MyPhotoAI · pSEO case study

Slug strategy

The slug manifest is the single most important content artifact in a pSEO system. Every other layer (image generation, sitemap composition, internal linking) reads from it. Getting the manifest right is the work; everything else is plumbing.

How slugs are generated

The drafting loop has three steps.

  1. Keyword research, AI-assisted. A keyword tool surfaces long-tail intents adjacent to the product's category. The list starts wide (50 to 100 candidate slugs) so it can be cut down rather than padded out.
  2. Slug skeletons drafted by AI. Each candidate slug gets a draft title, meta description, intro paragraph, and image prompt. The drafts are deliberately uniform in shape so the next step can compare apples to apples.
  3. Human curate to 20 to 30. The author cuts every slug that fails one of: not a real user intent, indistinguishable from a sibling slug, no internal link block makes sense, image prompt is generic.

The cutting step is where the work is. A pSEO surface with 100 mediocre leaves ranks worse than 25 strong leaves, because Google reads the cross-link density and the per-leaf uniqueness.

What gets cut

Three patterns end up on the cutting floor every time.

  • Slugs that are queries, not destinations. "How do I X" is a query the search engine should answer with a snippet; a static page rarely wins that surface. Keep slugs that describe an artifact or a category.
  • Slugs whose intro paragraph could open three other slugs unchanged. That is template fatigue showing up at draft time. Either rewrite uniquely or cut.
  • Slugs whose image prompt is generic. "Hands typing on a laptop" is not an image; it is a placeholder. If the prompt is not specific to the slug, the leaf will not be either.

Maintenance cadence

The manifest is treated as a curated set, not a published archive. Slugs can be removed if they underperform after three months. New slugs are added in batches of two to five, never one at a time, so the internal-link block can be wired across the new entries before they ship.

Connection points

  • The architecture explains how the manifest feeds the build.
  • The image pipeline explains how each slug gets a unique image generated for it.
  • The results page tracks how the curation step affected rank distribution across the live slugs.