Running a mid-size e-commerce operation means producing a lot of product descriptions. A lot. If you’ve never sat down to write 300 product descriptions, I’d encourage you to try it once so you can understand the specific kind of despair that sets in around number 40.
I started using AI writing tools for this about 18 months ago and the efficiency gains are real. What I didn’t expect is how much ongoing work it takes to maintain voice consistency at scale.
Early on, the outputs were fine individually but drifted significantly in tone when read across the catalog. Some descriptions were punchy and direct, others were formal and measured, others read like they’d been written for a different brand entirely. This was a prompt calibration problem. I didn’t solve it by getting better at prompting. I solved it by building a very specific house style document and treating the AI tool as a writer who gets that document as a brief before every assignment.
The current workflow: detailed style guide as a standing prompt context, batch generation in categories rather than one at a time, one human pass before anything goes live. With Walter Writes helping on the final polish pass, the output is consistent enough that I stopped getting customer feedback about the writing, which was the actual goal.
The failure mode I see other operators run into: treating AI output as a final product rather than a draft. The efficiency is in the drafting speed. The quality is in the human pass. Skipping the human pass saves 20% of the time and costs 80% of the quality.