We partnered with a coach who was spending over $3,500 per month on a content agency that was not meeting their needs
Despite the investment, they were frustrated with:
- Generic content that didn’t capture their unique expertise
- Lack of agility to respond to market trends or news
- Slow turnaround times (1-week revision cycles)
- Limited posting frequency (3 posts/week across all platforms)
- No real understanding of their business or industry nuances
They wanted to bring content production in-house but their 2-person marketing team had no capacity to manage it themselves.
The Solution: Building an AI Workforce
Instead of hiring another agency or bringing it in-house, we built them three AI employees that work together like a real content team at 2% of agency cost.
Results At A Glance
- 97% cost reduction
- 625% more content
- Better quality (founder prefers it to agency 70% of the time)
- 85% less time required
- Gets smarter every week
Phase 1: Deep Business Discovery
Before building anything, we needed to understand their business better than any agency ever had.
What We Gathered:
Brand Voice:
- Analyzed their best-performing content
- Reviewed their client success stories
- Documented what makes them different from competitors
Business Intelligence:
- Technical understanding of their services
- 3 detailed customer profiles
- What the previous agency kept doing wrong despite low engagement
Performance Audit:
- Which platforms mattered (LinkedIn dominated)
- Posting frequency and missed deadlines
- Team time spent in revision cycles with the agency
Phase 2: Building the Infrastructure
We built the one-time infrastructure that would power their AI workforce—not just for these three employees, but for any future additions.
What We Created:
Simple Control Dashboard:
- Review content, logs, and proposals
- Approve posts with one click
- Works on phone, tablet, or computer
- No complicated software to learn
Self-Learning System:
- Logs every action and outcome
- Identifies patterns automatically
- Proposes improvements based on data
- Gets smarter over time without manual updates
Quality Control Layer:
- Tracks what content performs well
- Validates every result based on specific rules we set up
- Automatically revises content that doesn’t meet quality standards
- Everything reviewed before final outcome
Security & Control:
- Company data stays private
- Full transparency on what’s created
- Override or edit anything
- Human approval required before publishing
Why This Matters: This infrastructure supports unlimited AI employees. Adding new ones later takes days instead of weeks.
Phase 3: Training the AI Employees
We trained four specialized employees using everything we gathered in Phase 1.
The Content Strategist:
- Researches new trends
- Reviews topics set by the business
- Decides what to post where and when
- Adjusts strategy based on performance data
3 Content Creators (one per platform), each with the following tasks:
- Writes posts based on specific frameworks
- Generates an image
- Drops all content into Airtable ready for approval
The Self-Improvement System:
- Each employee logs every decision
- The system analyzes data over time
- Proposes specific improvements
- Rewrites the instructions after human approval
The system learns from both approvals and rejections.
Phase 4: Testing & Launch
Testing Phase:
Launched live
Stress tested each content creator over time
Fine-tuned instructions and frameworks
Easy Expansion (The Infrastructure Advantage)
Adding new AI emplyees:
With the infrastructure already built we can now:
- Build new AI employee in a matter of days
- Same approval workflow
- Same quality standards