liveBook · Manning

Feedback

As explained in "Looks Good to Me"

Feedback is information or opinions shared to help another person or team evaluate and improve work.

Feedback gives reviewers and authors a way to evaluate work, clarify concerns, and improve a codebase together. In a code review, its value depends on comments that are focused, clear, empathetic, and directed at the code rather than the person. section 2.4.1 section 6.0

Make feedback useful by adjusting the practice to the team’s situation:

  • Replace vague suggestions with specific comments that provide context, explain the concern, and identify a focused outcome. section 2.4.1
  • Agree on expectations for feedback detail, comment resolution, and review completion in a documented team working agreement. section 4.3.1
  • Separate constructive criticism from personal or subjective attacks; feedback should progress the conversation, provide clarity, or raise the team’s capability. section 6.0 section 7.1.2
  • Build a culture where people can raise concerns honestly, receive relevant feedback without defensiveness, and continue working together after disagreement. section 9.2.4 section 1.5
  • Use pairing or mob programming for real-time feedback when written comments create delay, while retaining a concise review for decisions and final checks. section 11.1.1 section 12.1.2
  • Use AI for initial, recurring, or lower-stakes feedback, then reserve human attention for design, architecture, and project alignment. section 13.1.1 section 13.1.2

From vague reaction to constructive feedback

A comment that merely signals dislike gives the author little direction. A stronger comment names the relevant concern, supplies context, and states the intended outcome, allowing the author and reviewer to resolve the issue rather than debate personal preference. The same principle applies when a reviewer gives many detailed comments and another gives almost none: without shared expectations, authors experience inconsistent review quality and uncertainty. section 2.4.1 section 4.3.1

Figure 2.7 An example of a vague comment left on a code review
figure

Compare the vague code-review comment with the clear and constructive alternative shown in the related review figures. section 2.4.1

How "Looks Good to Me" covers it

How deep it goes
Explains comment quality, team expectations, feedback culture, real-time collaboration, and AI assistance without reducing judgment to automation.
Examples
Uses vague and constructive PR comments, inconsistent reviewer detail, pairing sessions, mob sessions, and AI review tools as examples.
What it assumes
Assumes participation in code reviews while teaching teams to define expectations and communicate concerns constructively.
What you can do after
Apply it via code review by writing focused comments, agreeing on response expectations, and choosing human or automated feedback deliberately.
How it connects
Connects feedback with code review, team working agreements, pair programming, mob programming, and AI-assisted code review.

Also explained in

Compare how 18 books explain feedback →

Related concepts

This explainer was generated by Manning's knowledge graph from the text of "Looks Good to Me". The section links point to the parts of the book it draws on.