DSLs enable reliable use of LLMs
Strong articulation of a recurring pattern in good AI engineering: move effort from reviewing arbitrary generated code toward building better vocabularies, abstractions, and validators that make generation reliable by construction.
Logged at IST: 2026-07-14 20:54 IST
What it is: Martin Fowler sharing Unmesh Joshi’s article on DSLs and LLM reliability
Gist: The article’s core claim is that LLMs become much more reliable when they are constrained by domain abstractions and DSLs instead of being asked to directly generate unconstrained general-purpose code. The deeper point is that DSLs do double duty: they help teams discover and stabilize a semantic model during design, and then they become a natural-language target that LLMs can generate against, validate, and repair with much tighter feedback loops.
Newsletter angle: Strong articulation of a recurring pattern in good AI engineering: move effort from reviewing arbitrary generated code toward building better vocabularies, abstractions, and validators that make generation reliable by construction.