iNDX CO+ Update: Highlights From January 5 to January 18 2026 — The Findability Breakthrough.

Summary

We are finally making real progress with iNDX. Thank you for sticking with me—this work is about to become much more tangible and useful.

Much of the content I share in the iNDX community is intentionally deep and technical, and in many cases it is most immediately relevant to marketers and those responsible for findability inside their organizations. That depth is necessary. As search shifts decisively into an AI-driven era, getting SEO and GEO/AEO right is no longer optional if you want your company, products, or ideas to be found by the right customers at the right time.

That said, clarity is coming.

In the next bi-weekly update, I will release a clear roadmap that distills this work into an executive-level guide for what everyone needs to do to remain findable in the AI era—without the technical complexity. Alongside that roadmap, I will also release a practical set of tools that you can begin using immediately.

And this is not just for brands. If you are an employee, do contract, freelance or side work or if you have assets with idle capacity that can be rented, shared, or monetized—this applies to you as well. In an AI-mediated economy, everyone with a product, service, skill, or asset needs to prepare for how discovery actually works.

I believe I have cracked the code on durable, future-proof SEO and GEO/AEO, and I will begin implementing these frameworks across my other companies and my personal brand.

Findability: Main Category

Rising Generative Engine Optimization (GEO) Trends
This post outlines how Generative Engine Optimization is emerging as a distinct discipline, driven by AI systems that synthesize answers rather than rank links. It highlights the growing importance of clearly structured, declarative content that AI can reliably interpret and reuse. https://www.seo.com/blog/geo-trends/

Google: Don’t make “bite-sized” content for LLMs
This discussion explores Google’s guidance against over-fragmented content, arguing that large language models perform better when given coherent, well-structured material instead of overly reduced snippets. The takeaway is that clarity and structure matter more than aggressive atomization.

A clear case for structure, brevity, and clarity
This post reinforces the idea that content optimized for AI discovery must be explicitly structured, concise, and unambiguous. It provides examples showing how well-declared structure reduces inference errors and improves downstream AI usability. https://www.wordstream.com/blog/ai-search-optimization-for-intros

State of AI Search Optimization 2026
An overview of where AI-driven search is headed in 2026, emphasizing the shift from keyword optimization to schema, metadata, and semantic clarity. The post positions structured data as the primary lever for long-term discoverability.

How big are Google’s grounding chunks?
This post examines emerging data on how Google segments and “grounds” content for AI processing. It offers insight into optimal content sizing and reinforces why coherent blocks of meaning outperform fragmented approaches.