running-content-engine

name	running-content-engine
description	Use when the team needs a systematic content production workflow, when content output is ad hoc or inconsistent, when existing content lacks a distribution plan, when BOFU conversion content is missing, or when a single content person needs to maximize output with AI assistance. Use when content exists but has no measurement or repurposing system.
user-invocable	true
metadata	{"version":"1.0.0"}

Content Engine

Overview

The content engine turns positioning, messaging, and customer insight into published assets that generate pipeline. At $1M-5M ARR, content compounds only when operated as a system with prioritization, AI-assisted production, distribution checklists, and performance measurement.

When to Use

• Content production is ad hoc with no editorial calendar or backlog
• Team publishes mostly TOFU blog posts but lacks BOFU conversion content
• Content exists but has no distribution plan or repurposing workflow
• A single content person needs to produce at scale with AI assistance
• No measurement system exists to tier and optimize existing content
• Sales team cannot find or use marketing content in deals
• Founder knowledge is not being captured as content

Don't use when: You have no upstream positioning, messaging, or customer research to base content on. Build those first.

Quick Reference

Phase	Duration	Output
Strategy foundation	Day 1-2	Funnel allocation, channel map, editorial themes
Prioritization and scoring	Day 3	Scored backlog of 30-50 pieces
AI-assisted production	Ongoing	15-25 pieces/month via 7-stage pipeline
Repurposing engine	Per piece	10+ format variants per core asset
Founder content	Ongoing	4-6 authentic voice pieces/month
Editorial calendar	Ongoing	Monthly calendar with weekly theme cadence
Performance measurement	Monthly	Tiered library with optimization actions

Core Deliverables

• Content Strategy -- Funnel allocation (50% BOFU, 35% MOFU, 15% TOFU) and channel-content fit map
• Scored Content Backlog -- 30-50 pieces prioritized by intent, ICP relevance, competitive gap
• AI Production Pipeline -- 7-stage workflow (brief, draft, enrich, edit, optimize, distribute, measure)
• Repurposing Framework -- 1-to-10 system per core asset
• Editorial Calendar -- Monthly structure with BOFU, MOFU, founder, and research weeks
• Performance Tier System -- 90-day tiering with actions per tier

Common Mistakes

• Inverting funnel allocation (80% TOFU instead of 50% BOFU)
• Publishing without a distribution checklist completed before go-live
• Using AI for volume without quality control checkpoints
• Gating generic content behind forms instead of ungating value
• Ignoring content decay and letting stale pieces erode authority
• Creating content without a proprietary angle (original data, customer quote, unique framework)
• Separating content from sales instead of building with a "sales can send this" lens

Integration

Feeds into: optimizing-geo-visibility, creating-sales-enablement, executing-launch-playbook, reducing-cac, accelerating-pipeline, growing-nrr

Refresh: Strategy quarterly. Backlog and performance monthly. Full library audit every 6 months.

See workflow.md for phase-by-phase execution, scoring matrix, AI production pipeline, distribution checklists, and measurement tiers.