Systems | Development | Analytics | API | Testing

The Real Reason Your AI Project Is Stuck in Pilot Mode

Ever wonder why so many enterprise AI projects never make it past the pilot stage? It’s not the AI—it’s the foundation. In this video, we break down why rushing into complex models without fixing inconsistent data, fragile pipelines, and afterthought governance is a recipe for failure. Fix the basics first!

Brand an Embedded Analytics App in Minutes with AI Theme Builder

It's the day before your POC, and the embedded analytics demo still looks like it belongs to someone else. Your designer handed over a brand guide last week. Your developer has been buried in CSS variables ever since: cross-referencing token names, mapping changes across components, reloading the page after every tweak to see what broke. The UI is almost right. The nav color is close. The typography still isn't matching, but there's no time left.

Ship iOS and Android builds twice as fast on GitHub Actions

Last year, Nathan Hillyer's iOS platform engineering team at ForeFlight had self-hosted Mac hardware in their office, two engineers keeping them alive, and a codebase with over 2 million lines of Objective-C, Swift, and C++. Every Xcode update was a fire drill. Every capacity spike during a merge meant somebody was physically racking hardware in the Austin office. ForeFlight didn't want a new CI system. They wanted to stop being a data centre.

AI agent streaming in action: barge-in, human handover, and session continuity

You're mid-conversation with an AI support agent. You've explained the problem, the agent is halfway through a response, and the connection drops. When you reconnect, the response is gone. You type the same question again. The agent asks the same clarifying questions again. Three minutes of context, gone. Not because the model forgot it, but because the delivery layer stored nothing.