Isaac Sacolick

How can enterprise devops teams improve the resiliency of their mission-critical apps, integrations, and data pipelines? Look to the practices of SaaS providers.

Caught in the elevator with an inquisitive CEO or board member? Emphasizing the business's primary objectives, growth targets, and operational goals is vital to making a strong future-leader impression.

Platforms embedded in industry workflows will prove more challenging to replace than many assume.

As technology and regulations evolve, enterprises need to address data governance throughout pipelines, models, and AI agents. AI can help.

AI projects can often feel insurmountable due to the time and effort involved to move them into production. Here are five recommendations to help CIOs and their teams reach the summit.

Whether they are competing approaches or complementary, there are good ways to incorporate both these AI-based methods into developing resilient applications.

Now is the perfect time to develop skills, research new security protocols, and experiment with potential use cases.

AI doesn’t scale on models alone. It requires the same focus on infrastructure, shared open-source standards and systems that defined the cloud.

AI is a necessary bet, but most organizations are sleeping on a new class of technologies. How will you tap into their power?

With access to many different types of data fabrics, companies big and small can use them to provide AI agents with wide access to data sources, unstructured data, shared business context, and guardrails.