Pre-recorded session.
Modern LLMs are remarkably good at generating code. However, the real challenge is not generating individual components, but building deterministic business applications. While AI models are inherently probabilistic, applications need to be reproducible, predictable, and reliable.
In this talk, I present an approach in which natural language is not translated directly into Angular code, but into a declarative DSL. This DSL describes forms, and is interpreted deterministically by a runtime built on Angular Signal Forms.
Instead of generating code, this approach creates deterministic applications that can be described declaratively, validated, and continuously evolved. The talk demonstrates how a declarative DSL can bridge the gap between probabilistic AI and deterministic business applications.
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