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Building a CLI with Laravel Prompts

As Laravel web developers, we often need to build Artisan commands for our applications. But interacting with the console can sometimes feel a little cumbersome. Laravel Prompts is a package that aims to improve this experience by providing a simple approach to user-friendly forms in the console. In this article, we'll take a look at Laravel Prompts and some of its features that you can use. We'll then build a simple GitHub CLI client using Prompts to demonstrate how to use it in your applications.

Everything you need to know about the new user experience across Qlik Cloud Analytics and Qlik Talend Cloud

Do attractive things work better? Some say they do, and for good reason. According to a widely cited Stanford research study, 94% of first impressions are design related. Visually appealing designs have the remarkable ability to influence user perception and make it easier for people to find solutions to the problems they encounter. This is a testament to the power of design in shaping the user experience.

Data Strategies Map a Journey From Origin To Destination

There is a scene in Mission: Impossible – Rogue Nation where Tom Cruise is hanging onto the outside of a jet as it has taken off. And while, yes, he’s going with it, he’s not really on board or in control. Some data executives feel like that. It’s not enough to establish goals — or, the destination in this metaphor. The data strategy must provide a flight plan for making sure you get there — on time, on budget and, of course, safely on board.

Top Benefits of API Observability for Modern Applications

API observability is essential for enhancing performance, speeding up issue resolution, and tightening security. An API observability tool is crucial for understanding and managing the complex web of API interactions within modern enterprise applications. With the benefits of API observability, you can dive deep into API behavior, ensuring reliability and better user experiences.

Improve Customer Experience and API Security with WSO2 Identity Server 7.0

In today’s digital world, APIs have become key to connect apps and services, both internally and externally. However, when integrating with external entities like partners and service providers, API security is a major concern for businesses. And from a user’s perspective, traditional authentication approaches in mobile apps or digital channels often deliver a less-than-ideal digital experience.

Quickly Establish a Performance Baseline: A Simple Guide for Immediate Results

Creating a performance baseline is a fundamental step in ensuring that your software applications run smoothly and efficiently. This guide will focus on how to quickly create a performance baseline for load testing, making it accessible to everyone from non-technical business owners to seasoned software engineers. Let’s dive in!

Unveiling the Future of Testing: Automation for All with SmartBear HaloAI

SmartBear is revolutionizing the way teams deliver high-quality software, faster than ever before. Today, we’re announcing a set of major product enhancements to Zephyr Scale, the leading Jira-native test management platform, to empower everyone on your team to automate tests, regardless of coding experience. This “Automation for All” is fueled by the power of SmartBear HaloAI, which is transforming software development and testing productivity.

Testlio Clients Achieve Estimated 5x ROI on Payments Testing

Company drives effort to reduce $1.1 trillion in failed digital payments. Austin, TX, July 9, 2024 – Testlio, a leading quality management company, today announced that its clients achieve an estimated 5x return on investment (ROI) through its payments testing services. This milestone underscores Testlio’s pivotal role in mitigating the critical issue of failed digital payments, which cost businesses an estimated $1.1 trillion annually.

RAG vs Fine-Tuning: Navigating the Path to Enhanced LLMs

RAG and Fine-Tuning are two prominent LLM customization approaches. While RAG involves providing external and dynamic resources to trained models, fine-tuning involves further training on specialized datasets, altering the model. Each approach can be used for different use cases. In this blog post, we explain each approach, compare the two and recommend when to use them and which pitfalls to avoid.