However after looking at all of these articles, these all seem like instances of users misusing the product. The product happens to reply on social media, so media publications immediately capitalized on this.
Seems less like malicious intent from xAI's part and more like a product with young and/or insufficient moderation controls.
Grok Build seems faster to me than `omp` and Claude Code but I can't put my finger as to why. Anecdotally, after disabling code uploads the agent doesn't respond instantly anymore (it used to respond within milliseconds).
For sure! And maybe display a helpful message on your screen with the most convenient payment method (usually Bitcoin) to send a quick payment to unlock your files.
Grok Build has had impressive performance in a couple of my projects. And fast. So this revelation has been very disappointing...
I will say, a majority of the code I'm writing now is fully through an online LLM. If a company wanted to reconstruct a project I'm working on, they could just replay all of the tool calls from their logs, if they decide to retain the data (I did this locally once to recover a project that I mistakenly clobbered in Git).
Still, this is a big overstep IMO. At the very least, they should make it clear in their terms of service and privacy policy, and not hidden through legalese. Not all usage of Grok Build will be through their enterprise plan which offers ZDR.
Refreshing to see this be the top comment, thank you. I agree.
To answer your question, Grok 4.5 seems to be pretty good at simple tasks and gets even some of the trickier ones correct but it tends to struggle with bigger codebases that aren't very uniform. I've noticed that it uses a fraction of the tokens to get to solutions which is really impressive compared to GLM 5.2 which tends to be an overthinker.
I'm not sure if Grok 4.5 will become part of my stack yet but I am genuinely impressed with what it's been able to achieve.
I'm also unsure if Grok 4.5 is the same base as Grok 4.3. Maybe it is and the data they've used in pretraining is additive (the Cursor data) but it feels like a completely different model than the previous Grok versions.
I've come to this conclusion too. It's a bit disappointing. I fully realize this is more than likely just user error. And now with AI agents the maintenance of a Postgres instance is likely less of a burden. But I can't help but yearn for the simplicity of a single SQLite file and bespoke solutions for things like queues, pub/sub, caching, etc.