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Building an SDK developers love: Best practices for AI integrations and customization
Building an SDK that’s both deeply customizable and easy to integrate is one of the toughest challenges facing developer teams today. In this session, we’ll share the core principles we used to design the Beefree SDK and our Custom LLM AddOn—showing how to balance flexibility, usability, and modular design without overwhelming developers. By the end, you’ll walk away with practical strategies for creating extensible, developer-friendly SDKs that scale.
February 11th, 2025
Creating an SDK that is both deeply customizable and effortless to integrate is one of the biggest challenges in modern developer experience, especially as AI development pushes teams to support faster, more flexible workflows. In this session, we walk through the principles behind building scalable, AI ready SDKs using real lessons from the Beefree SDK and our Custom LLM AddOn. You learn how to offer powerful extensibility without introducing complexity that slows developers down.
We explore how to design intuitive interfaces, improve communication between the SDK and the host application, and validate the right features through meaningful user feedback. You also see how documentation and early customer involvement dramatically improve adoption.
Key topics include
• How to balance customization with simplicity
• When to use tools like the Content Dialog interface and Callbacks to improve user interactions
• Proven ways to build dynamic and adaptable SDK architectures
• Why early user feedback prevents missed opportunities
• How clear documentation accelerates adoption
• Lessons learned from building the Custom LLM AddOn and supporting enterprise AI needs
By the end of the session, you have a stronger understanding of how to design SDKs that deliver flexibility, scale safely, and keep developers focused on building great products.
