The first wave of Gen AI in software engineering has been dominated by coding assistants. But coding is only one part of the product development lifecycle. A team can produce more code and still move slowly because of unclear requirements,…
Software engineering ran on pure adrenaline over the last decade. Everyone rushed to split up monoliths, automate builds, and run endless agile cycles. Then AI tools showed up with a simple promise—multiply your code output by ten. Fast-forward to today:…
A few years ago, the board of directors at a global financial institution reviewed the outcomes of a massive technology initiative. The enterprise had spent eighteen months rolling out AI coding assistants to over four thousand software developers. The project…
AI won’t fix broken DevOps. But it will expose it.For years, DevOps has promised us the ultimate trifecta: faster releases, seamless collaboration, and rock-solid software. Naturally, organizations bought in. They poured massive budgets into CI/CD pipelines, embraced infrastructure as code,…
We are currently living through one of the greatest misdirection in the history of software engineering.When generative AI first broke into the mainstream, the entire industry hyper-focused on a single, simplistic question: How much faster can a developer type code?Wall…
Artificial intelligence has changed software development faster than almost any technology shift in the past decade. What started with AI code completion has evolved into AI-powered code generation, automated testing, documentation, and debugging. Developers today can generate boilerplate code in…
The software engineering landscape is experiencing a profound structural dislocation. For decades, technology leaders leaned on quantifiable metrics to measure the output of engineering teams. They relied heavily on lines of code generated, pull request counts, or basic sprint velocity.…
Modern software engineering is evolving beyond code creation to become a discipline driven by data, intelligence, automation, and continuous optimization. For years, most teams were judged by the visible part of software work: what made it out the door. A feature was launched,…
IntroductionThe boardroom conversation around technology has officially fractured.But pull back from the metrics for a second, and a completely different reality corporate leaders face comes to light.For the past few years, the mandate delivered to CIOs and CTOs across major industries…
By Vikas BasraIn the race to deliver software faster and more reliably, enterprises are seeking tools that go beyond automation to truly amplify engineering impact. ATONIS™, the AI-powered engineering workbench from Ness, delivers exactly that: measurable outcomes grounded in real…