I built a native Android app that lets a maintenance contractor search photos, voice notes and reports by describing a problem. It runs completely offline. There’s no cloud search service behind it, and the phone doesn’t need a signal. Read more
Meta has arrived with Muse Wonder, and the claims are bold. Its launch positions Muse Wonder ahead of GPT-6.1 Sol, while Muse Wonder Full supposedly beats Fable 5.1 and GPT-6 Astra. That sounds impressive. I wanted to find out what those claims meant for actual projects. Read more
I tested Google’s Gemini 4 Argon against Claude Opus 5.5 on six projects, from a Canva-style editor to a fully rendered kitchen in Blender. I wanted to find out which model could turn a detailed brief into something useful, rather than something that simply looked impressive at first glance. Read more
Jev can now make decisions about images, rather than just text. You describe what it should check, supply a picture, and get a structured answer. A new box question type can also return coordinates around an object or relevant area. Read more
I trained a small, open-source decision model on my own machine to do one job: pick the next tool in a customer support conversation. Training took minutes, and the training data never left my network. The model was Laya, which has roughly 420 million parameters. Those parameters are the internal values that training adjusts. Compared … Read more
Small AI decision models are getting interesting. Models such as Winnow, Decider, and Laya can make decisions on your own hardware. That gives you options if you want to keep inputs inside your infrastructure, run without a network connection, or put a decision step directly into software and automations. But a local model is useful … Read more
Jev isn’t a chat model. It’s a decision model. You give it context and a question, and it returns an answer that your software can use. That distinction sounds small, but it changes where AI fits in an application. A chat model might write a customer reply. A decision model can determine which team should … Read more
A RAG agent does a lot of work before it answers a question. It searches documents, decides which passages matter, chooses whether to search again, and checks whether its answer matches the sources. Each step can involve a small judgment call. I used to rely on language models for many of those calls. They worked, … Read more
GPT-6 Astra is extremely capable, but capability alone doesn’t guarantee a good workflow. I see two common problems. Some people use Astra like a standard chatbot and leave a lot of value on the table. Others put every task on the highest effort setting, use computer control for everything, and burn through usage far faster … Read more
GPT-6 Astra represents a major step forward for AI agents that can operate a computer and browser. Instead of only producing text, code, or recommendations, it can work through applications, interact with websites, click through interfaces, and complete multi-step tasks. I tested it across six very different examples. Some were serious business workflows. Others were … Read more
Claude can create a beautiful-looking website. But at its core, it doesn’t know what great design is. Models such as Fable 5.1 and Opus have learned from millions of websites. When I ask for a “modern-looking website,” I’m often asking for the average of all those sites. That’s why so much AI-generated work ends up … Read more
Fable 5.1 is Anthropic’s strongest model yet for coding and design, and the /design command gives Claude a full visual canvas inside the Claude desktop app. I can also trigger the same workflow from Claude Code in the terminal. That sounds like a shortcut to great design. It isn’t, at least not by itself. If … Read more
Claude Design can create surprisingly good motion graphics in a matter of minutes. I can describe a character, a movement, a burst of confetti, a glow, and a shadow, then refine all of it through a simple chat. The difficult part comes at export. Right now, Claude Design exports video as MP4. That works perfectly … Read more
A lot of major names in AI have announced a new open standard called Agent Plugins. The idea is refreshingly simple. It gives developers one portable format for bundling agent skills and MCP servers, so the same plugin can work across multiple AI coding agents. That matters because AI agent workflows are becoming fragmented. A … Read more
AI systems can fail while every normal engineering signal looks fine. The app is online. Error logs are clean. Tests pass. No exception gets thrown. Yet the answer is wrong, the agent used the wrong tool, response quality has dropped, or the monthly model bill has suddenly tripled. That is the awkward reality of software … Read more
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