Intent Formalization: A Grand Challenge for Reliable Coding in the Age of AI Agents
Agentic AI systems can now generate code with remarkable fluency, but a fundamental question remains: \emph{does the generated code actually do what the user intended?} The gap between informal natural language requirements and precise program behavior -- the \emph{intent gap} -- has always plagued software engineering, but AI-generated code amplifies it to an unprecedented scale. This article argues that \textbf{intent formalization} -- the translation of informal user intent into a set of checkable formal specifications -- is the key challenge that will determine whether AI makes software more reliable or merely more abundant. Intent formalization offers a tradeoff spectrum suitable to ...
| Authors | Shuvendu K. Lahiri |
|---|---|
| Primary category | cs.SE |
| Published | 17 March 2026 |
| Last updated at source | 17 March 2026 |
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