21:32Mehul Mohan · Talking Head
China's New AI Beat Claude AND OpenAI! (WHAT)
GLM-5.2 is MIT-licensed, 1M context, trained without American silicon — and it trails Opus 4.8 by just 1% on the hardest coding benchmark.
June 17thThe argument in one line.
SpaceX acquiring Cursor completes a vertical AI stack — compute, model, and developer distribution — that lets XAI compete directly with OpenAI and Anthropic on their strongest turf: daily active developer workflows.
Read if. Skip if.
READ IF YOU ARE…
- You use Cursor or any AI-assisted IDE and want to understand how the acquisition changes the product trajectory.
- You are choosing between AI coding tools and wondering whether Cursor's model independence is gone.
- You follow the AI infrastructure space and want a practitioner's read on what Cursor actually brings to XAI beyond its user count.
SKIP IF…
- You want a technical deep-dive into Composer 2.5 training details — this is commentary, not a research paper.
- You are already tracking XAI/SpaceX news daily and have the full context.
The full version, fast.
SpaceX exercised an April option to buy Cursor at a $60B all-stock valuation, folding it into an entity that spans rockets, Colossus data centers, and the Grok model family. The deal isn't about user source code — which isn't trivially useful for training — but about Cursor's reinforcement learning environments, engineering talent, and millions of active developers as instant distribution. Composer 2.5 was already jointly trained with SpaceXAI using 1M H100 equivalents; a purpose-built foundation coding model is the plausible next step. The open multi-model era of Cursor may be narrowing, but the upside is models built specifically for coding rather than borrowed from OpenAI or Anthropic.
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00:00 – 00:44
01 · Hook: SpaceX acquires Cursor
SpaceX tweet announces all-stock acquisition. Context from April tweet showing the two options Cursor was given.
00:44 – 01:33
02 · SpaceX IPO context
SpaceX stock at $212 vs $1.35 IPO target; $3T valuation on $18-20B revenue; all-stock deal denominated in inflated currency.
01:33 – 02:56
03 · AI harness vs. AI models
Elon assembling best-of-field companies. Cursor's past independence (multi-model), its business model (enterprise + token margins), Composer series built on Kimi.
02:56 – 03:55
04 · XAI / SpaceXAI org map
XAI, SpaceXAI, x.com — one Elon empire with blurry org boundaries. SpaceXAI had already collaborated on Composer 2 and 2.5.
03:55 – 05:33
05 · Composer 2.5 and Grok V9
Jointly trained from scratch on Colossus 2 (1M H100 equiv). Pricing: $0.50/M input, $2.50/M output. Grok V9 Medium 1.5T params, evals look good.
05:33 – 07:51
06 · What Cursor actually brings
Not raw user source code — the RL training environments Cursor built for Composer are the real asset, along with talent and post-training expertise.
07:51 – 09:29
07 · Instant distribution play
XAI had near-zero developer mindshare for coding. Cursor acquisition is the Twitter playbook: buy at scale rather than build from zero.
09:29 – 10:56
08 · Windsurf/Devin comparison
Cognition rebranded Windsurf to Devin Desktop but still offers OpenAI/Claude/Gemini APIs. SWE 1.6 model exists but they are not in the foundational model race.
10:56 – 12:10
09 · Model landscape roundup
Kimi K2.7, SWE 1.6, Opus 4.7, GPT-5.5 as daily drivers; orchestrator/executor pattern for cost-conscious developers; Mistral meme.
12:10 – 12:51
10 · Wrap
Competition and velocity are good for developers. CTA: like, subscribe, comment.
Lines worth screenshotting.
- Cursor was given two options in April: acquisition for $60B or pay $10B for the compute partnership — acquisition was always the more likely outcome.
- SpaceX stock at $212 on a ~$1.35 IPO target means the all-stock deal is denominated in highly inflated currency — Cursor founders got rich on paper.
- A $3T valuation on $18-20B revenue is indefensible by traditional metrics; SpaceX is priced as a platform, not a business.
- Cursor went from a VS Code fork to a company jointly training models with 1 million H100 equivalents — the product category changed completely.
- The AI harness vs. AI models distinction is the key frame: harness makers get squeezed unless they also own the model layer.
- User source code from Cursor isn't as valuable as it sounds — pre-training on arbitrary code doesn't work without structure; post-training RL environments are the real asset.
- RL environments are like games the AI plays to get better — they can be bought or built, and Cursor built them through Composer training runs.
- Evals looks good means Grok V9 solved the RL environment problems Cursor designed for it — that's the actual signal, not a marketing phrase.
- Windsurf rebranded to Devin Desktop and still offers OpenAI/Claude/Gemini APIs — they remain harness-only, not model owners.
- The AI coding IDE market is collapsing from independent multi-model brokers into vertically-integrated stacks owned by model companies.
