I do have this experience. I've used Claude Code (with Opus mostly), and then switched to opencode (mostly with Kimi 2.6) for my personal projects; it's based on a couple months of use.
Claude Code is better. But Opencode + kimi 2.6 is workable, which is big. For bare code writing, if you know what exactly you want, most popular models are fine (deepseek, kimi, etc), it feels more or less the same as anthropic models.
At the same time, Opus seems to understand my intent way better than e.g. deepseek. I need to be much more precise with my prompts when using deepseek - it often goes in a wrong direction if I'm lazy. This results in a workflow which feels quite a lot different from Claude Code.
Kimi is in between - for me it brings back "lazy prompting" workflow, and I can trust its plans more than deepseek. It enables a workflow similar to Claude Code, it's workable, but it is a bit worse everywhere. Smaller context, a bit more errors, decisions are a bit worse, recommendations are a bit worse, debugging capabilities are a bit worse, etc.
On the usage side, $100 Claude plan is a great value actually. On paper, per-token kimi is way cheaper, but Claude subscriptions are heavily subsidized - you get much more tokens than $100 can buy you. So, in the end, opencode + kimi vs claude code could be of a similar cost, for similar usage patterns. Deepseek can be cheaper, and it has insanely cheap cached tokens, but experience may vary - depending on your habits, you may need to adjust how you work, coming from claude code.
I'd say for side projects something like $10 Opencode Go plan + $10 of extra DeepSeek v4 credits (e.g. on OpenRouter) can be very workable.
I wonder if they’re truly subsidised or if the API pricing is just massively inflated. Genuine doubt.
My CC stats show me using almost 300$ of Sonnet tokens on the 20$ plan. Is Anthropic willing to forgo 93% of the profit? A bit less than that but API is priced, say, 3x what it should be?
CC is great, but Sonnet (my main model) isn’t worth the API pricing. The cheap-but-good models arrive at similar results for much less (for context I’m using Aivo with CC).
Anthropic is making money from people who under-utilize their subscriptions, and presumably by sneaky throttling or not-sneaky throttling power users. Currently they are in an adoption race. Whether being first will actually let them "win" the market (and the market is a bit ill-defined) is unclear.
To my feeling, I'm getting usage of Opus (and Fable before the cut) that's greater than what I got from Sonnet last year. I reached $100 of usage when weekly was at 50%. This means, I could squeeze $800 worth of tokens for $20.
Anthropic has sent out a newsletter explaining they were more or less adding 50% (even 100%?) of quota to everyone, due to some great deal they made. That might be it. I do get lots more usage lately.
This is generally been my experience as well, but i think the main reason for claude code being better at understanding intent is their massive system prompt.
>At the same time, Opus seems to understand my intent way better than e.g. deepseek. I need to be much more precise with my prompts when using deepseek - it often goes in a wrong direction if I'm lazy. This results in a workflow which feels quite a lot different from Claude Code.
how much of that is Opus injecting prior conversations from memory?
Almost none of it, if you're using Claude Code. Until recently Claude only had the option of retaining memory across conversations for the desktop app.
I almost never use the desktop app, I have maybe 2-3 conversations over the last year that have nothing to do with my job. Opus (and now Fable) genuinely do seem to "understand" what you intend based off what you're explaining a lot better than other models I've tried.
Gemini gets close in some cases, but it falls over in the actual implementation sometimes. I haven't tried Kimi yet but MiMo isn't too shabby either.
I'm using Claude code + (a patched) litellm proxy + openrouter + Qwen 3.7 max/kimi k2.6/deepseek v4 pro. The only feature that doesn't work is webfetch and web search, which I've replaced with the ddg MCP. Memory, caching, and everything else works fine.
Qwen comes close to opus for planning but fable is clearly superior. Kimi and deepseek are pretty much indistinguishable from opus for coding if opus writes the plan.
I'm now testing out fable for research and planning and deepseek v4 flash for coding. I'm guessing results will be pretty similar to opus + deepseek v4 pro and costs should be lower overall.
