Using AI as a University Instructor

I use AI almost every day, for both personal and professional tasks.

In the early days of AI – two years ago! – people sold compilations of “prompts” – magical incantations to get the AI genie to do something useful. Fortunately, that phase didn’t last long. Today I just treat AI like an assistant. This assistant knows a lot. They just graduated with a PhD in… well, pretty much every subject. But they are flaky, unreliable, and inconsistent. They need to be given very clear instructions, and their work needs to be carefully checked.

Rather than talking in generalities, I’m going to show how I use AI for a specific creative task.

Writing Lectures with AI

I teach computer science at a university in Silicon Valley. Sometimes, when I teach a new class or need to cover a new topic, I write a lecture from scratch. In the past, that took me about six hours. With AI, I’ve reduced the time to about 2 1/2 hours.

I start with very detailed instructions for my AI assistant. I include background and context, and I state specifically what output I want:

I am teaching an undergraduate course in the computer science department at a university in Silicon Valley. The course is “Object Oriented Design,” and we use the Java programming language. Write a lecture on the topic “Encapsulation, Delegation, and Refactoring Design Principles.”

The lecture should consist of 60-70 PowerPoint Slides. (Don’t actually create the slides; give me the lecture in outline form and I’ll make the slides myself.). Each slide should have 5-8 detailed bullet points. The bullet points should be understandable sentences or phrases, not just high-level topics. For each slide, include explanatory notes for me to use in the lecture. Focus on how the design principles solve real-world programming problems.

Where appropriate, show examples in the Java language. Examples may be in “before and after” form, showing how bad code can be improved by using the design principles.

Use current best-teaching practices to engage the students.

Given those instructions, the AI will produce a pretty reasonable lecture. I then go through the lecture slide-by-slide. As I do this, I create the actual powerpoint slides.

Sometimes I just make simple changes such as rephrasing something to fit my lecture style. I may delete points that seem like unnecessary tangents. I may add points that I think are important. I may split one slide into two, or combine slides. This is pretty much just copy-editing.

Sometimes I come across something that doesn’t make sense, or something I disagree with. This may be because:

I don’t understand the topic as well as I should
The AI has made an error
The AI has done a poor job of explaining the point

So I go back to my assistant:

Slide 17 is confusing. Can you explain the point you’re trying to make?

Sometimes the explanation will open up new questions. I may ask follow-on questions, or have the AI look up some references for me. Eventually, I may rewrite the questionable slide myself. Or, I may hand the task back to the AI:

OK, I think you’ve made some good points with regard to slide 17, but I think a better explanation is needed. Please expand that into 5 slides, and include a sample program in Java.

Also, as I go through the slides, I will sometime ask for illustrations to supplement the text:

Looking at the program on slide 26, please create a UML Class Diagram that clearly shows how the Delegation Principle is being used.

Or,

Slide 31 is important and I think we need to emphasize the point. Can you create a cartoon / meme to reinforce that?

In short, I treat AI as an assistant and collaborator. I can typically use about half the slides verbatim. Others require editing and clarification, and sometimes (as I’ve shown) I use AI to help me think through the changes that are needed. Occasionally I find that I don’t like the order in which things are presented, and I’ll re-arrange the slides.

After I’ve gone through the entire lecture, and created the PowerPoint slides, I upload the file to the AI with the following instructions:

I’ve uploaded a set of slides for my lecture, based on our work. Can you review the slides and let me know if you spot any errors, or things that could be improved?

Based on the feedback, I may make some final adjustments. The end result is a better lecture than I could have written myself, in less than half the time.

Related Uses

I use AI in many other ways for my classes. Here are a few more examples:

Updating Lectures

Sometimes I have a lecture that needs to be revised or updated. Here’s an example prompt:

I am teaching a graduate course in the computer science department at a university in Silicon Valley. The course is “System Architecture.” I’ve just uploaded a lecture on “The Current State of Quantum Computing.” The lecture was written two years ago, and needs to be updated to reflect recent progress. There may also be important things I missed. Can you prepare a revised lecture, following the outline of my existing lecture? Stick to my existing lecture as much as possible; limit changes to correcting incorrect information and adding new information.

The lecture should consist of 60-70 PowerPoint Slides. (Don’t actually create the slides; give me the lecture in outline form and I’ll make the slides myself.). Each slide should have 5-8 detailed bullet points. The bullet points should be understandable sentences or phrases, not just high-level topics. For each slide, include explanatory notes for me to use in the lecture.

Use current best-teaching practices to engage the students.

Once the AI creates the updated lecture, I go through the same review-and-edit cycle that I use for a new lecture. It’s much shorter and faster, because we’re starting with a good foundation.

Writing Quizzes and Tests

Preparing tests takes a lot of work. I might give a multiple-choice test at the end of a learning unit (multiple choice tests are not ideal, but can be automatically graded, which saves a lot of time). In the past, writing the test would take me 3-4 hours. With AI, I can cut that to an hour:

I am teaching an undergraduate course in the computer science department at a university in Silicon Valley. The course is “Object Oriented Design,” and we use the Java programming language. I’ve just uploaded slides for six lectures. Based on these lectures, please prepare 60 multiple choice questions that cover the material.

