Systems | Development | Analytics | API | Testing

At Qlik Connect, one of the big messages we’re putting in front of customers is this: you’re closer to agentic AI than you think. I believe that because a lot of our customers already have more of the foundation in place than they may realize. If you have been working to improve data quality, strengthen governance, connect data across the business, and move analytics beyond reporting into real decision support, you are already building the conditions agentic AI needs to deliver value.

“The data integration landscape is currently undergoing a seismic shift. We are moving away from an era of human-led data pipelines and entering the age of Agentic Data Management.

APIs are bits of software that act as interpreters for two different programs. They'll connect to each service via endpoints and relay messages back and forth, doing the work of software integration for you. DreamFactory is a secure, self-hosted enterprise data access platform that provides governed API access to any data source, connecting enterprise applications and on-prem LLMs with role-based access and identity passthrough. But how does this actually look in the real world?

Choosing the wrong date-time API can seriously snarl up your Kotlin app. Timezone mismatches, formatting bugs, inconsistent timestamps – all of them can seriously drain your time and they’re hard to trace without the right tooling. Kotlin gives you multiple date-time tools – LocalDate, Instant, DateTimeFormatter, and kotlinx-datetime – but each is designed for a specific use case across Android, server-side, and multiplatform projects.

Sending money today feels effortless. But pause for a second, when was the last time you used cash for a transfer or stood in a queue for a wire transfer? Exactly. Digital remittances and peer-to-peer payments are growing at an incredible pace across the globe. What used to take hours or even days, with high fees and multiple intermediaries, now happens in seconds. Cross-border transfers, splitting bills, paying freelancers, everything has shifted to real-time, mobile-first experiences.

When testing debt piles up, it creates a quality ceiling that effectively stops your release velocity, regardless of how many developers you hire.

You whipped up a simple MCP server prototype over the weekend. It routed a single AI agent to a few internal tools, your demo impressed leadership, and the team asked the dreaded question: "When can we ship?" You smiled and said, "Give me two weeks." Fast-forward three months**.** You’re firefighting expired tokens at 2 AM. The compliance team is camped in your inbox. Your once-elegant codebase is now a distributed systems nightmare. Sound familiar?

Agentic AI puts new pressure on data access, making architectural flexibility and control more important than ever.

One of the things I have learned spending time with enterprise data and analytics teams is that insight without proximity to action is only half the job. You can build a beautiful dashboard, surface a critical pattern, or flag a risk in real time, and still have the insight die on a slide before it ever changes what happens next. The gap between "we know this" and "we did something about it" is one of the most persistent problems in enterprise software.