The AI credential revolution: A guide for IT professionals and business leaders.

Artificial intelligence is rapidly changing how enterprise applications are designed, but many organizations still struggle with a familiar problem: translating business requirements into working software. In this episode of DEMO, Pega CTO Don Schuerman introduces Blueprint, a design-time AI capability that aims to close that gap by turning workflow ideas into functional applications in minutes.

The hyperscalers were quick to support AI agents and the Model Context Protocol. Use these official MCP servers from the major cloud providers to automate your cloud operations.

Is the data center building boom driven by competitive signaling or real demand? If adoption falls short, today’s boom will bring tomorrow’s bust.

There is probably a more direct route from AI models to the software we want than having agents work with code.

How does CPython’s new native-JIT compiler stack up against PyPy? We ran side-by-side benchmarks to find out, and the answers may surprise you.

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with projects that support AI development.

Smaller models, lightweight frameworks, specialized hardware, and other innovations are bringing AI out of the cloud and into clients, servers, and devices on the edge of the network.

By releasing the code behind its search and vector engine under the SSPL, MongoDB is giving self‑managed users new visibility and control, helping developers build more reliable, production‑grade RAG ...

If the big bottleneck in your Rust development workflow is compile time, there are at least five ways you can fix it.

Databricks says Instructed Retrieval outperforms RAG and could move AI pilots to production faster, but analysts warn it could expose data, governance, and budget gaps that CIOs can’t ignore.

Developed using Anthropic’s Claude AI model, the new language is intended to provide memory safety without garbage collection while being easier to use than Rust and Zig.

Progress towards full AI-driven coding automation continues, but in steps rather than leaps, giving organizations time to prepare.

The acquisition could help enterprises push analytics and AI projects into production faster while acting as the missing autonomy layer that connects Fabric’s recent enhancements into a coherent syste...

In a new model for user interfaces, agents paint the screen with interactive UI components on demand. Let’s take a look.

Ruby Box is an experimental feature that provides separate spaces in a Ruby process to isolate application code, libraries, and monkey patches.

Google Cloud’s lead engineer for databases discusses the challenges of integrating databases and LLMs, the tools needed to overcome these challenges, and how AI-native databases will help bridge the g...

Latest update to the Node.js rival also brings more granular control over permissions and a faster, experimental type checker.

With something for everyone—whether you love the command-line or hate it—AI-powered shells have arrived.

The native just-in-time compiler in Python 3.15 can speed up code by as much as 20% or more, although it’s still experimental.

Marketing hype is calling everything an agent, but mislabeling automations or souped-up chatbots as agents is a governance failure waiting to happen.

Your enterprise may be more locked into a vendor’s AI than you realize, thanks to AI-native features in services you’re already using.

Start winding down the year with our picks from the most-read generative AI features and tutorials of 2025.

The best defense against prompt injection and other AI attacks is to do some basic engineering, test more, and not rely on AI to protect you.