How We Review AI Work

For all client work: websites, copy, content, ads, and SEO

Our Promise

Nothing goes to a client until a human on our team has reviewed it and stands behind it.

AI can turn out code, copy, ads, and articles faster than we can read them. Our bottleneck is now how long it takes us to review. We should plan our work around what we actually have time to check.

Ground rules

What we promise clients

Clients trust us because we can back up what we hand over. That only holds if we never promise more than we can review.

How deeply to review

Client facts & claims

High-risk code

Published content & ads

Everyday web work

Throwaway & drafts

If a change mixes a few of these together, review the whole thing at the strictest level that applies.

Day-to-day workflow

  1. Know what you're building first. Decide what the change is and how strictly it needs to be reviewed before you start prompting.
  2. Work in small chunks. Feed the AI the client's actual source material so it doesn't guess or fill in blanks on its own.
  3. Run the automated checks. Fix or regenerate until they pass: build, tests, and linters for code; spelling, links, and plagiarism for copy.
  4. Do the human review. Check the work yourself. If the AI wrote code you don't fully understand, or copy you can't vouch for, don't try to patch it—throw it away and ask for something simpler.
  5. Leave a quick review note. On the PR for code, or in the doc or ticket for copy and ads. Mention what the AI generated, what you checked, and who signed off.
  6. Ship it. Merge or publish once it's signed off (and once the client approves in writing, if it includes factual claims).

When you're pressed for time

Generate less. Never skip the review. If a deadline is tight and reviews are piling up:

Skimming high-risk code, spot-checking factual claims, publishing a batch nobody read, or merging something because it "looks fine at a glance" isn't how we work.


The batch limits are practical starting points. We'll revisit them every few months based on what's working for the team.