Systems | Development | Analytics | API | Testing

The Truth About AI Web Development and Dev Productivity

Can AI solve the PHP talent shortage — or does it introduce new challenges? In this clip from a recent Zend webinar, “The 2026 State of PHP,” PHP experts Matthew Weier O’Phinney and Adam Culp explore how AI web development is changing the way teams modernize applications, and why AI alone isn’t the answer. AI is already accelerating development workflows, helping teams generate code, document processes, and move faster through modernization projects. But when it comes to replacing skilled engineers, the reality is more nuanced.

What Is a Context Graph and Why Does AI Need One?

The context graph — not the UI layer or system of record — is the true competitive IP of the AI era, and Kong built Context Mesh to help companies govern it. Without the right context layer, AI agents are generic and interchangeable regardless of which LLM is underneath. Companies that own and protect their context graph can differentiate their agentic workflows; those that don't are left with legacy CRUD backends that don't translate to agentic use cases. Context Mesh gives enterprises policy and governance over what agents can consume — the rulebook for all context flowing in and out.#Shorts.

How to scale AI test automation without losing test visibility

According to SmartBear’s Closing the AI Software Quality Gap study, 93% of teams are already using AI to generate code. The same study found that 60% expect AI to produce nearly half of all code within the next year. This shift in development velocity is already impacting software testing and quality. Most teams say application quality is suffering, and 60% have experienced quality issues in the past year because development is moving faster than testing can keep up.

AI-Powered Personalization in Retail Banking: How Banks Can Deliver Hyper-Personalized Experiences at Scale

Retail banking is quietly undergoing one of its biggest shifts in decades. Customers no longer compare banks to other banks. They compare them to Netflix, Amazon, and every digital experience that already gets them. That expectation has changed the game. This is where AI-powered personalization in retail banking comes in. Instead of offering generic products to broad customer segments, banks can now deliver hyper-relevant experiences in real time.