Anthropic launched a new Claude Code feature on April 14, 2026: Routines. A Routine is a Claude Code automation that runs in Anthropic’s cloud. You set it up once. Then it runs on a schedule, on an API call, or when a GitHub event fires — with your Mac completely off. What Is a Routine? A Routine packages three things together: ...
If you use a Mac, you probably press Cmd+Space dozens of times a day. That opens Spotlight. It works. But it is basic. Raycast does everything Spotlight does — and a lot more. And the core is free forever. Who is this for? If you are a developer on Mac who wants faster app switching, clipboard history, and integrations with tools like GitHub, Linear, and VS Code — all with a single hotkey — this is for you. ...
Every pull request in your repo should be reviewed. But manual code reviews take time — often 2-4 hours per PR. And reviewers miss things when they are tired or rushed. AI code review tools read every PR automatically and leave comments in minutes. Not replacing human reviewers — augmenting them. The AI catches the obvious bugs, the human reviewer focuses on architecture and business logic. Here is how to set it up on GitHub. Three options — from easiest to most customizable. ...
Most developers use Claude Code like a chatbot. Type a question, get an answer, copy the result. That is maybe 20% of what it can do. Here are 5 tricks that change how you work. 1. The ! Prefix — Run Shell Commands Instantly Type ! before any shell command in the chat and Claude runs it immediately — and reads the output. ! git log --oneline -5 ! npm test ! docker ps ! cat package.json Claude sees the result as part of your conversation. No copy-pasting terminal output into the chat. No switching windows. ...
Everyone writes about AI tools. Nobody shows how they actually use them day to day. Here is my real workflow — which tools I open, when I use each one, what works, what fails, and what it actually costs. No sponsored content. Just what I do. My Daily Setup Three screens. Two AI tools always running. One browser tab. Left screen: Cursor (main code editor) Right screen: Terminal with Claude Code Browser: Claude.ai or ChatGPT for quick questions That is it. No 10 tools. No complex setup. Two AI coding tools and a chat window. ...
Every AI agent we have discussed so far needs the cloud. You send a prompt to Claude or GPT, wait for a response, and pay per token. That works for coding and content generation — but what about a sensor on a factory floor? A camera in a farm? A device with no internet? That is where edge AI comes in. Running AI models directly on the device — no cloud, no latency, no API costs. ...
Most “AI apps” in 2023-2024 were wrappers. Take a text box, send it to ChatGPT API, display the response. That was it. In 2026, a new category is emerging: AI-native apps. These are applications designed from the ground up with AI as the core logic — not an add-on feature. The difference matters. And understanding it will change how you build software. What is an AI-Native App? An AI-native app is an application where AI is the primary logic engine, not a helper feature. ...
If you test APIs, you probably use Postman. But Postman has some problems. Bruno fixes them. The Postman Problem Postman started as a simple tool. Now it requires an account to use. Your collections sync to Postman’s cloud. The free tier has limits. And if Postman changes its pricing again, you lose access to your work. That is a lot of trust to put in one company. What Is Bruno? Bruno is an open-source API client. It works like Postman. You can send HTTP requests, test REST APIs, GraphQL, and gRPC. You can organize requests into collections. ...
You have probably seen “MCP” everywhere lately. Every AI tool seems to support it now. But what is it actually? The problem before MCP Imagine you have 10 AI tools and 20 data sources. Databases, APIs, file systems, Slack, GitHub. Each AI tool needed its own custom integration with each data source. That is 200 different integrations to build and maintain. Developers called this the N×M problem. What MCP does Model Context Protocol is a standard. Like USB-C, but for AI. ...
PyTorch is the standard framework for deep learning research and production. Most AI papers, Hugging Face models, and state-of-the-art systems use PyTorch. This article gets you from zero to a working neural network. Setup pip install torch torchvision import torch print(torch.__version__) # 2.x print(torch.cuda.is_available()) # True if you have a GPU Tensors A tensor is the fundamental data structure in PyTorch. It is like a NumPy array, but it can run on GPU and supports automatic differentiation. ...