End-user programmers, who lack formal training and understanding of AI, represent a large user base that could greatly benefit from large language models (LLMs). While professional programmers understand the limitations of AI-generated code, end-users such as accountants or journalists could leverage AI for their needs without acquiring deep programming knowledge. However, challenges arise in areas like intent specification, code correctness, quality assurance, and the automation's impact on end-user programming practices. Existing metaphors of AI assistance do not fully encompass the distinct challenges faced by these users.
End-user programmers, including accountants and journalists, often lack programming skills yet stand to gain significantly from the assistance offered by AI and LLMs.
The challenges of using large language models in programming applications involve issues like intent specification, code correctness, and the consequences of automation.
Existing metaphors for AI-assisted programming, such as search and pair programming, fall short in fully capturing the distinct nature of programming with AI.
Writing effective prompts for AI tools remains a complex challenge, and programming activities are shifting towards verification and debugging of AI-generated code.
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