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Remember when Jarvis ran Tony Stark’s entire life and helped him build a high-tech Iron Man suit? That’s pretty much AI in eCommerce now, but instead of building suits, it’s building smarter stores and smoother shopping experiences. While most people are still stuck using AI to write basic product descriptions or churn out ad copy, the real power of artificial intelligence in commerce lies under the hood.

Government organizations are under increasing pressure to act with agility, collaborate across departments, and make fast, data-driven decisions. In the defense sector, these challenges are heightened by the need to unify complex functions in support of national security. Internal processes must be as effective and responsive as the forces they serve.

If you’ve been on the fence about trying the Ash Framework, this post is for you. We’re going to explore why Ash is a game changer for Elixir developers by building something complex, real, but surprisingly elegant. We’ll create AshTherapy, an AI-powered therapeutic chat service that handles conversations, messages, and user interactions — all powered by Ash. Before we go further, let’s first answer the question: what exactly is Ash?

Scaling REST APIs for databases with heavy traffic requires careful planning to ensure fast, reliable performance. Here’s the gist: -Stateless Design: APIs should process requests independently, enabling horizontal scaling and efficient load balancing. -Caching: Use client-side, server-side, and CDN caching to reduce database strain and improve response times. -Optimized Queries: Fine-tune database queries, use indexes, and implement pagination to handle large datasets effectively.

Europe’s transition to electric vehicles (EVs) is gearing up and one car maker is leading the charge. The Volkswagen Group recently eclipsed Tesla as Europe’s top EV maker, with deliveries surging a stunning 89% year on year to 347,900 vehicles. But it’s too early to celebrate yet, with the EU’s 2035 ban on new petrol and diesel cars looming large, keeping adoption moving is crucial. That’s where Elli, Volkswagen Group’s charging and energy company, comes in.

Most companies talk about being “AI-first.” At Ably, we decided to actually become one. We build realtime infrastructure for AI applications. To do that credibly, we need to live and breathe AI ourselves – not just in our product, but in how we work every day. Two years ago, we began a company-wide push for AI adoption.

When you’re building realtime systems, blind spots slow you down. The new dashboard gives developers self-serve visibility into everything happening inside their apps, from high-level usage to individual connections, channels and messages. No setup. No external tools. Just open your browser and observe your data in motion.

Why “standalone AI” falls short AI works best when embedded in a process Guardrails are not a limitation—they’re an enabler Process-driven AI in action How leaders should be thinking about AI now Artificial intelligence is no longer optional in state and local government—it’s essential for meeting public expectations amid staffing shortages and budget constraints. AI is showing up across agencies and programs.

In one of our posts, Kong AI/MCP Gateway and Kong MCP Server technical breakdown, we described the new capabilities added to Kong AI Gateway to support MCP (Model Context Protocol). The post focused exclusively on consuming MCP server and MCP tools through Kong MCP Gateway. Now, it's time to check how an AI agent can leverage the AI and MCP infrastructure exposed and protected by Kong AI/MCP Gateway.

Enterprises have invested decades of development effort into SQL Server stored procedures. These procedures contain critical business logic—validation rules, complex calculations, transaction handling, reporting queries—that applications need to access. But stored procedures weren't designed for modern API-driven architectures.