AI-Assisted Workflows · Discussion

AI-Assisted Reviewing

As of this writing (2026). AI tool behavior changes quickly — revisit this page periodically rather than treating it as permanent guidance.

Definition

Generative AI tools are exceptionally good at summarizing content, especially when there’s enough similar material in their training data to draw on. That makes an AI-generated summary a useful starting point for a review — including reviewing your own writing — as long as it’s applied through the same rubric a careful human reviewer would use, from Effective Reviews, not treated as a finished review on its own.

Learning Outcome

After using this workflow, you should be able to use an AI tool to accelerate either side of the review process — as the author self-reviewing a draft, or as the reviewer producing a first pass — while still exercising your own judgment about what the AI got right, wrong, or missed.

Core Structure

The shared rubric: breadth of topic exploration, depth of topic exploration, “enough words, no more” (efficient prose, free of vague or imprecise terms and jargon), and story integrity (a real beginning, middle, and end, with a conclusion that synthesizes).

As an author:

  1. Ask an AI tool to identify strengths and opportunities for improvement in your content and storytelling, using the rubric above.
  2. Revise your draft to address what it found.
  3. Ask the AI tool for an updated review against the same rubric, and iterate again if useful.

As a reviewer:

  1. Ask the AI tool to summarize the article in 1–2 paragraphs.
  2. Ask it to describe the article’s strengths and opportunities for improvement, using the rubric.
  3. Assess the quality of that AI-generated review yourself — don’t submit it unread.
  4. Add, subtract, or correct anything you find insufficient or wrong.
  5. Submit three separate parts: the original AI content, your assessment of that content, and your modified review.

Worked Example

Reviewing the same caching-strategy report used in the Effective Reviews worked example: ask the AI tool to summarize it and apply the rubric. Say it comes back reporting good depth but flags “story integrity” as weak, because the conclusion doesn’t clearly restate the original problem. Your job as reviewer is to check that against the actual text — if the conclusion does tie back to the problem, but subtly, you’d correct the AI’s assessment rather than pass it along unchanged, then submit the AI’s original note, your correction, and your final review as the three required parts.

Common Pitfalls

  • Submitting an AI-generated review unread, skipping the “assess the quality of the AI review” step entirely.
  • Treating the AI’s rubric scores as objective rather than as a first pass to be checked against the actual text.
  • Not separating the three required parts (AI content / your assessment / your modified review) — collapsing them loses the record of what you actually contributed.
  • Using AI review output to avoid engaging with the piece, rather than to accelerate a first pass before you engage with it directly.

Checklist

  • AI summary requested (1–2 paragraphs)
  • AI strengths/opportunities requested, using the shared rubric
  • AI review quality assessed by a human before use
  • Corrections made where the AI’s read was wrong or incomplete
  • Submission includes all three parts: AI content, your assessment, your modified review