How We Built Our Own Website with Agentic Design

Industry: AI Consulting

Dogfooding Our Own Approach

At Virgent AI, we believe in practicing what we preach. Our website isn't just a marketing site—it's a working demonstration of agentic design principles.

What is Agentic Design?

Agentic design treats every touchpoint as an opportunity for intelligent interaction. Instead of static pages, we build systems that:

• Respond to context - Adapt based on user behavior
• Anticipate needs - Proactively offer relevant information
• Learn and improve - Get smarter with each interaction
• Scale human effort - Handle routine tasks automatically

Our Website Implementation

1. Intelligent Contact Form

As detailed in our other case study, our contact form uses AI to:

• Filter spam and low-quality submissions
• Assess lead quality in real-time
• Provide instant, personalized responses
• Route to appropriate follow-up flows

2. Embedded Prompts

Throughout the site, we use embedded prompts that:

• Guide users to relevant content
• Answer common questions inline
• Reduce friction in the discovery process
• Collect implicit feedback on content quality

3. Dynamic Content Personalization

Returning visitors see:

• Content related to their previous interests
• Updated information on topics they explored
• Personalized calls-to-action
• Streamlined navigation paths

4. Agentic Chat Interface

Our chat system:

• Understands context from the current page
• Maintains conversation memory across sessions
• Escalates to humans seamlessly when needed
• Learns from every interaction

Technical Architecture

Front-End

• Next.js for server-side rendering
• React for dynamic components
• Tailwind for rapid styling
• Vercel for deployment

AI Layer

• LangChain for agent orchestration
• Multiple LLM providers for resilience
• Custom prompt engineering
• WebLLM for privacy-sensitive operations

Data & Learning

• PostgreSQL for structured data
• Vector database for semantic search
• Analytics for behavior tracking
• Feedback loops for improvement

Results

Lead Quality

• 95% spam eliminated
• 40% increase in qualified leads
• 50% faster qualification cycle

User Experience

• 30% longer average session
• 25% more pages per visit
• Higher returning visitor rate

Operational Efficiency

• 80% of inquiries handled automatically
• Faster response times
• Better lead routing accuracy

Lessons Learned

What Worked

1. Start simple - MVP first, sophistication later
2. Measure everything - Data drives improvement
3. Human fallback - AI + human beats AI alone
4. Continuous iteration - Ship weekly improvements

What Didn't Work

1. Over-personalization - Can feel creepy if obvious
2. Complex flows - Simple usually wins
3. Too much AI - Sometimes static content is fine
4. Ignoring edge cases - Failures damage trust

Try It Yourself

As you browse our site, you're experiencing these principles in action:

• The chat is AI-powered
• The contact form is intelligently filtered
• Content recommendations are personalized
• Navigation adapts to your behavior

We built this to demonstrate what's possible. If you like what you experience, imagine what we could build for your business.

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This case study demonstrates our commitment to dogfooding—we don't recommend anything we wouldn't use ourselves.

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Originally published on Virgent AI Case Studies