- XAI models had near-zero developer adoption before this deal; Cursor gives them millions of daily active users overnight.
- The orchestrator/executor pattern — smarter model plans, cheaper model executes — is becoming the default workflow for professional developers.
The IDE layer is just distribution — model ownership wins.
WHAT TO LEARN
Any AI coding tool that rents its intelligence from someone else is structurally weak — the acquisition cycle now favors whoever owns the model underneath the harness.
- Buying an existing platform beats building one cold — SpaceX acquired millions of daily active developers overnight rather than earning them over years.
- RL training environments are Cursor's real asset, not user source code — raw code doesn't improve a model without carefully designed reinforcement problems.
- Post-training with RL environments works like a game: set problems, run the model, grade answers, update weights — and Cursor already had those environments built.
- The orchestrator/executor pattern is becoming the default: a high-capability model plans, a cheaper instruction-following model executes the individual steps.
- Any coding tool that depends entirely on OpenAI or Anthropic APIs is in a structurally weak position — model companies can cut them out at any time.
- Windsurf rebranding to Devin Desktop signals a pivot to B2B harness sales — they are choosing not to play the foundational model game.
- XAI model adoption among developers was near zero before this deal — Cursor's distribution is the prize, not its training data.
Terms worth knowing.
- AI harness
- The software layer that sits above AI models — IDEs, agent shells, chat interfaces. It routes requests to models but doesn't own the intelligence itself.
- AI models
- The foundation models (GPT, Claude, Grok, Kimi) that do the actual reasoning. Owning the model layer is structurally stronger than owning the harness.
- RL environments
- Structured problem sets used in reinforcement learning post-training — the AI plays against them repeatedly, and correct solutions improve model weights.
- Post-training
- Training done after the initial pre-training run to shape model behavior — includes fine-tuning, RLHF, and RL with environment feedback.
- Pre-training
- The initial large-scale training run where a model learns from massive raw text/code data to build foundational capabilities.
- Colossus 2
- SpaceX/XAI's supercomputer cluster with approximately 1 million H100-equivalent GPUs, used to train the Grok model family and Composer 2.5.
- Composer 2.5
- Cursor's jointly-developed model, built on Kimi base models and post-trained with RL environments alongside SpaceXAI using Colossus compute.
- Orchestrator/executor pattern
- A two-model workflow where a high-capability frontier model generates a plan and a cheaper, faster model executes the individual steps.
Things they pointed at.
00:07linkSpaceX acquisition tweet Jun 16 2026
01:28productSpaceX stock at $212
03:56linkCursor Composer 2.5 blog post
05:33linkElon Musk Grok V9 Medium tweet May 2026
10:23productSWE 1.6 (Cognition)
Lines you could clip.
02:47
“Cursor went from a company that is just forking a VS Code IDE and distributing models and creating a harness to a company that is actually training models now.”
06:31
“I honestly don't really know what exactly is Cursor bringing on the table except for their team and the talent and whatever post-training they have done on Kimi.”
08:29
“Instead of creating a new product, he just said screw it, we'll just buy an existing platform which is in good shape. And now he's scaling it.”
Word for word.
Read-along
Don't just watch it. Burn it in.
See every word as it's spoken — crank it to 2× and still catch all of it. The same dual-channel trick behind Amazon's Kindle + Audible.
A company that builds rockets and wants to send people to Mars and Moon has announced that they want to acquire an AI IDE with a tweet where SpaceX mentioned that it has exercised the option to acquire Cursor AI in an all stock transaction with the goal of building world's most useful AI models. For the past few months, SpaceX AI has been jointly training a model with Cursor, which will be released in Cursor and Grokbuild soon.
And they just look forward to working closely with the Cursor team. And this makes sense because if you look at this tweet from April, you can see the mention that SpaceX and Cursor are now working closely together to create world's best coding work, coding and knowledge work AI and they gave Cursor two options. First is acquisition for $60,000,000,000 or pay $10,000,000,000 for their work together.
So this was basically a set deal, a done deal for SpaceX and for Cursor back in April itself, at least that's what the scenario was. But now because of the SpaceX IPO possibly going way too well, look at this, the SpaceX stock is at $212 right now.
If you look at the actual IPO figure, like where they wanted to start it roughly was $1.35 USD. And this is a massive value for a company, right?
SpaceX is over $2,000,000,000,000 over $3,000,000,000,000 if I'm not wrong.
Their total valuation is almost about $3,000,000,000,000 right now, which is an insanely, absurdly high valuation for a company that's making only $18 to $20,000,000,000 in revenue.
But see the game plan here is simple. Elon is doing the best in across or bringing rather best fields together.
