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How to Manage Shadow IT in 2026: Detection, Policy And Control

Shadow IT is any hardware, software or IT resource running inside your organization that the IT department never approved, never configured and, in most cases, does not know exists. It covers the file sharing account someone opened with a departmental card, the personal laptop plugged into the office network, and the AI assistant installed on a work machine last Tuesday. None of it is necessarily malicious, and all of it sits outside every control you have.

How Global Businesses are Adapting to an Increasingly Connected Economy

In recent years, advances in technology and digital commerce have made it easier than ever for businesses of all sizes to operate internationally. In an increasingly connected global economy, there are both new opportunities and challenges to be aware of. This post will explore how global businesses are adapting to an increasingly connected economy in 2026. Read on to find out more.

Nvidia Forecasts 70% Revenue Growth as AI Spending Heads Toward $1.3 Trillion

Nvidia has decided to break with its usual practice of providing guidance only for the upcoming quarter and, for the first time, has given investors an outlook for the next fiscal year. The company expects to increase revenue by approximately 70% to $673 billion, which would further cement its position in the Dow Jones index and make it the secondlargest U.S. technology company by revenue, after Amazon. This projection substantially surpasses market expectations based on growth of about 44% and is effectively an attempt to convince the market that the AI boom is far from over. Against this backdrop, Nvidia stock moved higher.

What an "Agent Harness" Actually Is - and Why Raw Model Calls Don't Survive Production

There's a demo that convinces every engineering team that agents are ready: someone gives a model a goal, it calls a couple of tools, and it produces a result that would have taken a person an hour. The gap between that demo and a system real users depend on is enormous, and most of that gap is not the model. It's everything around the model - the layer that decides what to do next, calls tools safely, remembers what happened, asks for help when it should, and records the whole run so you can debug it. That layer has a name: the agent harness.

How AI-Based Crop Counting and Health Analysis Boost Agricultural Yield

Modern farms need faster, more reliable ways to understand plant population, detect stress early, and act before losses spread, because manual scouting is time-consuming, resource-intensive, and highly dependent on human expertise. That challenge matters at the yield level, since pests and diseases can significantly reduce crop productivity, and early recognition is critical for protecting both output and quality. AI-based crop counting and health analysis address this problem by turning images, sensor data, and field observations into structured decisions that support more precise crop management.

Which Walk-Behind Floor Scrubber Brands Are Good for Schools?

Choosing a floor cleaning machine brand is rarely a simple popularity contest. For school facility managers choosing compact scrubbers, the stronger question is which company can solve the actual cleaning problem in classroom corridors, cafeterias, gyms, restrooms, entrances, libraries, and multi-use halls. A scrubber or sweeper is not a decoration in a purchasing spreadsheet; it becomes part of the daily workflow. Operators depend on it when traffic is heavy, supervisors depend on it when floors must be dry before opening, and managers depend on it when labor hours are already tight.

Monitor smarter with Applications Manager's GenAI capabilities

GenAI has moved well past the pilot stage. According to a Gartner finding, by 2026, more than 80% of enterprises will have used GenAI APIs or deployed GenAI-enabled applications in production. Today, GenAI is becoming an integral part of how infrastructure and application teams work every day. Organizations are depending on LLMs from a diverse range of vendors—OpenAI, Anthropic, Google AI, and DeepSeek—based on the strengths each offer for different use cases.

AI Code Review Loop in the Terminal: Introducing Harness CLI for Harness Code

Every developer knows the fatigue of the "12-tab code review dance": Agents have become first class citizens in SDLC and AI coding agents author code alongside human engineers, thus the above context switching destroys flow state. GitHub's gh CLI proved developers love the terminal, but modern delivery is tied to AI reviews, pipeline executions, risk scoring, and autonomous agents, not just git hosting.