The Hex Update: Issue 025

the hex update
media
AI’s impact on Google Search; informational content and its role with LLMs; everything is becoming television; design elements to make text look ‘futuristic’; and some other cool things I came across this week
Author

Collin K. Berke, Ph.D.

Published

May 15, 2026

Let’s catch up

Welcome to Issue 025.

I’ve just been chugging along this week with work and home projects. This includes staying busy and checking items off the to-do list. Not much else to report, so let’s dive in.

Three topics recently caught my attention:

For a bit of fun, I share an article demonstrating how various typesetting design elements are used to give text a futuristic look.

You’ll also find some additional links to other items I found cool this week.

Three things

Here’s what caught my attention this week:

How AI Is Changing Google Search and SEO (podcast)

This podcast is an interview with Nikola Todorovic, director of Software Engineering at Google Search. The episode focuses on the impact AI overviews have on search. According to Nikola, users are finding search can now answer more complex questions (02m58s). As such, search queries are becoming longer. Search has transitioned from keyword searches, to more conversational queries, and to now being longer AI prompts by users. To return better search results, AI overviews synthesize information returned by a technique called query fan-out (13m09s). Although this technique is meant to create better AI summary results based on user intention, it continues to challenge publisher’s SEO strategy. The interview then explores the impacts these features will have on the content ecosystem, as well as SEO going forward (20m29s). Todorovic was clear: there is no magic SEO wand to find success with this version of search and AI summaries. Despite this, he emphasized one area to focus on. Site owners should continue to create products and content that provide value to users. People still need to continue providing value to people.

Why does this matter?

Continue creating useful content for users. Useful in this case means creating and publishing content answering the various queries extending from what was originally asked by the user. It’s no longer about identifying and using the keywords users are searching for, but rather it’s about publishing content to meet user’s explicit and implicit intentions. AI search summaries seek to provide additional information users intend to receive. There’s also certainly some structural things that can be done to improve the chances content gets included within AI summaries. This Digiday article provides some places to start.

The Role of Informational Content in the Age of LLMs (blog)

This blog post outlines recommendations for writing informational content that works best with LLMs. Its thesis is the way informational content was written in the past is now obsolete. As such, it highlights several points and guidelines on what publishers can do if they are writing informational content. Simply put, according to the article, writing with keywords users are searching for is no longer the tactic. Now it’s about associations: the writing should connect the content to other topics or entitys. In addition, in this era of LLMs, publishers need to continue writing content that provides new, genuine value, clarifies complex ideas, and offers practical information not found elsewhere. It’s no longer about providing general information; publishers now need to provide specifics. The article also places extra emphasis on relying on the Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) quality guidelines provided by Google. As such, certain structural elements of the article are now critical: bylines, credentials, and moves that show expertise.

Why does this matter?

AI search summaries have impacted SEO strategy. Tactics useful for populating content in search rankings will no longer work for AI summaries. The specific tactics to get populated within summaries are still being experimented with. What we do know is how search works in terms of fan-out queries, and content written to address intent inherent in these fan-out queries is one area to focus. More importantly, though, is the need to continue creating genuine content that meets user’s needs. The E-E-A-T model is useful here. Also, Google’s AI search guidelines are worth a review.

Everything is Television (article)

Here’s a really interesting article about how all things in media are turning into television. The article shares several examples to support this point: the majority of time spent on platforms like Facebook and Instagram are spent watching video; podcasting’s move to more of a video first format; and AI tools rolling out spaces where users can watch endless amounts of AI generated video content. The article attempts to further explain the statement that “everything is turning into television”: the continuous flow of episodic video. The article posits it’s the infinitude nature of this flow of video that is the primary driver of consumption, not necessarily the content itself. The article then provides positives and negatives if all media embraces the grammar of television.

Why does this matter?

Platforms recognize the importance of video, especially the role short form video feeds have on discovery and consumption. Take Netflix’s recent feature roll-out of its vertical video feed for mobile as an example. It’s now critical for publishers who rely on other platforms to understand the shift in focus toward the flow of video, rather than strictly on the titles that are available. It’s also an interesting thought experiment to consider the impacts a move for all of media to embrace the grammar of television can have. That’s a bigger question worth further exploration. Some interesting points made in this one, so I suggest taking a look.

Check out the links above for the full story in each item, not just my brief summary and analysis.

What I found interesting this week

I’ve been trying more and more to use visidata from some data work, specifically data entry and exploration. It’s a really powerful tool, but I’ve clumsily used it in the past. It’s main utility, for me, is to be able to view data from the terminal.

Well, this week I began trying to learn how to use it for other data tasks. To assist in my learning, I drafted the start of a cheatsheet for my reference. For now it’s just focused on data entry and editing data files. The hope is to expand it some more as I learn new things. Here’s what I’ve got thus far:

# Entering data
`za`     - blank new column
`a`      - blank new column
`e`      - edit a new cell
`Ctrl+s` - save a sheet

Oh, I also learned about the clipr R package this week. It’s a really nice utility to write things to your system’s clipboard. I’ve found some really neat programmatic uses for it.

Cool things I recently bumped into

A collection of links to things I’ve found cool recently (or was reminded are cool).

That’s it for this update.

I hope you have a good weekend.

Cheers 🎉!

Let’s connect

If you found this content useful, please share. If you find these topics interesting and want to discuss further, let’s connect: