Marketing

Building a marketing operating system with Claude Code

Create a version-controlled repository (e.g., CLAUDE.md at the root plus structured folders) that lets an AI assistant load business context, route requests, and run repeatable marketing workflows without re-prompting each session. This functions as structured memory (brand voice rules, active campaigns, what worked/what didn’t) that can be refreshed regularly so the assistant doesn’t start from zero each time.

Why the human is still essential here

The marketer defines the system architecture, decides what context and rules are stored, keeps the “memory” sources current, and reviews/steers outputs; AI executes workflows and retrieves context but doesn’t own strategy or final decisions.

How people use this

CLAUDE.md marketing command center

Maintain a root CLAUDE.md that routes common requests (briefs, copy, reporting) to the right repo folders so Claude loads the correct context automatically each session.

Claude Code / GitHub

Version-controlled brand & campaign playbooks

Store brand voice rules, ICP notes, offer libraries, and past winning ads in a repo so updates are tracked and the assistant reliably references the latest guidance.

GitHub / Claude Code

Automated weekly performance narrative

Use a repeatable workflow that pulls key metrics, compares against targets, and drafts a weekly marketing update using the same reporting structure every time.

Claude Code / Model Context Protocol (MCP)

Community stories (2)

LinkedIn

I've been using AI agents for content work for 6 months now.

I've been using AI agents for content work for 6 months now.


The biggest problem isn't the writing quality.

It's not hallucinations.

It's not even cost.


It's the amnesia.


Every single session, AI starts from zero. It doesn't know my brand voice. It doesn't know we stopped using "innovative" because a client called it "empty corporate speak." It doesn't know that the last LinkedIn post about AI productivity got 4x the engagement of the one about automation tools.


So what happens?


I spend the first 10 minutes of every session re-explaining who I am, what we're working on, and what's already been tried. Every. Single. Time.


It’s a bit like an intern with a head injury.


And it compounds. Because without memory:

→ Your AI suggests headlines you already rejected

→ It writes in a tone you corrected yesterday

→ It pitches ideas that flopped last week

→ It can't learn what YOUR audience actually responds to


You're not building on anything. You're starting over. Repeatedly. With a tool that's supposed to save you time.


The fix isn't better prompts. You can write the most detailed prompt in the world and it'll be forgotten by tomorrow.


The fix is structured memory. Files your AI reads on startup that tell it: here's the brand voice, here's what worked, here's what didn't, here are the active campaigns. Updated automatically every night.


Once I set this up, my AI went from "generic content machine that needs babysitting" to "knows my projects, remembers last week's feedback, and suggests ideas based on what actually performed."


The difference between an AI that writes content and an AI that learns your content is memory.


Nothing else comes close.

DB
David BaumCEO and Co-Founder @ Relato
Feb 26, 2026
X

I Built a Marketing Operating System Inside Claude Code

I run a $3M creative agency and was tired of bouncing between AI tools with no shared memory. So I built a “marketing operating system” using Claude Code + a GitHub repo (centered on a CLAUDE.md file), plus reusable markdown “skills” (copywriting, strategy, content planning, etc.), brand-specific context folders, and MCP tools (YouTube transcript research, Reddit monitoring, thumbnail generation) so workflows load the right context automatically and improve over time.

AQ
Ali QureshiFounder, creative agency
Feb 23, 2026