A decentralised AI network where consumers contribute video data through a mobile app and node operators run validator infrastructure. Operators evaluate the network on technical and economic terms; contributors respond to reward mechanics and community. One message could not serve both, and the network needed volume on both sides simultaneously to be commercially useful.
“Reggie helped build the growth team from the ground up. His leadership and hands-on approach inspired juniors and built awesome team culture.”
“Deep knowledge in marketing with a deep passion about crypto. Always quick to produce results.”
“Helped kickstart our marketing strategy from concept to new product launch.”
Collecting, formatting, summarising, monitoring. High frequency, low judgment, and you can tell good output from bad at a glance.
Positioning, pricing, what to say and to whom. AI produces plausible marketing fast, and plausible is the failure mode — it reads fine and says nothing.
A workflow nobody uses is worth nothing. Most of these projects die at team adoption, not at the build, which is why SOPs and handoff are part of the work.
Story Mode installs the system and the operating discipline around it — so your team runs strategy, and the mechanical work runs itself.
These are the ones that consistently earn their keep in a small marketing team. Each is scoped to a specific job, with a checkable output and a named owner.
Pulls channel performance into one synthesised read with the changes worth noticing, so the Monday report stops consuming an afternoon.
Watches positioning, pricing, and launches across a named set of competitors and flags what genuinely changed rather than everything that moved.
Turns a topic and an audience into a structured brief with angle, proof points, and sources — the slow part before anyone writes.
Builds account context ahead of outbound or a sales call, so reps are not opening ten tabs to prepare for one conversation.
Checks links, tracking parameters, copy consistency, and asset variants before launch. Unglamorous, and it catches the errors that quietly cost money.
Monitors rankings and surfaces the pages and queries where a small change has disproportionate effect.
Where the team's week actually goes, measured rather than assumed. Rank tasks by frequency, judgment required, and whether the output is checkable.
Usually reporting or research. One workflow running reliably beats six half-built, and it proves the model to the team before you ask them to change how they work.
Add the next workflows, write the SOPs, and get the team using them in their normal week rather than as a side experiment.
Your team runs the system without you. Ownership assigned, failure modes documented, and a way to tell whether it is still working.
Workflow design and installation, scoped to the operating needs a diagnosis surfaces rather than a fixed package.
Installed by the same operator who runs the marketing engagements, which is why the workflows tend to fit how marketing actually gets done.
One 30-minute call. A practical conversation about where your team's week is going and which parts are worth automating.
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