For teams building AI-driven applications with complex workflows, treating the UI layer as infrastructure can dramatically reduce friction as the product evolves. For Icanpreneur, KendoReact became that foundation.
The Telerik and Kendo UI Q2 2026 release embeds context-aware AI across UI generation, app migration, document processing and development tooling – helping teams accelerate everyday workflows across the application lifecycle.
Telerik Document Processing Libraries not only let you create RAG resources for your LLMs. They let you integrate those libraries into Microsoft’s latest agent-based tools.
This article shows .NET developers how to get started building and debugging agent-based applications locally with Microsoft Agent Framework and DevUI. The article also explores how DevUI shortens the agent development loop by providing a visual interface for running workflows and inspecting agent interactions. This can now be addressed with the Progress AI Observability Platform.
While there are numerous ways to deploy an app to Cloud Run, see how to containerize and deploy a NestJS API. We will use a few products on GCP, such as Buildpacks and Artifact Registry, to build and deploy our image, and then finally deploy it to Cloud Run.
Learn how to measure and optimize AI token spend before billing surprises hit. Discover why production AI costs diverge from estimates and how trace-level observability helps teams control LLM spending.
The RAG resources you create to use with your LLMs are strategic resources, just like your organization’s databases. Telerik Agent Tools let you create the custom tools for managing those resources.