Insights on Mobile Development, UX Design, and Digital Innovation
SubscribeFor the past three years, "AI strategy" mostly meant "which API do we call." That's changing. A growing number of product and engineering teams are pulling specific AI workloads out of the cloud and running them directly on the user's device.
Across 1.2 million plans, we watched users trust the AI enough to book and watched them quietly abandon good itineraries for reasons that had nothing to do with itinerary quality. This article is about what separated the two.
We built a booking platform for a client operating in two markets. The core logic, search, availability, and reservations, worked fine. Launch in market one went smoothly. Then came market two, and things started breaking in places we hadn't looked.
Previously, we shared how to integrate a local LLM into a Flutter app. Today, we will add the RAG to the equation.
Claude Opus 4.6 scored 80.84% on SWE-bench Verified in February 2026: the benchmark that measures whether a model can actually fix real GitHub issues. That number matters because it's the point where repo-wide refactoring stops being a party trick and starts being something you can ship with.
By 2026, this has shifted AI tools integrated into modern development workflows, such as Cursor GitHub Copilot and LLM agents have introduced a third option, the hybrid model, combining professional developers with AI.
Base44 is one of the most talked-about vibe-coding tools right now. You describe what you want, and it generates a working web app: database, UI, and logic included. For the right use case, it’s genuinely impressive.