* plugin for Logic Pro to A/B mix with reference tracks, with ai-based stem splitter (e.g. isolate vocals in ref track, and compare with your vocal track)
* plugin for Logic Pro to simulate how a mix will sound on my macbook and phone (I captured real impulse responses for that, sounds very close)
* an app for spaced repetition for guitar video lessons / their parts (no idea why platforms like truefire don’t have this feature)
* workout planning/tracking app
* an app to create impulse responses for acoustic guitar, to make it sound good live
It feels insincere and manipulative, especially when I don't know upfront if the content (music, video, text) is from another human being or from AI.
AI will become good enough to write songs better than humans; it's a matter of time. But it feels like someone tries to hack my mind, exploit my human instincts, it doesn't feel like genuine art the way it was for the whole human history - people expressing themselves, creating and sharing something beautiful with each other.
The end result is an automated personalized "enjoy" button, and this is sad.
> AI will become good enough to write songs better than humans; it's a matter of time.
I'm unconvinced. The process of songwriting is so dependent on being able to listen to what you've made and decide whether you enjoy it or not. We can train a model to imitate popular music, but we can't train a model to enjoy music, because we can't quantify enjoyment and turn it into a data set. You can train an LLM on soup recipes, but you can't train one to taste the soup and tell you whether it's good or not.
That's part of what offends me so much about the notion of AI-assisted "creativity." Creating music should be a way of engaging more deeply with music, but you've discovered a way to pay even less attention to music than before. None of the details in an AI-generated song really matter; they were chosen arbitrarily, because they seemed normal. Indeed, they are so normal that your ear will slide right off of them.
You can't fix a soup that someone else prepared—not as an amateur. You don't know what went into it, so you can't pick out the individual flavours and decide whether they're right or not. They were never "right" for you, because you didn't pick them. It's like ordering a Big Mac, taking it apart, and trying to workshop it into Duck à l'Orange. All you get is a Big Mac with some orange slices on it. Maybe you like Big Macs; maybe you're happy. It's a pretty poor substitute for creativity, though.
> But it feels like someone tries to hack my mind, exploit my human instincts, it doesn't feel like genuine art the way it was for the whole human history - people expressing themselves, creating and sharing something beautiful with each other.
There's a thin line between art and business - quite often the goal isn't to have you feel something, it's to sell you product that you pay for, and if by the way you feel something, that's cool.
To compute accuracy, you compare the moves which are made during the game with the best moves suggested by the engine. So, the engine will evaluate itself 100%, given its settings are the same during game and during evaluation.
You get 99.9something% when you evaluate one strong engine by using another strong engine (they're mostly aligned, but may disagree in small details), or when the engine configuration during the evaluation is different from the configuration used in a game (e.g. engine is given more time to think).
I think he/she is reacting mostly to this quote from the article, not to the main article topic:
> I have a good answer: my job is to double our value-add capacity over the next three years. Essentially, to double our output without increasing spending.
> You know what? With my XP plans and the XP coaches I’ve hired, it’s totally doable. I think I’m being kind of conservative, actually.
The URL parsing in httpx is rfc3986, which is not the same as WHATWG URL living standard.
rfc3986 may reject URLs which browsers accept, or it can handle them in a different way. WHATWG URL living standard tries to put on paper the real browser behavior, so it's a much better standard if you need to parse URLs extracted from real-world web pages.
We need a better URL parser in Scrapy, for similar reasons. Speed and WHATWG standard compliance (i.e. do the same as web browsers) are the main things.
It's possible to get closer to WHATWG behavior by using urllib and some hacks. This is what https://github.com/scrapy/w3lib does, which Scrapy currently uses. But it's still not quite compliant.
Also, surprisingly, on some crawls URL parsing can take CPU amounts similar to HTML parsing.
can_ada dev here. Scrapy is a fantastic project, we used it extensively at 360pi (now Numerator), making trillions of requests. Let me know if I can help :)
Exit Through the Gift Shop - an amusing documentary about somebody trying to find Banksy (a street artist), and much more, supposingly directed by Banksy himself.
There is some debate if it is documentary or not (the story is almost too good), but it seems the evidence suggests it is real.
EDIT: sorry, I missed the "last 4 years" part in the question. This film is older than that.
Definitely this, my subconscious can't let go of the question as to whether this documentary is an exquisitely elaborate hoax or a rare capture of a "truth is stranger than fiction".
And if the goal was to create that confusion... meta-wow.
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