We automated our blog with AI and watched traffic flatten. Learn why AI content fails without human strategy, and how we're fixing our approach to create content that actually delivers value.
Reading time: 8 minutes
Summary: Over 70 days of fully automated AI blogging, our traffic dropped from 245 impressions to nearly zero. We're now at the beginning of building a hybrid approach that combines AI efficiency with human expertise. This post documents what failed, why it failed, and the framework we're testing to fix it. We'll publish follow-up results as we gather data.
Timeline: 70 days of automated AI content generation
Publishing frequency: 1 post per day
Total posts published: 70
Results:
| Metric | Our Performance | Why This Matters |
|---|---|---|
| Total impressions (70 days) | 245 | Extremely low visibility |
| Impressions (first 37 days) | 245 | Initial traction, then collapse |
| Impressions (days 38-70) | 0-4 per day | Traffic essentially flatlined |
| Click-through rate | 31%* | *Low sample size; unreliable metric |
| Bounce rate | Not tracked | Critical oversight in measurement |
| Content that drove engagement | 0 posts | No post generated meaningful traffic |
Post title: "UK AI Investment Soars with £31bn" Impressions: 4 Problem: The post reformatted existing news without adding perspective, analysis, or value beyond what readers could find in dozens of other sources published the same day.
We removed human decision-making from every stage of content creation. Here's what that looked like:
| Missing Element | Impact on Content | Result |
|---|---|---|
| Audience needs assessment | AI couldn't determine if our specific readers needed this information | Content answered questions nobody was asking |
| Strategic angle | No unique perspective or insight | Indistinguishable from competitors |
| Quality control | No human verification of value | Published content that shouldn't exist |
| Business context | No connection to our expertise or audience challenges | Generic information, not strategic assets |
The core problem: We optimized for production speed, not reader value.
Most small businesses face this impossible choice:
Costs:
Benefits:
Limitations:
Costs:
Benefits:
Limitations:
What small businesses actually need:
This is the problem space we're entering.
We're building a platform that automates research and drafting while creating structured moments for human expertise injection.
| Step | What Happens | Who Does It | Time Required |
|---|---|---|---|
| 1. Topic Research | AI monitors your industry for relevant trends and matches them against likely customer questions | AI | Continuous background process |
| 2. Strategic Proposal | Platform suggests specific topics based on search intent + relevance to your business | AI + Human approval | 2 minutes (review suggestion) |
| 3. Content Generation | AI creates draft using research, competitor analysis, and your brand guidelines | AI | Automated |
| 4. Expertise Injection | Platform asks targeted questions only you can answer (e.g., "What's your definition of AI slop?" "What mistake do you see clients make with this?") | Human | 10 minutes |
| 5. Draft Review | You review AI-integrated content, add editorial notes, refine positioning | Human | 10 minutes |
| 6. Final Polish | Platform integrates feedback; you approve or request one more revision round | AI + Human | 10 minutes |
Total human time per post: ~30 minutes
Total cost per post (estimated): $85-$120 (platform fee + your time value)
The platform is designed to extract what's unique about your business through targeted questions during the expertise injection phase:
Example questions the platform might ask:
These questions serve two purposes:
1. They're faster to answer than writing from scratch
2. They extract insight AI cannot generate on its own
This is the critical difference: We're not replacing human expertise. We're building infrastructure that makes it faster to integrate your expertise into well-researched, well-structured content.
What failed: Removing humans from the strategic and creative decisions
What might work: Removing humans from the repetitive, time-consuming research and drafting
The test: Can we create content that:
We're honest about what we don't know yet:
We don't have data showing:
We're committed to:
Timeline for measurable results:
We expect to have meaningful data within 90-120 days of consistent publishing (1 post/week). This aligns with typical SEO timelines for new content to gain traction.
We're at the beginning of this journey, not the end. Here's what we understand so far:
1. Scale isn't the problem. Strategy is.
Publishing one post per day with zero human input gave us zero results. The volume didn't matter because none of it was strategic.
2. AI is excellent at structure, terrible at judgment.
AI can research, organize, and draft. It cannot decide what's worth saying, what angle serves your audience, or what makes your perspective unique.
3. The bottleneck isn't writing speed. It's extracting expertise efficiently.
Most business owners don't have time to write blog posts. But they do have expertise worth sharing. The challenge is building systems that capture that expertise in 30 minutes instead of 3 hours.
4. "Value" must be measurable.
We used the word "value" throughout our original approach, but we never defined what it meant operationally. We're now defining it as:
If we can't measure it, we can't improve it.
We're building this platform in stages:
Current stage: Testing hybrid workflow on our own content
Next 90 days: Publish 12 posts using this approach, measure performance
Following 90 days: Invite beta testers, gather feedback, iterate
We're looking for beta testers who:
What beta testers get:
Randomly selected VIP bonus: 3 beta testers will receive comprehensive VIP account setup, one-on-one workflow optimization sessions, and priority support throughout testing.
We will publish follow-up results transparently:
90-day check-in: Traffic data, engagement metrics, workflow efficiency
6-month review: SEO performance, cost-per-acquisition, user feedback
12-month analysis: Long-term viability, ROI comparison vs. other content approaches
If this doesn't work, we'll say so. If it works partially, we'll explain what succeeded and what failed. If it exceeds expectations, we'll share the data.
This post isn't a case study. It's documentation of a hypothesis we're testing in real-time.
Are we trying to help businesses produce content, or are we trying to help businesses produce results?
Content is the output. Results—traffic, leads, customers—are the outcome.
We believe the gap between the two is strategy. AI can accelerate production, but humans must drive strategy.
We're building a platform that doesn't let you skip the strategic work. It just makes everything else faster so the strategic work becomes feasible for businesses without dedicated content teams.
That's the hypothesis. Now we test it.
Questions about our approach or interested in beta testing?
Sign up for early access →
Last updated: Nov 17th 2025
Next update scheduled: 90 days from launch
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