He's bringing space, he's bringing AI and he's building now bringing the companies which are on top of AI as well. We have discussed time and time again that there are basically AI harness which is one thing and then there are AI models which is another thing. Now what made Cursor sort of special was not only that it is actually a good IDE which can potentially you can use to work with any sort of AI model at least in the past.
But also that it was sort of like an independent company, right? So they could probably give you whatever IDE worked best.
So they would give you access to OpenAI models, they'll give you access to Anthropic models. And based on how they were working, they would also give you access to their own models like Cursor created Composer series of models which was sort of built on top of Kimi models which also caused a small controversy when they released Composer two if I'm not wrong because they did not mention that Kimi was the base model under that.
But the idea here is that the way Cursor makes money is through enterprise deals or token margins.
So if they are flowing your tokens through OpenAir and Tropic other models, they might have the option to keep a small cut and just pass on the costs further. Now, this acquisition makes sense because if you look at SpaceX, I mean, on face it will feel like to you like what the hell is going on because SpaceX is a rockets company, right?
But the way Elon is organizing and just doing a lot of these things, it turns out that I don't know what this company is, but there is a company under Elon which is doing space, which is doing data centers and which is also doing AI.
Right? Now sometimes this company is XAI, other times this gets merged into SpaceX to call SpaceX AI and then there is an x.com platform on top of that in the first place.
Then XAI was supposed to work on things like Grok which was a platform as well as their model names. But now because XAI is now SpaceXAI which has also worked with Cursor over the last few months as we saw, potentially over Composer two or Composer three models.
Composer 2.5, sorry. Composer three is not there yet. Composer 2.5 is where we are at.
So you see, if you look at Composer 2.5 and if you read their blog post, you'll see that there are mentions of together with SpaceX AI we are training a significantly larger model from scratch using 10x more compute. With Colossal two's million H100 EQLMs, our combined data and training techniques, expect this to be a major leap in model capacity.
So Cursor went from a company that is just forking a Versus Code IDE and distributing models and creating a harness to a company that is actually training models now. Right?
Composer two and two point five are built with base models which are already there.
But it will not surprise me if eventually they would also build a base model on their own like Kimik 2.5. Right? Because now it looks like they have compute.
They have a million H100 equivalents and they have the backing and the blessing of Elon Musk and his $3,000,000,000,000 company which recently did an IPO.
So it will not surprise me if they are going to launch a foundational model specifically for programming very soon. And if you look at Composers two point five's pricing also, it's relatively affordable.
It's not on the margins of how GBD 5.5 or even like OpenAir or or, you know, Claude prices their models, which is like on the expensive side of things.
So this is even affordable in some way on API pricing as well, Not just subscription, which I'm sure they would also offer at some point. And as you can see, this was sort of evident from Elon's tweet also back in May that Grok's foundation model V9Medium, which is a 1,500,000,000,000 parameter model, has finished training, Evals looks good, a lot of Cursor data was added in supplementary training and there is more to come.
Right, so I honestly don't really know what exactly is Cursor bringing on the table except for their team and the talent and whatever post training they have done on Kimi.
And you might say that hey Mehul, how can you say that there are millions or even hundreds of millions of developers using Cursor every day. Right? So they have a lot of data.
Well the thing is the problem with this data that people are writing and typing even if Cursor hypothetically has their source code with them it's not as simple as that you just take some arbitrary random data and you just start training a model on top of that.
Especially not in the post training part which is what cursor has been doing so far. So pre training yes maybe in pre training case you can have like your AI model is actually digesting and looking at all sorts of data.
But I doubt that Cursor was going to build or at least pre train a model from scratch like build a foundation model on their own. Maybe with XAI they would but not on their own because this is actually very expensive.
But at the same time, the post training that cursor is doing it's almost fully done using techniques like reinforcement learning environments. Right? And I've talked about this a little bit on the channel.
I'll start covering this more because I'm also trying to get involved into this field. But the idea here is that these are like sort of games in a way that your AI plays in order to get better, right?
Which has the challenges, rewards, problem statements, whatever needs to be done. So these environments are created by external people. You can either buy these environments or you can build them on your own.
And you run your AI against them in training phase so you train your AI on these reinforcement learning environments and you improve the weights of the model and then you also run evals on top of that.
Once the model is trained you check how good the model is in the place. Which is what Elon said. Evals looks good.
This line if you don't understand this what this means is that the reinforcement learning environments that Cursor had or probably like wherever they got them and they ran it on this Grok foundational model V9 that was able to solve the problems the AI was given. The AI was able to solve those problems.
That is what this line means. Yeah, but this is super interesting that we have yet another player entering into the coding space.
Honestly speaking nobody at least as of now that I know, nobody actually uses XAI's models for coding. Right?
It's not that popular. Maybe like there would be a small set of Elon fans who are using this. But I don't see it in interactions I'm doing with people, in day to day people just talking about which models are good about coding.
