• •Lex, a technical writer, documented instances where LLM tools altered file structures during automated editing tasks.
• •The analysis confirmed that LLMs can inadvertently strip essential metadata or break encoding standards in complex document formats.
• •It remains unclear whether these errors stem from systemic model hallucination or specific limitations in the API integrations used to bridge the LLM and the document software.

Lex reports that delegating document editing tasks to LLMs frequently results in unintended file corruption. Unlike human editors who respect formatting constraints, automated agents often misinterpret technical syntax, leading to broken files. This friction between generative capability and data integrity creates a hurdle for workflows that require strictly preserved document structures. Until developers implement more robust schema-validation layers, widespread adoption of LLMs for document management remains risky for technical files.