At EnPowered, Mike Kirkup ended up running the financing arm, manually collecting and validating documents... until he couldn’t take it anymore.

The internal tooling he built became Arlo, a product now used by lenders to automate and augment document workflows with AI.

In this episode, Daniel and Mike talk about what makes using AI different from old school automation. Yes, Arlo automates mundane tasks, but it also asks follow-up questions and flags mismatches humans miss.

Mike explains how Arlo became goal-oriented rather than rules-based. That shift not only made the AI smarter, it pushed users to rethink what they were actually trying to accomplish and how they were doing it.

Listen in to learn about how to truly be AI-first when designing solutions, building trust in AI despite its unpredictability, and how a simple question—“Why do you even ask for that document?”—can change how a whole industry works.

🔑 What You’ll Learn in This Episode:

• ✅ What it's like to demo AI that asks unpredictable questions
• ✅ The courage it takes to give AI more room to operate
• ✅ How AI nudges companies to reexamine outdated workflows
• ✅ Why domain expertise is critical to building useful AI tools
• ✅ Why you shouldn't get a PhD to break into AI

🔗 Resources & Links:

• 🤝 Connect with Mike on LinkedIn
• 📓 Learn more about Arlo
• 📩 Subscribe to the Artificial Insights newsletter for summaries and takeaways

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