- OpenAI is buying WindSurf and probably did diligence on these models before it decided to invest.
- WindSurf may have collected valuable data from it users that is helpful in training a coding-focused AI model. The data would give a 6 month lead to OpenAI which is probably worth the $3B.
- Even if Windsurf's frontier models are not better than other models for coding, if they excel in a few key areas it would justify significant investment in their methodology (see points above).
- There are still areas of coding where even the top frontier models falter that would seemingly be ripe for improvement via more careful training. Notably, making the model better at working within a particular framework and version, programming language version, etc. Also better support for more obscure languages and libraries/versions and the ability to "lock in" on the versions that the developer is using. I've wasted a lot of time trying to convince OpenAI models to use OpenAI's latest Python API -- even when given docs and explicit constraints to use the new API, OpenAI frontier models routinely (incorrectly) update my code to use old API conventions and even methods that have been removed!
Consider that the basic competency of doing a frontier coding model well is likely one of the biggest opportunities in AI right now (second to reasoning and in my opinion tied with image analysis and production). An LLM that can both reason and code accurately could read a chapter in a textbook and code a 3D animation illustrating all of the concepts as a one-shot exercise. We are far from that at present even in OpenAI's best stuff.
Thanks - this does help contextualize the $3B acquisition. When the story first broke all they seemed to be paying for was a coding agent (of which there are sooo many out there) and the large windsurf user base (but with no moat). So a lot of us were rather skeptical. The valuation is still kinda insane, I think, but Windsurf’s ability to train a frontier model - and with a much smaller team than the big AI shops - is the key differentiator from the Clines, Cursors, Aiders etc.
It is a bit of a shame that we’ll never get to see what they could do on their own. But I hope their clearly very talented employees do very well out of this.
this is clearly the right take… it’s fun to semi-dunk on “how on earth is that the valuation”, but this is one of those rare cases where the tech and platform are genuinely more valuable in the hands of the acquirer than they ever could be in the hands of the acquiree. because i think windsurf has executed as well as one possibly could in the space, but openai is the SOTA model king, and i don’t see that changing anytime soon.
So because they need to have a better business model, they will try to move users to weaker models compared to the best available? This "AI inside the editor" thing makes every day less sense in many dimensions: it makes you not really capable of escaping the accept, accept, accept trap. It makes the design interaction with the LLM too much about code and too little about the design itself. And you can't do what many of us do: have that three subscriptions for the top LLMs available (it's 60$ for 3, after all) and use each for it's best. And by default write your stuff without help if LLMs are not needed in a given moment.
You’ve got a couple of ideas colliding here, let me try to unpack them.
First, most of the major players already have their own models or have been developing them for some time. Your take feels a bit reductive. Take Windsurf pre-acquisition, for example, their risk was being too tightly coupled to third-party vendors. It’s only logical to assume that building task- or language-specific models will ultimately help reduce costs and offer more control.
As for the other point: in my experience, trying to fully leverage LLMs actually makes me more prescriptive in my designs. I spend more time thinking through architecture and making my code modular, more so than when I wasn’t using an LLM. I’m sure others may design less or take shortcuts, but for me it’s pushed the opposite behavior. Is it the “right” way? I’m not sure, but I’m enjoying it and staying productive.
I don't think they are targeting software engineers as users. They are seeking those on the software engineering margins, users who know what Python and for-loops are but don't care to configure Aider and review each of the overwhelming number of models released daily. They want to tell the editor to add function foo to bar.py. I suspect this latter market segment is much larger than the former!
I don't like or agree with this take. You're basically saying - "something good exists, so why try to improve upon it".
Their stated goal is to improve on the frontier models. It's ambitious, but on the other hand they were a model company before they were an IDE company (IIRC) and they have a lot of data, and the scope is to make a model which is specialized for their specific case.
At the very least I would expect they would succeed in specializing a fronteir model for their use-case by feeding their pipeline of data (whether they should have that data to begin with is another question).
The blog post doesn't say much about the model itself, but there's a few candidates to fine tune from.
> they will try to move users to weaker models compared to the best available
> you can't do what many of us do: have three subscriptions and use each for its best
I don't think has anything to do with whether or not AI is in the editor so much as it is the difference between a subscription (Cursor) vs. a BYOK approach (VS Codium + Cline, Zed, etc). Most BYOK plug-ins will let you set up multiple profiles against various providers so that you can choose the most optimal LLM for the given problem you're trying to solve.
i think this comment is just a reflection of how the world has not caught up with the inevitable shift of “software engineering” up further into “idea space”. i completely agree that the tooling has not caught up with this new world order yet. personally, i think “true software engineering” is more valuable than ever in the AI era, but the tools for actually realizing this are woefully behind.
