Consulting Case Study

The brief

Vaibhav Sharda was building Autoblogging.ai into a serious AI content product. The market was crowded with thin AI tools producing generic, easy-to-spot output. To stand out and scale, the platform needed to generate content that was not just fluent, but genuinely optimized: structurally sound, semantically rich, and aligned with how Google actually evaluates expertise.

Where I came in

I consulted Vaibhav on four interconnected fronts. AI prompting and prompt engineering, so the model produced outputs that respected the structure of high-quality SEO writing. AI output evaluation, so the platform could distinguish between good and great content. Business vision, where to focus the product roadmap. And the semantic SEO principles of writing, so every generated piece carried the entity coverage, topical depth, and intent alignment that Google rewards.

What we shipped

• Prompt architectures that produced structurally sound, entity-rich content
• Semantic SEO frameworks baked into the generation pipeline
• Output quality criteria the team could evaluate against
• Strategic input on positioning, product roadmap, and go-to-market
• Ongoing review cycles as the platform evolved

The result

The product hit a quality bar most AI content tools never reach. Autoblogging.ai's revenue grew by 1,200% over the engagement, and the platform secured a six-figure investment on the back of that growth. The differentiator was simple: while competitors generated text, Autoblogging.ai generated content that was optimized for how search actually works.