IT Strategy | News, how-tos, features, reviews, and videos
Why the rush to replace developers with LLMs is leaving companies with brittle systems, runaway cloud bills, and a painful rebuild.
Developers aren’t waiting while leadership dithers over a standardized, official AI platform. Better to treat a platform as a set of services or composable APIs to guide developer innovation.
Startups that embrace AI are unlocking growth like never before — smarter, faster and ready to take on the world.
The motivations, complexities, and steps toward European cloud independence run up against enterprise multicloud strategy.
Specialized cloud solutions continue to drive multicloud adoption as AI requirements and compliance regulations grow.
The surest way to value with AI is to use the tools that leverage your organization’s hard-won expertise and that integrate with the systems you have now.
Engineering fundamentals aren’t just for computer science students. They pay huge dividends in both your systems’ service levels and your company’s balance sheet.
Large cloud commitments tempt companies with their promises of deep discounts, but they come with hidden costs that may be a mistake for your business.
The big providers spend a lot on artificial intelligence, but they are not offering the things enterprises care about most. Here are the important questions to ask.
Consider these six ways to approach AI to help your organization unlock efficiencies while preventing major setbacks and significant cost overruns.
Big cloud brands are using nonexistent AGI as a marketing gimmick to boost interest in their cloud offerings.
In this issue: Cloud computing is highly established, and IT’s view has shifted from understanding the concept to making the best use of it to solve both technology and business challenges. The time is ripe to step back and revisit your thinking about the cloud.
High cloud costs rooted in insufficient training and inadequate architectural oversight use up money that could go to innovation or new markets.