Systems | Development | Analytics | API | Testing

Why API Security Is Foundational to AI Security (Akamai Study)

Secure AI starts with securing the APIs underneath it. This session breaks down why APIs and MCPs are the control plane for AI apps and agents, where unmanaged API risk hides, and how security and platform teams can improve visibility, posture, runtime protection, and governance across production environments. KEY TAKEAWAYS TIMESTAMPS.

SwiftUI PhotosPicker Tutorial: Let Users Pick a Photo #Shorts #swiftui #swiftuitutorial

SwiftUI PhotosPicker tutorial: how to let people choose a photo in SwiftUI with PhotosPicker from PhotosUI, load it with loadTransferable(type:), and handle and log the errors when loading fails. PhotosPicker opens the system photo picker. People choose a photo, and your app gets only the items they pick. This Short shows the whole flow in a real iPhone app in the iOS Simulator, with the exact code.

Best App Deployment Platforms in 2026: Which One to Pick for Your App #Shorts #appdeployment #coding

Best app deployment platforms in 2026: the right one depends on what you ship. Here is the short list by use case, with the free-tier changes that make older lists out of date. THE SHORT LIST Frontend apps: Vercel or Netlify. Every Git push gets its own preview link. Full-stack apps and APIs: Render or Railway, with databases next to your app. Mobile backend: Firebase, with auth, real-time data and hosting. Already on AWS or Google Cloud: AWS Amplify or Google Cloud Run. Static sites: GitHub Pages and Cloudflare Pages host them for free.

Nobody Wants Your New AI Agent #devops #aiagents #softwaredevelopment #techtrends #ai

DevOps customers are rejecting standalone AI agents and web interfaces in favor of integrating context directly into their existing harnesses, such as Copilot or Claude. Rather than logging into separate tools, developers prefer combining models and technologies within a single context window to streamline software development and debugging. Learn more: speedscale.com.

Building With ARIA: From Plain English to EDI Flows

ARIA is an AI Agent that has full knowledge of the Astera ecosystem. Sudais (Growth Strategist) sits down with Hasham Qazi (AI Product Specialist), to talk about why, and how that single agent, ARIA, builds data flows, workflows, and EDI pipelines from plain-language prompts. Hasham walks through a real use case, building an EDI flow from a file you hand to the agent, and explains what ARIA does when your prompt has gaps, how it checks its own work, and where it's heading next.

AI at Scale: Why Trust, Not the Model, Decides Who Wins

Every AI conversation eventually turns into a model conversation: which one is fastest, which one hallucinates least, which one your competitors are already using. Three recent episodes of The Data and AI Chief, hosted by ThoughtSpot's Chief Data and AI Strategy Officer Cindi Howson, make a different case entirely about what it takes to scale AI in the enterprise.

Performance Considerations with Offset and Cursor Pagination in Plain PHP and Doctrine ORM

Displaying a list of items from the database is probably the most common functionality built for web applications. This is where pagination with LIMIT clause comes into play, which is most likely what you learned to use. This pattern is called offset pagination. In this post I am going to contrast it with cursor pagination and the performance considerations that come with the choice of pagination algorithm. Examples are with Plain PHP and Doctrine ORM 3.7, which ships a new CursorPaginator class.

AI-Native CI/CD Testing: Building Reliable Release Pipelines for AI Applications

Traditional CI/CD pipelines relied on determinism, assuming code produced an exact, repeatable output. Generative models and agentic workflows break this model. A single prompt edit or model checkpoint update can pass standard unit tests while causing silent regressions like truncated API payloads or missing parameters five steps downstream. To ship probabilistic AI reliably, engineering teams must redefine what counts as a passing test.

Structured Logging: A Complete Guide with Examples

Plain-text logs are great if you want a simple explanation of how a function is performing or why a crash happened. But as your application grows, they become difficult to search and analyze. Structured logging makes production data easier to filter, correlate, and use across modern logging tools. This guide will give you the springboard to build structured logs effectively, showing you how to.