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AI documentation systems fail to preserve the 'why' behind decisions

The author argues that current documentation practices, while preserving individual artifacts like Jira tickets or Git commits, fail to capture the crucial "why" behind decisions. These explanations are often distributed across various communication channels and historical artifacts, residing primarily in human memory. The piece suggests a shift from simply asking "Did we document this?" to "Will someone understand the context and relationships of this document in the future?", emphasizing that true organizational memory lies in preserving the relationships between documents, not just the documents themselves. AI

IMPACT Suggests a need for new tools or approaches to capture the 'why' behind technical decisions, moving beyond simple document preservation.

RANK_REASON The item is an opinion piece discussing the limitations of current documentation practices and proposing a new approach to organizational memory.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI documentation systems fail to preserve the 'why' behind decisions

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · ValeryKot ·

    We Back Up Files. We Rarely Back Up Why They Exist.

    <p><em>Everything survived. Except the explanation.</em></p> <p>A while ago I was trying to understand why one of our services used Redis.</p> <p>Finding the artifacts wasn't difficult.</p> <p>There was a Jira ticket.</p> <p>A pull request.</p> <p>An architecture document.</p> <p…