Doc Williams has a rule I wish more people lived by. Go for quality, pick a narrow target, then go deep. He calls it a sniper approach, and he applies it to everything Brand Factory touches.
That is why LinkedIn was a puzzle for him. Doc had built a real audience on YouTube and a reputation in the no-code and AI world. On LinkedIn he was showing up in bursts and going quiet for weeks. He wanted outreach that matched the care he puts into his content, not the spray-and-pray posture he sees everywhere.
So we worked together to set it up properly. This is how it went.
Doc and Brand Factory
Doc runs Brand Factory out of the DC area. He makes videos on YouTube about AI, automation, and the tools people build businesses with. He has clients he consults for, sponsorships he takes on carefully, and a knack for being in the room when something new is shipping. He has interviewed Gary Vee. He speaks at director-level conferences for publicly traded companies when they want someone to explain what AI can actually do for them.
The thread in all of it is taste. Doc cares that things look right, sound right, and feel custom. He has said more than once that his stuff has to hold up next to creators like Justin Welsh, and you cannot get there with cookie-cutter output.
I'm more of a fan of a sniper approach. Get great quality content, go for very specific things, and just go from there.
Doc Williams, Brand Factory
Before Flow AI
When Doc and I first spoke, he told me honestly that he goes through waves on LinkedIn. He posts when he is live streaming or has a clear reason to. Otherwise he does not. He knew he should be posting more, and he knew LinkedIn was where the business buyers were. But he did not have a system, and the thought of logging in every day to scroll and prospect was not something he wanted to spend his mornings on.
He also had raw material most people would kill for. A 9,000 person email list from his creator work. An old alumni network spreadsheet, hundreds of names from a mastermind, sitting in a Google Sheet. Almost none of it was organised in a way he could use for outbound. The email list was mostly indie hackers, not decision makers. The alumni sheet was gold, but it was a list, not a workflow.
The honest before-state was bursts of effort, no repeatable system, and a feeling that his LinkedIn did not reflect the quality of the rest of his work.
The playbook Doc ran
We ran the same playbook I use with every customer. You can read the whole thing in our outreach playbook. Doc used the parts that made sense for him.
First, we tidied the profile. Headline, banner, about section, and a clear call to book a call. Doc's wife designs his banner, so I gave notes and she had a new version back in about twenty minutes. We grouped his about section into readable blocks instead of one long wall.
Then we built the list. We used Sales Navigator to curate a tight set of prospects. The first version targeted VP of Operations, COO, and Director of Operations, at companies of roughly 11 to 200 people, in advertising services, business consulting, IT consulting, and legal services, across the LA, New York, Atlanta, and Miami metros, with a filter to only include people who had posted on LinkedIn in the last month. Doc also had that old alumni sheet, and we ran it alongside the Sales Navigator list.
The message itself is where most outbound goes wrong. We used a soft icebreaker paired with a qualifying question. Something like, finally asking how AI has been impacting you as a COO, has it been easy to implement? The opener compliments without pitching. The qualifier invites a real answer and gives the people who are not interested an easy out. No pitch in the DMs. The pitch happens on the call, if there is one.
Where Flow AI fit in
Flow AI is the software that runs this playbook. For Doc, four parts mattered most.
Find Leads let us build the Sales Navigator list without Doc needing a Sales Navigator licence himself. When his focus later shifted, we rebuilt the list in the same tool and kept moving.
Auto-pilot, powered by Agent Maya, warms prospects up in the background. Maya sends connection requests and the opening message using the framework we set up together. Doc does not have to sit inside LinkedIn to make outbound happen.
Co-pilot is Maya as a Chrome extension inside Doc's LinkedIn inbox. When a prospect replies, Maya reads the full thread, the prospect's profile, and Doc's profile, then drafts a reply in the voice we set. Doc edits a word or two and sends. It keeps the replies human, because Doc is still the one choosing what to say.
The CRM tracks every conversation so nothing gets buried the way LinkedIn threads normally do. Maya also flags warm threads that need a follow-up, which is the part Doc liked most the first time he saw it. No more trying to remember someone by their face instead of their name.
What changed
I want to be honest about what happened. The first list did what a first list usually does. Doc's connection acceptance rate was healthy, which told us his profile and opener were working. The replies came in polite but often short, a few one-liners saying thanks or acknowledging a connection, not a flood of calls booked. That is what a first pass often looks like, and it is why we treat the first 90 days as a test.
The more interesting change came from Doc. He flew out to speak at a conference of directors from a publicly traded company who wanted to understand AI for their teams. He came back and told me the real conversation was not with operations leaders. It was with people at funded AI companies who had budget and needed help getting their message out. That matched Brand Factory's strengths better. It was also the natural fit for the audience he had already built.
So we pivoted. New list, same tool. We targeted Heads of Partnerships, Directors of Partnerships, and VP of Partnerships at technology, information, and internet companies in the US, still filtered to people who had posted on LinkedIn recently. We rewrote the opener around the work Doc actually wants to do, which is working with AI companies to reach their audience.
The other shift was operational. Doc now has a system he can step in and out of. Maya does the pedal work. Doc keeps the voice. When his audience moves, the system moves with him.
