From Darwinism in Search to Darwinism in AI: The Evolution of Evolution
Read Bernadeth Brusola’s analysis of Darwinism in Search and AI
By Jason Barnard
In 2019, I asked Gary Illyes from Google a question at the SMS Sydney conference: Does the Featured Snippet run on a different algorithm than the 10 blue links?
His answer changed how I - and eventually the industry - understood search.
Gary explained that Google uses separate algorithms for different SERP features, and these features bid against each other for placement. The feature that demonstrates the most value to the user wins the slot. Multiply your ranking factors together, and if any single factor scores below 1, your bid collapses. As Brent D. Payne put it: “Better to be a straight C student than 3 As and an F.”
I immediately recognized this as Darwinian natural selection applied to search results. I coined the term “Darwinism in Search” and published the framework in Search Engine Journal.
Then came the delicious irony.
When I interviewed Bing’s engineering team in 2020, Nathan Chalmers revealed that Bing’s whole page algorithm is literally named “Darwin.” I’d coined a term that already existed inside Microsoft’s codebase. The universe has a sense of humor.
The AI Evolution
Five years later, the framework has evolved - just as Darwin would have predicted.
Traditional Search (2019-2024):
- 10 result slots per SERP
- Content formats compete (video vs. image vs. text vs. featured snippet)
- The Whole Page Algorithm arbitrates
- Multiple chances to appear across a search session
AI Assistive Engines (2024+):
- 3-7 citations per turn (one side of an exchange)
- Passages compete for inclusion in synthesized answers
- The synthesis algorithm arbitrates
- Entire customer journey happens in one conversation
The math is brutal. In traditional search, you had 10+ opportunities per query. In AI conversations, you get 3-7 citation slots per turn - 70% fewer opportunities to survive.
And here’s the critical insight: the competition now happens across turns (each message), exchanges (one back-and-forth), and conversations (the complete journey). A prospect can move from discovery to decision in a single ChatGPT session, never visiting your website until ready to buy.
Cascading Queries: The New Selection Pressure
Fabrice Canel at Bing taught me about cascading queries - how AI breaks a user’s question into multiple sub-queries behind the scenes.
When someone asks “What’s the best CRM for SaaS startups?”, the AI also researches:
- What features do B2B founders care about?
- What’s the pricing model of HubSpot?
- Which CRMs integrate with Slack?
Your content must be the fittest passage for one facet of this cascade. As I wrote in Search Engine Land: “The best CRM article on Page 1 might lose to a single paragraph buried on Page 3.”
This is micro-answer engine optimization - winning at the passage level across cascading queries.
Darwinism in AI: The New Fitness Criteria
The selection pressure has changed. In traditional search, “fitness” meant relevance, links, and engagement signals. In AI, fitness means:
- Clarity: Unambiguous meaning (Google culled 3 billion ambiguous entities in June 2025)
- Consistency: Same facts everywhere across your digital ecosystem
- Corroboration: Third-party sources confirming your claims
- Confidence: AI trusts you enough to cite you
The consequence of low fitness has also evolved. In traditional search, poor fitness meant lower rankings - you’d still appear on page 2 or 3. In AI, poor fitness means algorithmic extinction. If AI doesn’t cite you, you don’t exist.
The Irony Completes Itself
Darwin’s original insight was that species adapt or die. The fittest survive not through strength, but through adaptation to environmental pressures.
In 2019, I applied this to search engines competing SERP features for user attention.
In 2025, the same principle applies to AI - but now your content is the species, the AI synthesis algorithm is the environment, and the selection pressure is clarity, consistency, and confidence.
The framework evolved. Just as Darwin predicted it would.
The Kalicube Process™ - Understandability → Credibility → Deliverability - is the fitness regimen for AI survival. Because in the age of AI Assistive Engines, you don’t optimize to rank. You optimize to be included in the answer.
And inclusion is everything.
Related Reading:
- Chunks, passages and micro-answer engine optimization wins in Google AI Mode (Search Engine Land, June 2025)
- SEO in the age of AI: Becoming the trusted answer (Search Engine Land, September 2025)
- How Bing Ranks Search Results: Core Algorithm & Blue Links (Search Engine Journal, April 2020)
- Bing’s “Darwin” Algorithm Revealed (Search Engine Journal, April 2020)
