Documentation

Setting Up Content Reservoirs

Complete guide to creating and configuring your first Content Reservoir for strategic content intelligence and automated generation.

Prerequisites

Before You Begin

  • • Active BlackOps Center account with reservoir access
  • • Defined content expertise area or niche
  • • Sample content (articles, posts, documents) in your expertise area
  • • Clear content goals and target audience identified

Step-by-Step Setup Process

1

Create Your Reservoir

Start by defining your expertise area and creating a new Content Reservoir.

Naming Best Practices

  • • Use specific, descriptive names: "AI in Healthcare" vs "Technology"
  • • Include target audience: "B2B SaaS Marketing for Startups"
  • • Avoid overly broad topics: "Business" → "Remote Team Management"
  • • Consider content volume: ensure enough source material exists
Example Configuration:
Name: "DevOps for Modern Applications"
Description: "Kubernetes, CI/CD, and cloud-native practices"
Target: "Technical leaders and senior developers"
2

Configure Reservoir Settings

Set up generation parameters, voice preferences, and content targets.

Voice & Style

  • • Tone: Professional, Casual, Technical
  • • Formality level: 1-10 scale
  • • Industry terminology preferences
  • • Brand voice guidelines

Content Targets

  • • Primary platforms (Twitter, LinkedIn, Blog)
  • • Content formats (threads, articles, posts)
  • • Publishing frequency goals
  • • Audience engagement objectives
3

Add Source Content

Feed your reservoir with high-quality content to train the AI on your expertise and voice.

Direct Input

  • • Paste blog posts
  • • Add article links
  • • Upload documents
  • • Import presentations

Browser Extension

  • • Save web articles
  • • Capture Twitter threads
  • • LinkedIn post collection
  • • One-click adding

API Integration

  • • RSS feed monitoring
  • • Social media imports
  • • CMS integrations
  • • Automated collection
⚠️

Quality Guidelines

Add 10-15 high-quality pieces initially. Focus on your best content that represents your expertise and desired voice. The AI learns faster from fewer, better examples.

4

AI Training & Analysis

Allow the AI to process your content and build your voice profile.

Training Process

Content analysis and categorization (2-5 minutes)
Voice pattern recognition (10-15 minutes)
Theme and expertise mapping (15-20 minutes)
Generation model optimization (30-45 minutes)
Training Status:
Processing content... 73% complete
5

Test Content Generation

Generate your first pieces of content to validate the AI training and voice accuracy.

Initial Testing

  • • Generate 3-5 sample Twitter threads
  • • Create a LinkedIn post draft
  • • Test blog post outline generation
  • • Review voice consistency

Quality Checklist

  • • Tone matches your brand voice
  • • Technical accuracy in your domain
  • • Appropriate complexity level
  • • Platform-specific formatting
Generation Guide

Advanced Configuration

Voice Profile Settings

Casual
Formal
Beginner
Expert
Conservative
Bold

Content Preferences

Include personal anecdotes
Use industry jargon
Include data/statistics
Add call-to-actions

Common Issues & Solutions

Generated content doesn't match my voice

The AI hasn't learned your voice patterns effectively from the source content.

✓ Add more diverse, high-quality source content • Adjust voice profile settings • Retrain with feedback examples

Content is too generic or broad

The reservoir topic is too wide or lacks specific expertise context.

✓ Narrow your reservoir focus • Add more specific source material • Update content targets

Training takes too long or fails

Content quality issues or technical limitations affecting AI processing.

✓ Check content format compatibility • Reduce initial content volume • Contact support for technical issues