DSLs Enable Reliable Use of LLMs
The author argues that Domain-Specific Languages (DSLs) act as a necessary constraint for LLMs to generate reliable code. By using DSLs as a source of truth, developers can iteratively refine system designs while maintaining clear boundaries for AI-generated output.
Why it matters
It addresses the challenge of 'hallucination' and lack of precision in AI-generated software systems.
LLMs generate code incredibly fast, but to ensure they generate exactly what is intended, they need clear boundaries. Abstractions and Domain-Specific Languages (DSLs) provide a strong harness that guides LLMs right from the start. The example of Tickloom - a domain model and DSL for illustrating distributed system behavior - shows how we can use an LLM as a partner to iteratively build a DSL and as a natural language interface to use it. Such a DSL can act as the key source of truth for software systems in the world of LLMs.
The article presents a technical architectural opinion without ideological bias.
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