I'm confused why they are working on their own frontier models if they are going to be bought by OpenAI anyway. I guess this is something they were working on before the announcement?
It seems OpenAI acquired Windsurf but is letting it operate independently, keeping its own brand and developing its own coding models. That way, if Windsurf runs into technical problems, the backlash lands on Windsurf—not OpenAI. It’s a smart way to innovate while keeping the main brand safe.
Why would OpenAI not let smart people work on models? That seems to be what they do. The point is: They are no longer "their own" models. They are now OpenAI models. If they suck, if they are redundant, if there is no idea there that makes sense, that effort will not continue indefinitely.
They were working on the model before the acquisition. It makes sense to test it and see how it does instead of throwing the work away. Their data will probably be used to improve gpt-4.1, o4 mini high, and other OpenAI coding models
openAI models have an issue where they are pretty good at everything but not incredible at anything. They're too well rounded.
for coding you use anthropic or google models, I haven't found anyone who swears by openAI models for coding... Their reasoning models are either too expensive or hallucinate massively to the point of being useless... I would assume the gpt 4.1 family will be popular for SWE's
Having a smaller scope model (agentic coding only) allows for much cheaper inference and windsurf building its own moat (so far agentic IDE's haven't had a moat)
Getting more money perhaps also, if they believed their model to be good, and had amassed some good training data Open AI can leverage, apart from the user base.
> Enabled from the insight from our heavily-used Windsurf Editor, we got to work building a completely new data model (the shared timeline) and a training recipe that encapsulates incomplete states, long-running tasks, and multiple surfaces.
This data is very valuable if you're trying to create fully automated SWEs, while most foundation model providers have probably been scraping together second hand data to simulate long horizon engineering work. Cursor probably has way more of this data, and I wonder how Microsoft's own Copilot is doing (and how they share this data with the foundation model providers)...
There is a world where the wrapper makers surpass the current model makers in their area of focus. Cursor/Windsurf have all the data on when people got so frustrated with Claude they switched to Gemini/GPT and also all the data of when the problem was actually solved and when it wasn't.
The company that is best placed to collect tons of high quality data of this type is undoubtedly Google. They’ve had publications talking about how they capture data from their in house SWE tools and use it to improve their tooling.
Cynical take: describing yourself as a full stack AI IDE company sounds very invest-able in a "what if they're right" kind of way. They could plausibly ask for higher valuations, etc.
Optimistic take: fine tuning a model for their use-case (incomplete code snippets with a very specific data model of context) should work. Or even has from their claims. It certainly sounds plausible that fine-tuning a frontier model would make it better for their needs. Whether it's reasonable to go beyond fine-tuning and consider pre-training etc. I don't know. If I remember correctly they were a model company before Windsurf, so they have the skillset.
Bonus take: doesn't this mean they're basically training on large-scale gathered user data?
it was only a matter of time, they have too much good data to not train their own models, not to mention that claude API calls were probably killing their profitability.
It's a shame that my development work needs a specific VSCode extension (domain specific language for ERP systems) so my options are VSCode+Copilot or Cursor.
My favorite tools are cline and roo. My experience says cline eats tokens like crazy and roo eats less. I don’t try Aider since I do like to watch the mesmerizing diffs (fire verification) :)
Aider runs in your terminal and you can make comments against your code in any editor and it will execute your requests. It can use any model. CLine, mentioned in sibling comment is is same space.
you can use the codeium extension I believe no? Also I think that if the license of the extension that you are using permits it you could export that extension to the open source store
Sorry, but as a paid Windsurf user, I think Windsurf should stop chasing shiny frontier models and focus on building better predictable & manageable workflows to build real-life products.
- How about providing a Jira/Trello-style dashboard with subtasks for our AI, instead of copy-pasting "Cline Memory Bank" to .windsurfrules?
- How about supporting TDD and regression-fixing by default?
- How about using git with branches instead of the current undo-redo system?
- How about a better way of syncing documentation vs real code?
We are paying for more "manageable" AI agents to get stuff done, not a chaotic "genius-hacker" to hack together quick prototypes.
resters|9 months ago
- OpenAI is buying WindSurf and probably did diligence on these models before it decided to invest.
- WindSurf may have collected valuable data from it users that is helpful in training a coding-focused AI model. The data would give a 6 month lead to OpenAI which is probably worth the $3B.
- Even if Windsurf's frontier models are not better than other models for coding, if they excel in a few key areas it would justify significant investment in their methodology (see points above).
- There are still areas of coding where even the top frontier models falter that would seemingly be ripe for improvement via more careful training. Notably, making the model better at working within a particular framework and version, programming language version, etc. Also better support for more obscure languages and libraries/versions and the ability to "lock in" on the versions that the developer is using. I've wasted a lot of time trying to convince OpenAI models to use OpenAI's latest Python API -- even when given docs and explicit constraints to use the new API, OpenAI frontier models routinely (incorrectly) update my code to use old API conventions and even methods that have been removed!
