Building
AI Guardrails and Trustworthy LLM Evaluation: Building Responsible AI Systems
Introduction: The Rising Need for AI Guardrails As large language models (LLMs) grow in capability and deployment scale, the risk of unintended behavior, hallucinations, and harmful outputs increases. The recent surge in real-world AI integrations across healthcare, finance, education, and defense sectors amplifies the demand for robust safety mechanisms. AI guardrails—technical and procedural controls ensuring…
China’s YMTC moves to break free of U.S. sanctions by building production line with homegrown tools — aims to capture 15% of NAND market by late 2026
Yangtze Memory Technologies Co. (YMTC), China’s leading producer of NAND memory, has been on the Entity List of the U.S. Commerce Department since late 2022, which essentially bars its access to advanced fab tools. Despite sanctions and restrictions, YMTC plans to expand its production capacity this year, aiming to capture a 15% share of NAND…
Building a BioCypher-Powered AI Agent for Biomedical Knowledge Graph Generation and Querying
In this tutorial, we implement the BioCypher AI Agent, a powerful tool designed for building, querying, and analyzing biomedical knowledge graphs using the BioCypher framework. By combining the strengths of BioCypher, a high-performance, schema-based interface for biological data integration, with the flexibility of NetworkX, this tutorial empowers users to simulate complex biological relationships such as…
Building Advanced Multi-Agent AI Workflows by Leveraging AutoGen and Semantic Kernel
In this tutorial, we walk you through the seamless integration of AutoGen and Semantic Kernel with Google’s Gemini Flash model. We begin by setting up our GeminiWrapper and SemanticKernelGeminiPlugin classes to bridge the generative power of Gemini with AutoGen’s multi-agent orchestration. From there, we configure specialist agents, ranging from code reviewers to creative analysts, demonstrating…
Building Event-Driven AI Agents with UAgents and Google Gemini: A Modular Python Implementation Guide
In this tutorial, we demonstrate how to use the UAgents framework to build a lightweight, event-driven AI agent architecture on top of Google’s Gemini API. We’ll start by applying nest_asyncio to enable nested event loops, then configure your Gemini API key and instantiate the GenAI client. Next, we’ll define our communication contracts, Question and Answer…
Selfish reasons for building accessible UIs
All web developers know, at some level, that accessibility is important. But when push comes to shove, it can be hard to prioritize it above a bazillion other concerns when you’re trying to center a and you’re on a tight deadline. A lot of accessibility advocates lead with the moral argument: for example, that disabled…
Building AI-Powered Applications Using the Plan → Files → Code Workflow in TinyDev
In this tutorial, we introduce TinyDev class implementation, a minimal yet powerful AI code generation tool that utilizes the Gemini API to transform simple app ideas into comprehensive, structured applications. Designed to run effortlessly in Notebook, TinyDev follows a clean three-phase workflow—Plan → Files → Code—to ensure consistency, functionality, and modular design. Whether building a…
Breaking Boundaries: Building a Tangram Puzzle With (S)CSS | CSS-Tricks
, simple and effective. For rotation, we added eight radio buttons, each representing a 45-degree increment: 45°, 90°, 135°, all the way to 360°. These simulate rotation controls entirely in CSS. Every potential shadow position got its own radio button too. (Yes, it’s a lot, I know.) And to wrap it all up, I included…
Building Confidence in AI: Training Programs Help Close Knowledge Gaps
AI is reshaping the workforce at a breakneck speed, yet training efforts aren’t meeting the moment. Despite a quarter of executives feeling bullish on the technology, only 12% of workers have received AI-related training in the past year. This lack of preparation not only hinders the successful and safe adoption of AI, but also creates…
A Step-by-Step Coding Guide to Building an Iterative AI Workflow Agent Using LangGraph and Gemini
In this tutorial, we demonstrate how to build a multi-step, intelligent query-handling agent using LangGraph and Gemini 1.5 Flash. The core idea is to structure AI reasoning as a stateful workflow, where an incoming query is passed through a series of purposeful nodes: routing, analysis, research, response generation, and validation. Each node operates as a…