Install Omarchy on it!

What's Inside a GPU, and Why AI Needs Thousands of Them? youtu.be/SJAMqhf2L5Q?si=lFhN… via @YouTube

Connect your favorite bots to the plugins and external services and see the magic happen!

AI has reaches such an inflection point. From the release of OpenClaw to Dot. It’s getting crazy! #ai

So far I love both GrokBot and Muse. Let’s see what dots bring to the table

It’s amazing that even now people are actively rejecting the tech or not paying attention.

The open source models are now next to frontier. You only have to wait 1-2 weeks. Sometimes less!! What a time!

Why are LLMs so dumb? I cannot understand anything they say these days. It’s with all of them. I see their own thoughts a bit easy to understand than the final summary that looks like an old fashion Telegram message (not the app). It all looks gibberish! This wasn’t my experience a few months ago. Who else can relate?

How Jev Can Become the Decision Layer Around AI The more I think about Jev, the more interesting it gets. Not because it is another AI model. But because it can sit between an AI system and the action that happens next. You give it context. You ask a small question. It gives you a structured decision with confidence. Then your code decides what to do. That sounds simple. But there are a lot of places where this becomes useful. 1. Cybersecurity Imagine an AI agent wants to run a command, call an API, or access a file. Before you let it do that, Jev can answer questions like: “Is this action risky?” “Does this action match what the user asked for?” “Is this request outside the agent’s normal permissions?” “Does this webpage contain instructions that look like prompt injection?” You are not asking Jev to solve cybersecurity. You are using it as a checkpoint. Agent wants to act. Jev judges the action. Your code can then: Allow it. Block it. Ask a human. Or send it to a stronger model. 2. Document parsing Imagine you are processing thousands of contracts, resumes, invoices, research papers, or government documents. A normal LLM can read them. But you may not need a large model for every small decision. You might ask Jev: “Is this document a contract?” “Does this page contain financial information?” “Is this section about termination?” “Does this resume mention AWS experience?” “Is this document relevant to the user’s search?” Now Jev becomes a cheap sorting layer. The interesting documents move forward. The irrelevant ones stop there. 3. Social media Suppose you manage thousands of posts, comments, or messages. Before doing anything expensive, Jev could answer: “Is this comment a question?” “Is this customer angry?” “Is this post asking for support?” “Is this likely spam?” “Does this message need a human response?” Now your system can route things automatically. Support question → support queue. Sales question → sales team. Spam → ignore. Angry customer → human. Simple comment → automated response. 4. Model routing This may be one of my favorite use cases. Start with a small, cheap model. Then ask Jev: “Is this problem actually difficult?” “Is the current model likely to handle it?” “Does this require deeper reasoning?” If not, keep using the small model. If yes, move to Sonnet, Opus, GPT, or another stronger model. Instead of sending everything to your most expensive model, you only escalate when necessary. 5. Everyday software decisions This is where it gets even more interesting. A lot of software contains tiny decisions that are hard to express with normal if/else rules. “Does this email sound urgent?” “Does this expense look unusual?” “Is this search result actually relevant?” “Does this support ticket need engineering?” “Is this user probably trying to cancel?” None of these questions require a five-paragraph AI response. You just need a judgment. Yes or no. A category. A score. A confidence level. Then normal software takes over. That may be the simplest way to think about Jev. Large models do the work. Jev helps decide what should happen next. #Jev #TypeSafeAI #SystemOneModel #AIAgents #AgenticAI #ArtificialIntelligence #Cybersecurity #LLM #Automation #AISafety

Yup, building UsefulPrompts.ai via DSPy. And now adding Jev to it.

What do you mean output tokens are free?? Like forever?? What’s is happening! 😳🤯😜