To discuss the role of AI in software architecture, we have to think about the whole process, not just code generation or creating documentation like architectural diagrams. We all know that AI has gotten quite good at generating code. There are people experimenting with using AI to UML and C4 diagrams. AI will definitely play a role here. But I don't expect AI to have much of an impact on the rest of the process, which involves understanding and negotiating all of those human issues ...

In case you missed it, Kubernetes turned ten this summer. It's the perfect opportunity to reflect on how far cloud-native has come, and what the next ten years might hold. So to commemorate the occasion, here are ten top findings from Spectro Cloud's new 2024 State of Production Kubernetes report ...

The state of application development in 2024 shows further trends toward cloud development, open source, microservices and AI/ML integration according to the 2024 State of Application Development Report from Docker ...

While SaaS giants have been quick to proclaim new AI features along their existing products, are these new capabilities actually going to provide value? The AI experiences they're promising need to fit into their already complex user experience ... Here are three concepts you should be integrating into your roadmap if you're aiming to disrupt the SaaS space with AI ...

Generative AI (GenAI) is a clear priority for organizations — a survey conducted by Couchbase of 500 IT decision makers found that almost all respondents have specific goals to use it in 2024. As organizations prepare for GenAI's rapid growth, they are facing critical questions ...

A recent survey from Tricentis found that high-quality mobile apps can improve just about every aspect of a company's standing including enhanced end-user experience, increased brand value and sales, improved company competitiveness, and bolstered customer retention and acquisition ...

The failure to keep pace with AI-assisted workflows, the "AI Skill Threat," has created fear among developers that their skills will become obsolete as they adapt to AI-assisted coding. To overcome this uncertainty, developers need strategic upskilling ...

As organizations increasingly harness artificial intelligence (AI) to power various functions, the integrity, security, and reliability of the data inputted into these systems become paramount. This approach is fundamental in avoiding pitfalls during model training, a challenge commonly recognized by AI developers ...

We've been monitoring perceptions of Artificial intelligence (AI) for over a decade and early on we hypothesized that developers might be skeptical and have a difficult time trusting AI. We were wrong ...

As companies grapple with the rapid integration of AI into web applications, questions of risk mitigation and security are top of mind. AI-infused coding and secure defaults offer the potential for improved security, but organizations are still challenged with practical steps beyond just writing intent into policies and procedures. Further there are unique challenges with consumer-facing models not related to work, but something that must be managed as part of the growing attack surface ...

Software developers probably don't need to worry as much as they think about GenAI taking their jobs. But they do need to think twice about which language model they use. In fact, the Large Language Model (LLM) space is seeing something of a code generation arms race. How do you know which one's right for you? ...

The personality types you often encounter in software development organizations can be divided into two basic categories: poets and librarians. Poets are the creative types who dream up big ideas. Librarians make sure high-quality code gets built on time. Their goals and motivations differ, but great software results when they work together harmoniously ...