Yes, this is already accounted for in many benchmarks, but without deep context of the problem type, the top line pricing is the best starting point.
In my own experience, Fable is more token efficient than opus 4.8 with a higher likelihood of completing tasks correctly or at least with minimal corrective work. Opus regularly struggled to gather the correct context and reason effectively about what it had gathered.
GPT-5.6-sol crushes fable in speed and token efficiency and is clearly superior across many tasks that matter for me.
I also find all models from anthropic after opus 4.6 to suffer from the same ai slop language that long plagued OpenAI and seems to have been reduced drastically in 5.6
Non-competes in finance almost always come with compensation during the defined period.
The idea that a company can restrict at-will employee’s post-separation employment is absurd if they aren’t compensating the individual.
In many US states and countries outside the US, the enforcement of non-competes is very very hard. The problem is that they create a RISK of enforcement.
I gave fable 5 a task for which opus has been really really underperforming. Fable 5 took far less time and produced actually useful analysis. Instead of just regurgitating roughly what the code already does or misunderstanding entirely, it identified multiple routes to improve. Now, the code it is analyzing is not very good as it was mostly produced by opus.
Opus had consistently ignored my instructions and looped on broken logic over the last several weeks.
I’ll be sad when this model is removed from Claude code because I won’t be paying api pricing to work on open source projects.
As with anything, it depends on the quality and skills of the people doing the designing. I have yet to really work with a designer that embedded themselves enough in the UX to design anything I thought was good.
Granted, I have not worked with that many designers so it’s maybe small N problem.
The gap between figma and where our front end teams work and design is still too large.
I think the more likely result of this is fewer designers and more work for developers with some design skills.
I used Claude code to build a custom notes application for my specific requirements.
It’s not perfect, but I barely invested 10 hours in it and it does almost everything I could have asked for, plus some really cool stuff that mostly just works after one iteration. I’ll probably open source the code at some point, and I fully expect the project to have less than two stars.
Still, I have my application.
For anyone that’s interested in taking a look, my terrible landing page is at rayvroberts.com
Auto updates don’t work quite right just yet. You have to manually close the app after the update downloads, because it is still sandboxed from when I planned to distribute via the Mac App Store. Rejected in review because users bring their own Claude key.
Did you read the article? Author is talking about humans relying on chatbots to formulate all their responses for them without strict direction and refinement.
I'm sorry, but the music on the demo video is the most atrocious nonsense. I know it's crazy, but it makes me hate the app. openAI is falling off hard.
I’ve wanted a good markdown editor with automatic synchronization. I used to used inkdrop. Which I stopped using when the developer/owner raised the price to $120/year.
In a couple hours with Claude code, I built a replacement that does everything I want, exactly the way I want. Plus, it integrates native AI chat to create/manage/refine notes and ideas, and it plugs into a knowledge RAG system that I also built using Claude code.
What more could I ask for? This is a tool I wanted for a long time but never wanted to spend the dozens of hours dealing with the various pieces of tech I simply don’t care about long-term.
Why should anthropic open source Claude Code CLI? I understand you and some others want it, maybe it would be better for the community, but is it what’s best for anthropic?
Why should subscribers get your specific discount rather than what anthropic has calculated the discount should be?
I'm not arguing that human brains are magic. the current AI models will probably teach us more about what we didn't know about intelligence than anything else.
Are you a stream of words or are your words the “simplistic” projection of your abstract thoughts? I don’t at all discount the importance of language in so many things, but the question that matters is whether statistical models of language can ever “learn” abstract thought, or become part of a system which uses them as a tool.
My personal assessment is that LLMs can do neither.
In my own experience, Fable is more token efficient than opus 4.8 with a higher likelihood of completing tasks correctly or at least with minimal corrective work. Opus regularly struggled to gather the correct context and reason effectively about what it had gathered.
GPT-5.6-sol crushes fable in speed and token efficiency and is clearly superior across many tasks that matter for me.
I also find all models from anthropic after opus 4.6 to suffer from the same ai slop language that long plagued OpenAI and seems to have been reduced drastically in 5.6