But I do feel that this could change rapidly for a couple of reasons. First of all because of this cursor acquisition.
So basically SpaceX or XAI or whatever SpaceXAI they just got a core product which has millions of users already. That is how Elon also moved on acquiring x.com Twitter.
Instead of creating a new product, he just said that, Screw it. We'll just buy an existing platform which is in good shape. And now he's scaling Twitter.
I feel that this strategy should work out relatively well because Cursor despite all the competition and other problems it has and the subscription challenges that these companies have right now, the subsidy challenges, despite all of that, given that Cursor is now getting acquired by a company which can and has built foundational models you can expect some of the best development experience and development velocity new models getting out and delivered to you very soon.
I sort of expected it when Cognition acquired Windsurf but it seems like they are a little bit stuck into the branding part itself. Right?
So you can see like they have basically rebranded Windsurf into Dev and Desktop, first of all. Second of all, as far as I can tell, Cognition is a great company.
It has some of the best founders academically that I have seen. But they are still not playing that foundational model game, right, as far as I know.
They are building the AI harness and they are into the B2B space for selling this. But again, at the end of the day, they are still offering OpenAI, Claude and Gemini Frontier models as APIs, right, on top of their oh, actually, I I did actually forget.
They did made a SWE model. Right? Yeah.
I never got to use this because I don't use WinServe that much. But if is SWE 1.6 worth the hype?
So the first feedback we have is pretty good for what it is. It's not SONNET. I usually use SONNET to plan out changes and then use SWE to implement the plan again.
You know, we keep on seeing this pattern over and over again where you use a better model for thinking and then you use a instruction following model for executing. Right? So executor could be a cheaper model, but basically you want a smarter model to think out the plan details.
So the guy says it's pretty good, slightly better I'd say, but I have time out issues with it, which is I'm assuming Kimi K 2.6. And now we have Kimi K2.7 code as well. Right?
So I'm assuming that that bypasses the SWE 1.6 according to that person.
So I mean if you have money and if you have time to wait I think like you know, plus 4.7A, GBD 5.5. These are the sort of models that you'll just end up keeping using over and over again for everything.
If you're a little bit money conscious, you're paying APR rates, you know, you don't want to spend way too much, then you will have this orchestration sort of thing happening where for some things you're using something else. For others, you're using something cheaper as an option.
But I don't know, we don't know where this would end. What's the end result of doing all of this?
Every single company that we know who's working on Frontier AI right now, Anthropic, I would probably add XAI also now given that the cursor acquisition is a big thing for programmers at least.
OpenAI we have let's say Kimi, DeepSeek, GLM, ZAI or rather I should just say or Moonshot for Kimi.
You know, tell me if I'm missing any other interesting companies. Mistral maybe. I don't know like what's going on with Mistral.
There's a cat meme that's going on X these days. I don't know if you guys are following but people are saying that Mistral is about to release like a GAT model or something.
I don't know like what the meme is about. But I hope that's true because more content to cover, more sponsors to integrate even though this is not a sponsored video.
So make sure you leave a like and subscribe. But yeah, this is actually good right in terms of pricing, in terms of competition, in terms of velocity of things that are getting shipped.
It's a fun time to live in. That's all for this video. Hopefully you liked it.
If you did make sure to leave a like and subscribe to the channel. I am going to see you in the next video soon.
If you're still watching, make sure you leave a comment. I watched till the end below to tell me that you were still here. And let me know what do you think about the video.
The Hook
The bait, then the rug-pull.
When a rocket company buys a code editor, the knee-jerk reaction is confusion. The real story is that SpaceX isn't buying a text editor — it's buying the distribution layer that sits between millions of developers and whatever AI model they use every day.
Named ideas worth stealing.
01:33concept
AI harness vs. AI models
The harness (IDE, agent shell) routes requests to models but doesn't own intelligence. Model owners hold the structurally stronger position.
Steal forany analysis of AI tool company competitive moats
06:20concept
Pre-training vs. post-training asset distinction
Raw user code is useful for pre-training. RL environments are what makes post-training work. Cursor's value is in the latter.
Steal forAI company due diligence or discussion of what data moats actually means
10:40model
Orchestrator / executor pattern
- Orchestrator: high-capability model plans and reasons
- Executor: cheaper instruction-following model implements
Use an expensive frontier model for planning, a cheaper model for execution. Reduces cost without sacrificing plan quality.
Steal forany agentic coding workflow or multi-model cost optimization
How they asked for the click.
VERBAL ASK
12:10subscribe
“That's all for this video. Hopefully you liked it. If you did make sure to leave a like and subscribe to the channel.”
Standard subscribe ask at the end, light and non-pushy. Also uses a mid-video self-deprecating aside about not being sponsored.
MENTIONED ON CAMERA
FROM THE DESCRIPTION
Visual structure at a glance.
