James Cadwallader, co-founder of Profound, discusses the rising influence of AI search engines on traditional methods. He explains the difference between AI answering engines and chats, highlighting shifts in user behavior and traffic patterns. James shares which industries, like healthcare and automotive, can thrive in this new landscape and offers strategies for optimizing visibility. He emphasizes the necessity of understanding bot traffic, creating targeted content, and utilizing innovative tools like llm.txt to improve marketing effectiveness in the AI era.
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insights INSIGHT
Web Retrieval Powers AI Answers
The integration of web retrieval with LLMs is the key inflection point for AI answer engines.
This combination delivers distillations of real-time web data rather than static model knowledge.
insights INSIGHT
AI Search Holds User Attention
AI answer engines hold user attention by providing answers directly, reducing website visits.
Websites become information sources bots crawl rather than user entry points.
insights INSIGHT
AI Sources Can Misinform
AI answer engines often source information from third-party content rather than official brand sites.
This can lead to misinformation and increased customer churn.
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In this episode, I chat with James Cadwallader, co-founder of Profound, about the rise of AI search engines and their impact on traditional search methods. We discuss how tools like ChatGPT and Perplexity are changing user behavior and referral traffic patterns. James shares insights on which companies benefit most from this trend and offers strategies for enhancing brand visibility in AI search results. We explore the importance of tracking bot traffic, creating targeted content, and optimizing metadata to align with AI models' preferences, highlighting the need for brands to adapt to this new digital landscape.
🎧 What You’ll Learn
AI Answer Engine Dynamics
Distinction between AI chat (LLM-only) and AI answer engines (LLM + web retrieval)
Key inflection points like ChatGPT’s web-search launch (Oct 2024)
Who Benefits Most
Industries with long research cycles (auto, healthcare, consumer electronics)
Tech-savvy early adopters and B2B SaaS customers seeing 3–4× month-over-month growth
Measuring AI Impact
Tracking bot-to-human conversions via crawler logs + GA4 or Amplitude
Understanding AI referrals as a first touch in your marketing funnel
Tactical SEO Levers
Comparative “X vs. Y” articles with optimized metadata
Creating simple, highly structured (markdown-style) content for fast crawler reasoning
Emerging Best Practices
Implementing llms.txt and bot-first content feeds
Building a dedicated AI visibility team—your next marketing department
⏱️ Timestamps
00:00 – Intro: The AI search revolution
01:00 – AI chat vs. AI answer engines explained
03:00 – Case study: ChatGPT mobile growth spike
05:00 – Which verticals see the biggest AI referral lift
07:00 – Bot crawling: measuring crawler visits + human actions
10:15 – How Profound uses synthetic data to map AI sourcing
14:30 – Tactical content strategies: from comparative posts to digital PR
18:45 – The future of AI SEO: protocols, agents, and team structures
22:10 – Action steps: What founders & marketers must do now
🎙️ Guest Profile
James Cadwallader Co-founder of Profound, the “Ahrefs/SEMrush for AI answer engine visibility.” James leads R&D on mapping how LLMs retrieve and cite web content, helping enterprise brands optimize for this rapidly growing channel.
In the Pit with Cody Schneider | Marketing | Growth | Startups 