The 2024 Stack Overflow developer survey results included critical themes and sentiments around AI and the developer experience. With responses from over 65,000 developers in 180 countries, this report provides a comprehensive overview of the current state of software development. In this article, we’ll examine some of the report’s key trends and highlights and their strategic implications.

A quality assurance (QA) test plan or a software test plan is a document that outlines the steps, approaches, tools, and best practices for carrying out QA testing for your project. The purpose of a QA test plan is to define testing goals and objectives while considering cost, project requirements, and delivery timelines. Ultimately, this document ensures that all stakeholders are unified in their commitment to delivering a high-quality product.

Smooth and effective data migration helps organizations move data across systems efficiently to maintain their competitive advantage. Still, Gartner reports that only 17% of initiatives involving data migration are completed within their budgets or set timelines. Understanding these data migration challenges is the first step toward overcoming them. In this blog, we’ll explore data migration and its different types, challenges, and strategies for dealing with them.

Workflows determine how organizations conduct processes. These workflows can initially be very straightforward—just a simple series of steps that must be completed sequentially to achieve a particular outcome. However, the steps can become more complicated as business processes and requirements become more extensive. Your organization needs to keep these workflows running smoothly even as they become more complicated.

Organizations today are accumulating data more than ever. Traditional data management approaches, such as centralized data warehouses and siloed data marts, are struggling to keep pace with the ever-increasing volume, velocity, and variety of information. The complexity of modern data environments is outpacing the capabilities of these legacy systems and demands a more agile and distributed solution.

Imagine launching your software with confidence, knowing that every button click, data transfer, and user interaction works perfectly—no surprises, no last-minute bugs. This level of assurance doesn't happen by chance; it’s the result of accurate End-to-End (E2E) Testing. But what exactly does end-to-end testing mean? How does it ensure that your application not only works but grows under real-world conditions?

Ramkumar Nottath, the Senior Solutions Architect at AWS, beautifully puts it. And that’s where low-code or no-code ETL platforms can help—to make the data consumable and democratize it. In this blog, I explain low-code vs. no-code from my experience.

Does your application function as expected across the many devices your customers use? People use the same application across a wide range of gadgets, including mobile phones, smart TVs and streaming devices, gaming consoles, and desktop web apps. It’s imperative that all versions of your application work consistently and as expected across various platforms.

In 24.2, we introduced our enterprise copilot. Enterprise copilot allows you to upload business documents and collect them in knowledge sets. From there, you can ask questions about information in these documents and receive answers quickly. For instance, an organization with a heavy regulatory burden could upload legislative and operational documents. Then, these employees could get insights from Appian AI Copilot to ensure they adhere to compliance requirements.

In the field of Natural Language Processing (NLP), two prominent terms frequently arise: Small Language Models (SLMs) and Large Language Models (LLMs). While both play significant roles across various industries, including healthcare and life sciences (HC-LS), their applications and advantages diverge depending on the context and requirements of the task.