Summary Overload
This is the wall of text pain point. It's the counter-intuitive problem where the AI, in an attempt to be "helpful," buries you in a sea of verbose text. You ask for a simple summary, and you get a 500-word essay. This signal-to-noise ratio is so low that the AI's output is actually less useful than no summary at all, as it forces the human to do the work of finding the one important sentence hidden inside a mountain of helpful fluff.
AI models are often optimized for thoroughness and completeness, not conciseness. When asked to "summarize this change" or "write documentation," the AI defaults to explaining everything—the context, the "why," the line-by-line changes, and potential future implications. It fails to distinguish between critical, need-to-know information and trivial details, producing verbose, unstructured output that obscures the key information and overwhelms the reader.
This creates a massive "cognitive load tax" on the entire team, slowing down communication and reducing its effectiveness. Important information gets lost in the noise. Reviewers skip reading PR descriptions because they are consistently too long, leading them to miss the critical context of a change. Commit logs become un-scannable and useless for debugging, as every message is a novel. This forces developers to ignore the AI's helpful text, re-creating the very information silos the AI was supposed to fix.
The Novel Commit Message
A developer uses an AI to generate a commit message for a one-line bug fix. The AI produces a three-paragraph epic detailing the bug's history, the developer's "thought process," and the philosophical implications of the fix, making the git log impossible to scan.
The TL;DR That Needs a TL;DR
You ask the AI to "summarize this pull request." It generates a summary that is literally longer than the code changes (the diff) itself, completely defeating the purpose of a summary.
The Unscannable Documentation
An AI generates "documentation" for a simple function. Instead of a clear, one-sentence description and a list of parameters, it produces a full-page, essay-style "user guide" that no developer will ever read.
The Chatty Code Comment
The AI adds a helpful comment above a function that is five lines long, while the function itself is a simple one-liner, cluttering the code and making it harder to read, not easier.
The problem isn't the AI; it's the lack of a human-in-the-loop verification and governance system. These workflows are the perfect antidote.
Communication Hygiene Guardrail
View workflow →The Pain Point It Solves
This workflow directly attacks the wall of text problem by requiring concise rationale paragraphs for AI-generated changes and enforcing structured communication patterns. Instead of allowing AI to generate verbose, unstructured output, this workflow ensures that summaries, commit messages, and documentation are concise, scannable, and focused on critical information.
Why It Works
It enforces concise communication. By requiring rationale paragraphs for AI-generated changes (limited length), enforcing structured communication patterns (bullet points, headings, TL;DR summaries), and flagging overly verbose output, this workflow ensures that AI cannot generate helpful text that actually hurts communication. This prevents the cognitive load tax, makes PR descriptions and commit logs scannable, and ensures that important information is not lost in the noise.
Professional Commit Standards
View workflow →The Pain Point It Solves
This workflow addresses the "novel commit message" problem by enforcing conventional commit format (type(scope): description) with maximum 50-character descriptions and requiring clear, concise commit messages. Instead of allowing AI to generate epic commit messages, this workflow ensures that commit logs are scannable and useful for debugging.
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Engineering Leader & AI Guardrails Leader. Creator of Engify.ai, helping teams operationalize AI through structured workflows and guardrails based on real production incidents.