Stop Optimizing for “Chunking” - This Is What Actually Helps AI Understand Content

Why It Matters

Clear, entity‑focused copy helps LLMs surface brand content in AI answers, directly influencing organic visibility and marketing ROI.

Key Takeaways

• Avoid over‑optimizing content solely for chunking structures in marketing.
• Emphasize explicit entity connections within sentences and paragraphs.
• Use headings, tables, bullet points, but maintain natural narrative flow.
• Semrush AI Visibility Toolkit boosts brand visibility in AI-generated answers.
• Minor phrasing adjustments can dramatically improve LLM content comprehension.

Summary

The video argues that marketers should move beyond the prevailing focus on "chunking" – breaking text into headings, tables, and bullet points – and instead prioritize clear, explicit connections between entities within sentences and paragraphs. While such structural cues remain valuable, the speaker notes that the real breakthrough for large language models (LLMs) lies in how concepts are woven together, not merely how they are segmented.

Key insights include a reminder that the best content of recent years already incorporated chunking best practices, but now small linguistic tweaks can dramatically affect how LLMs parse and synthesize information. By making relationships between products, benefits, and target audiences unmistakable, brands can improve the likelihood that AI systems surface their content in generated answers. The speaker cites the Semrush AI Visibility Toolkit as an example of a product positioned to help brands appear more prominently in AI-driven search results.

A notable quote from the presentation: "Instead of saying our product does this thing really well, we say the Semrush AI Visibility Toolkit is great for brands looking to improve how they show up in AI answers." This reframing shifts the focus from vague capability claims to concrete, entity‑rich statements that LLMs can more easily interpret and reuse.

The implication for marketers is clear: refine copy to highlight explicit relationships rather than over‑engineering chunked layouts. Doing so can boost a brand’s visibility in AI‑generated content, driving higher organic reach and competitive advantage as AI becomes the primary interface for information discovery.

Original Description

Chunking, tables, bullet points… you’ve heard the noise. But that’s not the real unlock for AI visibility.

In this clip, Leigh explains what’s actually changing in how teams should think about content optimization in 2026 and beyond.

Leigh breaks down:

• Why “chunking” and NLP best practices aren’t new

• What high-performing content has already been doing for years

• Why over-optimizing for format can miss the point

• How writing clearer, more connected sentences helps LLMs understand meaning

• Why explicitly tying products, use cases, and outcomes together matters more than ever

• How small wording changes can dramatically improve AI comprehension

Using examples from Semrush, Leigh shows how modern content needs to be understandable not just to humans—but to AI systems synthesizing answers across the web.

The takeaway?

Don’t write for chunking. Write for clarity, context, and connection and let AI do the rest.