Are you ready for a retainer conversation?

State the decision or job the content supports, not a promise about revenue, reach, or conversion.

A clear audience and use case gives the conversation something concrete to evaluate.

Keep the source, date, permission status, and narrow claim for each sample. Label practice work as practice.

Keep the lesson consistent while changing the opening, pacing, format, and evidence for each platform.

For AI-assisted work, name the human review for product facts, claims, likeness, artifacts, captions, and audio.

Name the asset types, formats, aspect ratios, platforms, quantity, and usage notes before discussing polish.

Record inputs, due dates, review windows, revision limits, approval owner, and open questions.

Check hooks, claims, brand terms, captions, aspect ratio, audio, file naming, visual artifacts, and product details.

Use version names, one feedback deadline, and categories such as must-fix, preference, and future idea.

Offer fewer assets, a longer timeline, or a scoped add-on when the requested volume changes the agreed bar.

Start from a real launch, product detail, format, or public question. Do not manufacture personalization or send copied bulk outreach.

Listen, reflect what you heard, and keep confidential information out of casual notes.

Follow up only with context, stop after a clear no or opt-out, and respect a no-response signal.

Choose a short call, one-page brief, proposal, pause, referral, or close based on what is actually known.

Before the next cycle, summarize delivered, learned, and next decision; offer continue, change, or pause paths.