Step 7: Roll It Out to Your Team
Once the skill works, rolling it out is the easy part. If you want to document your process for the whole team, I covered building reusable AI workflows for your agency separately. I run it every Monday. It takes 30 minutes to review all 12 posts.
Each person gets a Slack DM with their four posts. Copy, paste, post. That is literally it. The same voice-file-plus-Claude pattern runs my LinkedIn DM workflow that saves two hours a day — different output, same plumbing.
Before the skill, we posted maybe twice a week between the three of us. Now we publish 12 posts per week. Every week.
The posts are better too. Not because the AI is a better writer. Because it starts from real stories with a clear structure.
We edit from 80% done instead of building from zero.
Victor told me his posts got more engagement after we started. Not because the AI wrote something magical. Because he actually posted consistently for the first time.
Consistency beats brilliance.
What the Delivery Layer Taught Me
Writing the posts is only half of it. Getting them in front of the right person at the right time is the other half.
We tried saving posts to a shared folder. Nobody opened the folder.
We tried emailing them. Nobody read the emails.
Slack DMs worked. A direct message with four posts, ready to copy and paste.
They see it, they grab it, they post it.
The Basecamp to-do adds accountability. It shows up in the weekly task list with a due date. If you haven't posted by Friday, the to-do is still staring at you.
Systems only work when the output lands where people already look. The same principle applies when you run an AI-powered agency: meet them where they are, not where you wish they were.
One Thing I Would Do Differently
I would write the voice file first. Before anything else.
I did it in step 4 because the planning conversation told me I needed it.
But if I started over, I would record myself talking for 30 minutes and transcribe it. Clean that up before even opening Claude Code.
The voice file is the single biggest factor in output quality. My first version was two paragraphs. The posts were generic.
The 596-line version produces posts I barely need to edit. Start there.
Frequently Asked Questions
How long does it take to build a LinkedIn content skill from scratch?
The initial build took about six hours over a few days. Two hours on the voice file, one hour collecting examples, 30 minutes planning, and the rest on building and testing.
After that, the weekly run takes 30 minutes for all 12 posts.
Does the AI write the posts or do I?
The AI writes the first draft based on real stories, your voice rules, and specific frameworks. You review, edit, and approve.
Think of it as starting from 80% done instead of a blank page. The human always makes the final call.
Can this work with ChatGPT instead of Claude Code?
The preparation steps are the same: voice file, examples, frameworks, real content sources. ChatGPT can handle the writing part.
The delivery automation needs a tool that can execute commands. That is where Claude Code or a workflow tool like Make comes in. I compared AI marketing automation tools that actually work if you want a full breakdown.
What if the posts don't sound like me?
Your voice file needs more detail. My first version was two paragraphs and the output was generic.
The current version is 596 lines. It covers everything from sentence length to banned words to how I describe problems. More specificity means better output.
How do I handle different team members with different expertise?
Define each person's domain in the skill. I handle marketing. Victor covers PPC.
Vinod writes about software development.
The voice rules apply to everyone, but the topics and framing shift based on who the post is for. The same voice-and-context approach carries over to paid LinkedIn too — here's how to use AI for LinkedIn ads.
What writing frameworks work best for LinkedIn posts?
We use three. How-to posts framed as "How I did this" in three steps. Personal stories as raw narratives.
And industry takes with an opinion on trends.
Every post has one idea, one hook, and ends with a question.
How do I make sure the AI doesn't make up stories?
Hard rule in the skill file: never invent. The AI pulls from two sources, a content ideas file and a notes folder.
If no source exists for a topic, it skips that topic. When referencing someone else's work, it frames it as "I read this." Never pretending something happened to you.
What was the biggest mistake during the build?
Leaving placeholder variables in the skill file instead of real values. The Basecamp integration had generic placeholders where the account ID and API token should be.
The AI got confused and tried to open a browser instead of using the API. Once I hardcoded real credentials, it worked instantly.
How many posts per week should each person write?
We settled on four: two how-to posts, one story, one industry take. That covers Monday through Thursday.
Consistency matters more than volume. Pick a number your team can sustain week after week.
Can I use this approach for content besides LinkedIn?
The same steps work for any repeated content task. Email newsletters, Twitter threads, blog outlines, client updates.
The ingredients are identical: a voice file, a structure, examples, and real content. We started with LinkedIn because it was our worst blank-page problem.
