Now that all the providers have moved towards in-housing their coding solutions, the sweetheart deals are gone. And the wrapper goes back to "at cost" usage. Which, on paper should be less value / $ than any of the tiers offered by the providers themselves.
Whatever data they collected, and whatever investments they made in core tech remains to be seen. And it's a question of making use of that data. We can see that it is highly valuable for providers (as they all subsidise usage to an extent). Goog is offering lots of stuff for free, presumably to collect data.
One interesting distinction is on cursor vs. windsurf. Windsurf actually developed some internal models (either pre-trained or post-trained I don't know, but probably doesn't matter much) swe1 and swe1-lite that are actually pretty good on their own. I don't think cursor has done that, beyond their tab-next-prediction model. A clue, perhaps.
Anyway, it will be interesting to see how this all unfolds 2-5 years from now.
Early on Cursor added value by finding clever to integrate LLM into an IDE, which would allow single shot output of an LLM to produce something useful, and do so quickly. That required a fair bit of engineering to make happen reliably.
But LLM agents completely break that. The moment people realised that rather than trying to bend our tools to work within the limits of an LLM, we could instead just make LLM “self-prompt” their way to better outputs, Cursors model stopped being viable.
It’s another classic case of the AI “Bitter Lesson”[0] being learned. Throwing more data, and more compute at AI produces faster, better progress, than careful methodical engineering.
[0] http://www.incompleteideas.net/IncIdeas/BitterLesson.html
$20 on API pricing is what Claude Pro will give you in a day. It doesn't matter how good cursor is, this is a massive limitation and price differential that they can't overcome. Even if they go with DeepSeek which is much cheaper, they are still significantly more expensive than a Claude subscription.
This all becomes very clear when you do something that feels like magic in Claude Code and then run /cost and see you’ve blown through $10 in a single hour long session. Which is honestly worth it for me.
Not because of Cursor‘s pricing, but because in the end Claude Code is unmatched.
For example they can react to in editor linter errors without running a lint command etc.
'We previously described ... as "rate limits", which wasn't an intuitive way to describe the limit. It is a usage credit pool'
Cursor just makes that window one month long.
Technically, that's a rate limit.
But yeah, only technically.
From the site : “Supermaven uses Babble, a proprietary language model specifically optimized for inline code completion. Our in-house models and serving infrastructure allow us to provide the fastest completions and the longest context window of any copilot.”
For $200/month you can get equivalent value to a team of engineers. Plan accordingly! The stack is no longer safe for employment. You need to move up to manager or move down to metal.
Why couldn't Claude do a managers job?
I see people mention converting old legacy code from an old language to something more modern. I've also seen people mention greenfield projects.
Anything other than this? I'm trying to bring this productivity to my work but so far haven't been able to replace a week of work in a few minutes yet
I also saw that it was 0.8x the ‘credit cost’ thinking still that I had 500.
Now to learn that the 500 has gone and you get unlimited only on auto shows how easy it has been to misunderstand what they’re trying to say.
Also, I’ve no idea how to find out the cost of MAX. Especially as their web agent has the text MAX next to the selected non-max model.
This news coupled with google raising the new gemini flash cost by 5x, azure dropping their startup credits, and 2-3 others(papers showing RL has also hit a wall for distilling or improving models), are now solid signals that despite what Sam altman says, intelligence will NOT be soon too cheap to meter. I think we are starting to see the squeeze from the big players. Interesting. I wonder how many startups are betting on models becoming 5-10x cheaper for their business models. If on device models don't get good, I bet a lot of them are in big trouble
[1] https://www.investing.com/news/economy-news/anysphere-hires-...
Nvidia sold $35B of just datacenter GPUs last year. Of which the vast majority will be used for AI.
Cerebra entire revenue last year was only $78M. That’s three orders of magnitude smaller than Nvidia datacenter GPU business. Scaling a company 10X in a year is a pretty hard thing to do, and it’s not a question of money, it’s a question of people and organisation. So much stuff in a business breaks when it scales 10X, that it take months to years to fix enough stuff to support another 10x growth spurt without everything just imploding.
any reference for this?
I’m not convinced that these price increases represent an attempt to squeeze more profit out of a saturated market.
To me they look an awful lot like people realising that the sheer compute cost associated with modern models makes the historical zero-marginal cost model of software impossible. API calls to LLM models have far more in common with making calls to EC2 or Lambda for compute, than they do a standard API calls for SaSS.
A lot of early LLM based business models seemed to assume that the historical near zero-marginal cost of delivery for software would somehow apply to hosted LLM models which clearly isn’t the case.
You mix that in with rising datacenter costs, driven by lack of available electricity infrastructure to meet their demands, plus everyone trying to grab as much LLM land as possible, which requires more datacenters, more faster. And the result is rapidly increasing base costs for compute. Which we’re now seeing reflected in LLM pricing.
For me the thing that stands out about LLMs, is that their compute costs are easily 100-10000x greater per API call than a traditional SaSS API call. That fact alone should be enough for people to realise that the historically bottomless VC money that normal funds this stuff, isn’t quite a bottomless as it needs to be to meaningfully subsidise consumer pricing.
LLM are still to new, and still advancing to quickly for optimisation to take place. It’s like we’re back in the MHz wars of old between CPU manufacturers. The goal is just more performance, regardless of cost, because it was clear that even in the consumer space, people wanted more performance.
Then we hit a kind of plateau in last 10 years, where basic compute is so powerful that your average consumer is not longer upgrading every year for better performance. A 5 year old machine has enough performance for most people. Then the focus on energy efficiency kicked in, because people didn’t want faster computers, they wanted battery life and cheaper computers.
No doubt we’ll see the same with LLM, possibly quite soon. Claude Sonnet 4 and similar class models have enough reasoning performance, that agentic systems can be quite reliable. Which means we hit the base level of “reasoning” performance needed, and we can extend that “performance” in domain specific ways by lightly customising the agentic framework, with no need to fine tuning. The elimination of fine tuning to build domain specific agents is a huge game changer. But it also means that putting together a 10x or 100x efficient model, with “reasoning” performance equivalent to current gen LLM would also be a huge game changer. It opens up the possibility to apply this tech into spaces that currently require either lots of specialists knowledge to fine tune an LLM, or a huge amount of on tap compute to allow the agents to take enough turns to slowly “reason” they’re way through problems.
But a Claude Sonnet 4 that runs on a iPhone for example. That would make Apple’s complete failure to improve Siri look like a genius level move. Why bother with small incremental improvements using current tech, when waiting a few years, and just stuffing a full fat LLM and agent system into an iPhone will basically give you the ultimate Siri.
Cursor deserve the criticism, but its been pretty obvious since they introduced the new Ultra plan that we were going to see classic enshittification on the formerly premium options. Very frustrating for long term supporters especially.
Note that although this update apologises for the miscommunication (which looks more like deliberate obfuscation), the only option for getting what we paid for (I'm on the annual plan) is the menu setting above, which should be default on!
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