Benjamin Houy shut down Lorelight, a generative engine optimization (GEO) platform designed to track brand visibility in ChatGPT, Claude, and Perplexity, after concluding most brands don’t need a specialized tool for AI search visibility.
Houy writes that, after reviewing hundreds of AI answers, the brands mentioned most often share familiar traits: quality content, mentions in authoritative publications, strong reputation, and genuine expertise.
He claims:
“There’s no such thing as ‘GEO strategy’ or ‘AI optimization’ separate from brand building… The AI models are trained on the same content that builds your brand everywhere else.”
Houy explains in a blog post that customers liked Lorelight’s insights but often churned because the data didn’t change their tactics. In his view, users pursued the same fundamentals with or without GEO dashboards.
He argues GEO tracking makes more sense as one signal inside broader SEO suites rather than as a standalone product. He points to examples of traditional SEO platforms incorporating AI-style visibility signals into existing toolsets rather than creating a separate category.
Debate Snapshot: Voices On Both Sides
Reactions show a genuine split in how marketers see “AI search.”
Some SEO professionals applauded the back-to-basics message. Others countered with cases where assistant referrals appear meaningful.
Here are some of the responses published so far:
- Lily Ray: “Thank you for being honest and for sharing this publicly. The industry needs to hear this loud and clear.”
- Randall Choh: “I beg to differ. It’s a growing metric… LLM searches usually have better search intents that lead to higher conversions.”
- Karl McCarthy: “You’re right that quality content + authoritative mentions + reputation is what works… That’s not a tool. It’s a network.”
- Nikki Pilkington raised consumer-fairness questions about shuttering a product and whether prior GEO-promotional content should be updated or removed.
These perspectives capture the industry tension. Some see AI search as a new performance channel worth measuring. Others see the same brand signals driving outcomes across SEO, PR, and now AI assistants.
Related: Stop Trying To Make GEO Happen
How “AI Search Visibility” Is Being Measured
Because assistants work differently from web search, measurement is still uneven.
Assistants surface brands in two main ways: by citing and linking sources directly in answers, and by guiding people into familiar web results.
Referral tracking can come through direct links, copy-and-paste, or branded search follow-ups.
Attribution is messy because not all assistants pass clear referrers. Teams often combine UTM tagging on shared links with branded-search lift, direct-traffic spikes, and assisted-conversion reports to triangulate “LLM influence.”
That patchwork makes case studies persuasive but hard to generalize.
Why This Matters
The main question is whether AI search needs its own optimization framework or if it primarily benefits from the same brand signals.
If Houy is correct, standalone GEO tools might only produce engaging dashboards that seldom influence strategy.
On the other hand, if the advocates are correct, overlooking assistant visibility could mean missing out on profitable opportunities between traditional search and LLM-referred traffic.
What’s Next
It’s likely that SEO platforms will continue to fold “AI visibility” into existing analytics rather than creating a separate category.
The safest path for businesses is to continue doing the brand-building work that assistants already reward, while testing assistant-specific measurements where they are most likely to pay off.
Read also: Why You Should Be Focusing On Brand Marketing Right Now
Featured Image: Roman Samborskyi/Shutterstock