Consider that the basic competency of doing a frontier coding model well is likely one of the biggest opportunities in AI right now (second to reasoning and in my opinion tied with image analysis and production). An LLM that can both reason and code accurately could read a chapter in a textbook and code a 3D animation illustrating all of the concepts as a one-shot exercise. We are far from that at present even in OpenAI's best stuff.
libraryofbabel|9 months ago
It is a bit of a shame that we’ll never get to see what they could do on their own. But I hope their clearly very talented employees do very well out of this.
keeganpoppen|9 months ago
antirez|9 months ago
infecto|9 months ago
First, most of the major players already have their own models or have been developing them for some time. Your take feels a bit reductive. Take Windsurf pre-acquisition, for example, their risk was being too tightly coupled to third-party vendors. It’s only logical to assume that building task- or language-specific models will ultimately help reduce costs and offer more control.
As for the other point: in my experience, trying to fully leverage LLMs actually makes me more prescriptive in my designs. I spend more time thinking through architecture and making my code modular, more so than when I wasn’t using an LLM. I’m sure others may design less or take shortcuts, but for me it’s pushed the opposite behavior. Is it the “right” way? I’m not sure, but I’m enjoying it and staying productive.
ipnon|9 months ago
bluelightning2k|9 months ago
Their stated goal is to improve on the frontier models. It's ambitious, but on the other hand they were a model company before they were an IDE company (IIRC) and they have a lot of data, and the scope is to make a model which is specialized for their specific case.
At the very least I would expect they would succeed in specializing a fronteir model for their use-case by feeding their pipeline of data (whether they should have that data to begin with is another question).
The blog post doesn't say much about the model itself, but there's a few candidates to fine tune from.
unknown|9 months ago
[deleted]
vunderba|9 months ago
> you can't do what many of us do: have three subscriptions and use each for its best
I don't think has anything to do with whether or not AI is in the editor so much as it is the difference between a subscription (Cursor) vs. a BYOK approach (VS Codium + Cline, Zed, etc). Most BYOK plug-ins will let you set up multiple profiles against various providers so that you can choose the most optimal LLM for the given problem you're trying to solve.
keeganpoppen|9 months ago
bhl|9 months ago
visarga|9 months ago
The definition of vibe coding - trust the process, let it make errors and recover
firejake308|9 months ago
allenleee|9 months ago
jstummbillig|9 months ago
seunosewa|9 months ago
kristopolous|9 months ago
dyl000|9 months ago
for coding you use anthropic or google models, I haven't found anyone who swears by openAI models for coding... Their reasoning models are either too expensive or hallucinate massively to the point of being useless... I would assume the gpt 4.1 family will be popular for SWE's
Having a smaller scope model (agentic coding only) allows for much cheaper inference and windsurf building its own moat (so far agentic IDE's haven't had a moat)
anshumankmr|9 months ago
blixt|9 months ago
This data is very valuable if you're trying to create fully automated SWEs, while most foundation model providers have probably been scraping together second hand data to simulate long horizon engineering work. Cursor probably has way more of this data, and I wonder how Microsoft's own Copilot is doing (and how they share this data with the foundation model providers)...
whywhywhywhy|9 months ago
lemming|9 months ago
figassis|9 months ago
bluelightning2k|9 months ago
Cynical take: describing yourself as a full stack AI IDE company sounds very invest-able in a "what if they're right" kind of way. They could plausibly ask for higher valuations, etc.
Optimistic take: fine tuning a model for their use-case (incomplete code snippets with a very specific data model of context) should work. Or even has from their claims. It certainly sounds plausible that fine-tuning a frontier model would make it better for their needs. Whether it's reasonable to go beyond fine-tuning and consider pre-training etc. I don't know. If I remember correctly they were a model company before Windsurf, so they have the skillset.
Bonus take: doesn't this mean they're basically training on large-scale gathered user data?
heymijo|9 months ago
I don’t know Varun (their founder/CEO) personally but I get highly competent vibes from him. I’d let my skeptical self lean on your optimistic take.
dyl000|9 months ago
open source alternative https://huggingface.co/SWE-bench/SWE-agent-LM-32B
though I haven't been able to find a mlx quant that wasn't completely broken.
aquir|9 months ago
DrBenCarson|9 months ago
bicepjai|9 months ago
aitchnyu|9 months ago
albertot|9 months ago
TiredOfLife|9 months ago
knes|9 months ago
tianshuo|9 months ago
We are paying for more "manageable" AI agents to get stuff done, not a chaotic "genius-hacker" to hack together quick prototypes.
infecto|9 months ago