Mobile apps used to feel simpler. Now, even basic utilities often come bundled with subscriptions, account systems, telemetry, recommendation feeds, or unwanted AI features. Even Firefox — one of the few browsers people still pointed to for privacy — recently started softening some of its old “we don’t sell your data” messaging while pushing deeper into ad-tech and AI integrations [1] [2]. That rubbed a lot of people the wrong way, including me.

Foundational Agentic RAG is a template-level framework for building secure, document-grounded AI assistants using Retrieval-Augmented Generation (RAG) and agentic reasoning. Designed with scalability and modularity in mind, it enables individuals or organizations to index internal knowledge (PDFs only) and interact with it through a conversational UI. The system is powered by OpenAI’s GPT models, FAISS vector search, LangChain/LangGraph for agent behavior, and a customizable Vite + React frontend with Clerk authentication.

By automating processes, improving user experiences, and offering intelligent solutions in a variety of fields, AI agents have completely transformed industries. This advancement saves time and resources while improving accuracy and efficiency. Developers and organizations are increasingly building AI agents for applications such as customer service bots and the automation of tedious processes. However, a common limitation among these agents is their inability to efficiently retain information from past interactions, leading to repetitive conversations and a lack of personalized engagement.

In this tutorial, we will be building a simple Morse Code Translation API using GoFr, a framework designed to simplify microservice development. GoFr is ideal for building lightweight APIs that are easy to deploy, manage, and monitor. If you’re new to GoFr or Go in general, this is a great way to get started.

Want to build a system that detects two-wheeler traffic rule violations? You’re in the right place! In this tutorial, I’ll show you how to create a simple violation detection system using Python and Roboflow. We’ll focus on three main violations:

Have you ever used ChatGPT, Gemini, Claude, or any other generative AI application and wondered how you could build something similar on your own? If you’ve ever wanted to create a chatbot that can answer questions based on specific documents, data, or context, you’re in the right place. In this guide, we’ll walk through the process of developing a local AI chatbot using Ollama and LangChain. Whether you’re interested in personal projects or professional applications, this tutorial will equip you with the knowledge to get started.

APIs are the secret sauce that adds exquisite flavour to a developer’s projects, acting as bridges that connect different software components and services. They give developers access to a wide range of functionalities and data, allowing them to improve their projects with features that they wouldn’t have had the resources to build from scratch. Whether it’s accessing real-time weather data, retrieving information about movies and TV shows, or integrating authentication SDK into applications, APIs empower developers to create richer, more dynamic experiences for their users. In this article, we’ll explore eight fun and free(mium) APIs that are sure to inspire your next project.

A user can play Gravity Glide, a game about switching gravity to evade obstacles, on their pc or smartphone. Create a script PlayerMovement.cs. Grab the player rigidbody and give it a constant velocity in x-axis of 5, and make it move in x-axis automatically. For gravity switching, setup touch input for android and spacebar for windows. Keep changing rigidbody gravity scale between 1 and -1 with every switch performed.