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. ...
You know NumPy and Pandas. Now it is time to train a model. scikit-learn is the standard library for machine learning in Python. It is simple, well-documented, and works for most real-world tasks without a GPU. Setup pip install scikit-learn pandas numpy import sklearn print(sklearn.__version__) # 1.5+ The ML Workflow Every supervised ML task follows these steps: 1. Load data 2. Prepare features (X) and target (y) 3. Split into train and test sets 4. Train a model 5. Evaluate on test set 6. Make predictions on new data Let’s go through each one. ...
Before you train any machine learning model, you need to handle data. NumPy and Pandas are the two libraries you will use every day. This is a practical crash course. No theory — just the operations you actually need. Setup pip install numpy pandas Check versions: import numpy as np import pandas as pd print(np.__version__) # 2.x print(pd.__version__) # 2.x NumPy: Arrays NumPy gives you fast multi-dimensional arrays. They are faster than Python lists for math operations. ...
AI and machine learning are not the same thing. In 2026, that distinction matters more than ever. This article explains the current state of AI/ML, what changed recently, and gives you a clear learning path as a developer. What Changed in the Last Two Years Two years ago, most developers used AI as a tool — an autocomplete, a chatbot, a code generator. Now, developers are also building with AI. They embed models into apps, fine-tune models for specific tasks, and build pipelines that chain AI calls together. ...
You are working on a big refactor. Claude Code keeps asking: “Can I edit this file?” “Can I run this command?” “Can I delete this?” You say yes every time. There is a flag that skips all of that. It is called --dangerously-skip-permissions. Developers call it YOLO mode. This article explains what it does, when it is safe, and when it can destroy your project. What Is YOLO Mode? YOLO mode is Claude Code running with no permission prompts. It executes everything — file edits, shell commands, deletions — without asking. ...
Anthropic released a feature that changes how you work with Claude Code. It is called Remote Control, and it does exactly what the name says: you can control a Claude Code session running on your laptop from your phone, tablet, or any browser. Start a task at your desk. Walk into a meeting. Keep watching from your phone. What is Claude Code Remote Control? Claude Code Remote Control connects the Claude mobile app (iOS and Android) and the web interface at claude.ai/code to a Claude Code session running on your local machine. ...