Systems | Development | Analytics | API | Testing

Credit used to be a destination. You went to a bank, filled out forms, waited days, sometimes weeks, and hoped for approval. That model is quietly disappearing. Today, credit shows up exactly where you need it. While shopping online. While booking logistics. Even while managing business cash flow inside a SaaS dashboard. No redirects. No friction. No traditional loan journey. This shift is what we call Embedded Lending. It is not just a feature.

Mobile-first businesses often enter the market confident in their app’s speed, but the reality is that many overestimate their performance – and pay for it through user churn and lost revenue. With 5.78 billion unique mobile users worldwide as of October 2025, representing 70.1% of the global population, the pressure to deliver a fast, reliable experience is immense.

In an API-driven setup, a gateway often sits between clients and backend services: it can validate input, aggregate upstream responses, and give you one place to observe traffic. Koa is a strong fit for that role. Its core stays small, async/await is first-class, and middleware composes in a predictable stack. In this article, you will build a compact API gateway with Koa that: You will also wire up AppSignal for the Node.js stack.

While AI accelerates development velocity by a factor of ten, a critical consequence remains: testing hasn’t kept pace. According to SmartBear research, 70% of software professionals report that their application quality has already degraded due to AI-accelerated development. Even more concerning, 60% have experienced quality issues in the past year as development velocity outstrips testing capacity.

Since its debut in June 2023, SwiftData has fundamentally changed how Apple developers approach persistence. Devs the world over love it for its versatility, its declarative ease and its powerful querying system. But if you’re new, SwiftData can take some getting used to. Failures can feel less transparent and relationships can play out differently to how you might expect. So in this tutorial we’ll show you how SwiftData works and how to.

Last updated: May 2026 An Oracle MCP server is a service that exposes Oracle Database data as tools an AI agent can call through the Model Context Protocol (MCP). Rather than handing an LLM direct credentials to a database holding ERP, financial, or healthcare records, you put an MCP server between the agent and Oracle.

Last updated: May 2026 A Snowflake MCP server is a service that exposes Snowflake warehouses as tools an AI agent can call through the Model Context Protocol (MCP). It sits between AI clients like Claude or ChatGPT and your Snowflake data, translating discoverable tool calls into governed SQL — with row access policies, dynamic data masking, query budgets, and audit logging applied automatically.

It's easy to get caught up in the AI hype, but excitement can stop us from seeing the practical steps needed to make AI truly work. At Appian, we recognize that AI is at its most powerful within a process. Before you get to embedding AI in process, however, you must determine if AI is what you need.

“Garbage in, garbage out.” We are not the ones who said this, George Fuechsel did. But when we are talking about AI today, it is hard not to repeat it. We spend a lot of time discussing what AI can do, the outputs, the predictions, the impact it can create. Much less attention goes to what is actually going into these systems.

The challenge of any aerospace company is to deliver new capabilities without compromising safety, reliability, or precision. At our current juncture, legacy technology runs into conflict with modern tool stacks. Artificial intelligence (AI) creates fissures in compliance and auditability, and innovation and productivity gains come at a cost of greater complexity. Despite these seismic shifts, the central question remains the same.