models bring.
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Since Fable, my legit infrastructure project has turned into the sort of thing I can do 95% on my phone. It’s reliable enough instead of doing big reviews, I’ve just been giving it smaller tasks, and dozens in parallel.

I created a skill that’s focused on getting PRs merge-ready, and now my attention is fully back where it should be, on deciding what changes will make the product better.

Our entire stack is Apache 2.0 open source, including the agent docs, so if you wanna try sitting at a higher level of abstraction, install the skill in your repo or just clone our whole project and start adding features: https://good.vibes.diy/blog/beast-mode-skill-for-claude-code

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This reads like a paid testimonial.
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If by that you mean I paid a lot to learn this. But at least I typed it with my own two hands.
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I am glad! But you are indeed selling your own product here, correct?
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The website linked is an utter mess. In design and performance.
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I didn’t mention my case since it’s quite esoteric, but I am working on an application using the Apple RoomPlan API, which is very powerful but very limited in customizability. Opus simply couldn’t alter the scanning view for me, it would try things over and over and eventually started making up parameters and passing them hoping it would work.

Completely failed, but I knew it was possible because a competitor app does it.

Fable also failed, then added log lines (as did Opus, but Opus failed to do anything useful with them) and then reversed engineered the API, and made it work.

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Here’s one difference I have seen. I forgot I had a multi-session audio probe running while trying to repro audio glitches, and Fable came back with: “your pops are already on tape.”

Interesting choice of words. Phrased so casually. It picked a low-tech idiom that fit the situation instead of giving some sterile technical answer. That kind of language and context awareness never happened for me with Opus, or gpt 5.5.

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you're living in the age of AI; not AGI. Also, there's pretty much zero moderation on HN, so astroturfing is likely streaming through just as bad as reddit. It' sjust noit as obvious because it's a smaller scoped website.
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This is like when a vacuum doesn’t pick something up after a few tries. The user picks the thing up, looks at it, then puts it back down and tries again until they finally give up and move it to the trash.

If you can’t design a solution and instead waste days and who knows how much money in tokens instead of just turning on your brain for a few minutes, you are in the wrong profession.

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My experience comparing GPT-5.5 and Fable:

GPT-5.5 is better for:

- Strategic thinking

- Long-form writing, including essays and white papers

- Image creation

- Code generation

Fable is better for:

- Using tools

- Testing code

- Working in live environments

- Making changes to existing software

- Creating polished PowerPoint and Word documents

Fable’s tool access is its biggest advantage. It's hard to describe but Fable ability to access sandbox environments with way more tooling can quickly become a superpower in now workflows.

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We’ve really evolved quickly into simple vectors for a magical tool that solves our problems. Can’t solve the problem? There’ll be a new release soon that can!
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