AI on X has become an endless parade of flashy demos. Most look cool, but very few are genuinely useful. The novelty is wearing off, and people are getting desensitized. The next phase isn't about making AI look smarter—it's about making it more useful. If we keep optimizing for virality over utility, we'll erode the perceived value of AI itself.
BREAKING: President Trump reveals the details of his conversation with FIFA President Gianni Infantino over the controversial red card call on star American player Folarin Balogun.
"All I did was ask for a review because I didn't think it was a foul. And, you know, again, I'm good at this stuff. I didn't think it was a foul. I thought it was two great athletes that crashed into each other and got entangled."
"I think they made a really brilliant decision. I think the referee's call was horrible and nobody talks about that. They talk about the red card like it's fine, nobody talks the referee's decision to red card."
GPT-5.5 keeps cutting corners. When asked to scrape or fetch a webpage, it just gets stuck, then uses old data to fake an answer instead of verifying the latest information. Is there any good way to fix this?
Local small models won’t replace cloud LLMs; their real opportunity is becoming OS-level agents that understand intent, call native tools, and complete tasks directly on personal devices.
Mac-1 captures the current shift: model capability is becoming commoditized, while the next battleground is the agent application layer, native tool orchestration, and real workflow execution.
Here's a teaser of our Mac-1 model.
> 6.6B model
> runs locally (on any Mac)
> requires 7GB RAM (12GB ideal)
> can use 487 MacOS native tools
> perform multi-tool chained tasks
> reasoning: ON
> output: ~65 tok/s
We built a robust application layer around the model to make UI/UX MacOS native. The "model-focused" SaaS era is here.
Stay tuned for more.
Why I Gave Up on Codex PlusPlus?
After spending another two days struggling with Codex PlusPlus, I’ve decided to give up on it.
My advice to most people who don’t have an IT background is: don’t use it.
On one hand, Codex updates so quickly that compatibility issues keep popping up. On the other hand, ask yourself: why use Codex with your own API in the first place? What’s the real value?
For most users, professionalism and stability are the core requirements.
Don’t be like me—constantly jumping from one agent to another, repeatedly trying to build things from 0 to 1, while never truly thinking through the actual project itself.
That’s not where AI delivers its greatest value.
Sometimes, the right move is to let go of what isn’t working, stop chasing every new AI tool, and take the time to think deeply about your project.
Don’t let AI keep you running in circles and standing still.