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Generative AI Is Easy to Demo but Hard to Deliver: The MVP Illusion

Generative AI has become the easiest demo in tech history, but one of the hardest products to operationalise. Walk into any startup pitch meeting, and you'll witness something remarkable: entrepreneurs can now showcase seemingly revolutionary AI capabilities in minutes. A few prompts to GPT-4, some impressive outputs from Midjourney, or a quick code generation session with GitHub Copilot, and investors are nodding appreciatively. The wow factor is instant, the potential appears limitless, and the competitive advantage seems obvious.

A Guide to Optimizing Kubernetes Clusters with Karpenter

With the promise of auto-provisioning and self-healing, Kubernetes environments can be an attractive option for hosting your application platform. However, with increasing budget restrictions, the competitive cloud providers and offerings, and the need to do more with less, engineers are looking to get a handle on their resource utilization.

Building RAG with enterprise open source AI infrastructure

One of the most critical gaps in traditional Large Language Models (LLMs) is that they rely on static knowledge already contained within them. Basically, they might be very good at understanding and responding to prompts, but they often fall short in providing current or highly specific information.

LLM Testing in 2025: Methods and Strategies

Large Language Models, or LLMs, have become a near-ubiquitous technology in recent years. Promising the ability to generate human-like content with simple and direct prompts, LLMs have been integrated across a diverse array of systems, purposes, and functions, including content generation, image identification and curation, and even heuristics-based performance testing for APIs and other software components.

NoOps and the Future of DevOps: How GenAI is Eliminating the Tools Tax

Software development has evolved into a complex symphony of tools, platforms, and processes. While each new tool promises to solve specific challenges, together they’ve created an unexpected burden on development teams. The very solutions meant to streamline our work have paradoxically become a source of friction. A shocking stat from Gartner reveals the scale of this crisis: developers spend only 10-25% of their time actually writing code.

How to Test and Formal Release Apps with AirDroid Business?

Welcome to this tutorial video where we walk you through how to test and formally release your company-owned apps or apps from the Google Play Store in AirDroid Business. AirDroid Business is a mobile device management (MDM) solution that helps you manage all your Android devices effectively and securely.

Three benefits of AI-Powered Incident Management

Today, every enterprise is digital. Regardless of industry, every business must incorporate digital technologies and strategies into its operations to remain competitive. Maintaining reliable IT infrastructures and digital services while minimizing downtime due to unplanned outages is critical to business success.

Breaking Silos: Unifying DevOps and MLOps into a Cohesive Software Supply Chain - Part 2

In this blog series, we will explore the importance of merging DevOps best practices with MLOps to bridge this gap, enhance an enterprise’s competitive edge, and improve decision-making through data-driven insights. Part one discussed the challenges of separate DevOps and MLOps pipelines and outlined a case for integration.

Troubleshooting CORS Errors in Offsite API Calls

You may have wrestled with a web application attempting to call an offsite web service, such as an OpenTelemetry Collector, and gotten an odd error with the word CORS in it. Something like: Or, maybe you got a generic thrown error from your fetch statement that states Error: Failed to fetch …and you wondered, “What’s the problem, and how can I fix it?” These kinds of errors are called CORS errors, and they can be a bit confusing.