Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

SDLC guides teams to plan, build, test, and deliver software. Discover phases, KPIs, tools, and checklist with our quick start guide. Picture this: You and your team have spent a tremendous amount of ...

Implementing agentic software engineering requires more than connecting an AI model to your repositories—it starts by ...

Considering the scaling history and trajectory of generative AI models (specifically large language models, or LLMs) specialized for coding, the software development life cycle (SDLC) is ripe for ...

This article was co-authored by Dr. Anand Nayyar, professor and vice chairman (research) from Duy Tan University, Vietnam. The emergence of artificial intelligence (AI) has fundamentally reshaped ...

There are mountains of articles on the various software development life cycle methodologies, but nothing beats personal experience. While there may be no single SDLC methodology that fits all ...

As of 2025, integrating Artificial Intelligence is no longer a futuristic ambition but a core business function. However, many organizations are discovering a painful truth: forcing AI projects into a ...

Code generation and copilots are just the beginning of new AI-enabled ways to develop, test, deploy, and maintain software. Coding in the 1990s usually meant selecting an editor, checking code into ...

Security is a key consideration when it comes to platform engineering, which is the next step in the evolution of DevOps. Platform engineering is a discipline for designing, building and maintaining ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...