Isaac Sacolick

A cloud outage is a bigger problem if you don't learn from it. Increasing cloud failures are exposing critical weaknesses in enterprise architecture. Here are 3 things to do about it.

Creating data products is a good way to accelerate delivery, reuse data assets, reduce risks, and manage costs. Standardized data products can also help improve analytics and AI capabilities.

AI capabilities allow models to reason about a 3D space in the physical world. Inspecting bridges, creating digital twins, and making self-driving cars safer are just a few uses, but many different industries can find uses for these technologies.

Major tech vendors' strategies, products, and conference agendas paint a varying picture of agentic's enterprise impact — and what CIOs should consider when evaluating AI agents for the workplace.

The “pay for outcomes” deal is a risk transfer unless you can govern it.

Don't rush to replace older software with AI; legacy apps still run the world, and sometimes it's smarter to just add AI into your existing workflows.

If a predictable event like the World Cup still breaks your workflow, it's a sign your business data is too siloed to let your team adapt in real time.

New AI tools are giving SREs better ways to manage outages and problems, while at the same time AI-generated code increases the problems SREs must face.

As enterprises depend more and more on AI agents and automations, having a reliable orchestration layer above keeps workflows moving smoothly.

Agents need fast, fresh, real-world data to stay grounded and avoid errors. Microsoft's new grounding service helps solve this problem.