The questions should range in difficulty from moderate to very challenging, but they should not be “trick” questions. For each question, show the correct answer first, and then show three plausible but incorrect answers.

Also, for each question, shown an explanation justifying the correct answer.

In this example, I asked for 60 questions. I actually planned on giving a 40-question test, but I ask for more questions than I need. That way, if I don’t like some of the questions, I simply throw them out rather than trying to “fix” them.

I also use AI to create short-answer questions, essay questions, and programming problems. Those typically take a little more work, and back-and-forth, to craft. For a midterm exam, I might aim for 40 multiple choice questions, three essay questions, and three programming problems. I ask the AI to create more, so I can choose which to use.

Grading

Finally, I use AI for grading. This is a bit controversial. People are very wary of having AI grade students’ work.

It’s important to understand that in most university courses, assignments and exams are graded by a human “grader,” following a grading rubric (a standard or set of guidelines) prepared by the professor. The professor then reviews the grades before they are posted.

I am now using AI (or allowing my human grader to use AI), and then reviewing the output.

Just as with the tasks I’ve already described, using AI saves a lot of time and work. But more importantly, it allows me to give students much better feedback.

Here’a an example:

I am teaching an undergraduate course in the computer science department at a university in Silicon Valley. The course is “Object Oriented Design,” and we use the Java programming language. I’ve just uploaded an assignment that was given to the students, along with a detailed grading rubric.

I’m now going to upload the assignments the students turn in, one at a time. For each, assign a score from 0 to 100, based on the grading rubric. Show the scores for each aspect of the assignment, as specified in the rubrics.

Include detailed feedback for the student. Explain why points were deducted, and what the student could have done differently to earn full points.

I am very impressed with AI’s ability to give insightful feedback and advice. This goes beyond understanding the material and grading correctly; the comments that the AI provides are genuinely useful for students, and at least as good as I could write myself.

I’ve been doing this for two semesters. Sometimes students question the grading, and sometimes I agree with their concerns and change the scores. However, this is also true of human grading. I don’t think the number of complaints or errors has changed, and I think the feedback is much more comprehensive than what I – and my human graders – were able to provide in the past.

Using AI to Help Students Directly

As I incorporated AI into my workflow, I found that I was often using to explain things to me. If there was a topic that I didn’t fully understand, I’d ask AI to explain it to me. In the past, I would have:

Gone through some textbooks looking for an explanation
Done a web search
Watched some YouTube videos
Asked a colleague.

Now, I simply ask AI. If I’m still not clear, I engage in a back-and-forth dialog. I ask more questions. I ask for examples. I cna even ask AI to quiz me!

It’s a very effective way to learn. And I encourage my students to do the same.

“If there is anything from today’s lecture you didn’t understand, come by my office hours on Thursday. Or, you can upload the slides to ChatGPT and have it answer your questions.”

Are Students Using AI to Cheat?

Students are certainly using AI to do their assignments. And unless they are explicitly told to do that, it is cheating.

This is nothing new. Studies show that about 60% of university students cheat, and that’s been true for many years. We try to fight it. For example, I give more weight to in-class exams, and less weight to assignments. But we can’t prevent it.

At the start of each semester, I give a short talk about what students will learn in the class, and why it’s valuable. I tell the students, “These are important skills that you will need to be successful in your careers. If you pay attention in class, and you do all the assignments and exams, you will learn these skills. If you have someone else do your work, or you use AI to do your work, you won’t learn the skills, and that will hurt your career.”

University students are adults. They are free to make their own choices. I can only encourage them to make the right choices.

Is There Still a Need for Faculty?

For now, certainly. I see myself as creating the course.

I curate the topics – I decide what’s important and what isn’t.
I build the framework and outline for the course.
I determine the subject and general content for each lecture.
I present that material, and try to engage the students at a human level, oftne with personal stories and anecdotes.
I give direction to the AI, and I review, edit, and approve its work.

I don’t know if that will be true in ten years. It’s possible that university-level courses will be entirely created and taught by AI. But for now, I am using AI – an incredibly powerful tool – to deliver better courses with less work.

Note About the AI

In this post, I’ve talked about “AI” generically.

I am currently using ChatGPT for my university work, for three reasons:

The university has a contract so all faculty members get premium accounts
I’m most familiar with ChatGPT
It does a pretty good job

I’ve played with other tools, and I’m sure I could get similar results using another AI engine.

I almost always use Gemini to create illustrations, infographics, cartoons and memes. In my opinions, it’s light-years ahead of ChatGPT for effectively conveying information in graphic form.

All of this will change quickly! This represents the state of things, as I see it, in June 2026.

11Feb

How Google AI Is Changing the Way Local Businesses Win the Map Pack

For years, ranking in Google’s local map pack felt relatively straightforward. If your business was close to the searcher, had the right category selected, collected a solid number of reviews, and kept your Google Business Profile (GBP) updated, you had a strong chance of appearing in the coveted top three results.

But Google’s rapid integration of AI into search is quietly reshaping how local visibility works.

The traditional map pack isn’t disappearing overnight. Proximity still matters. Relevance still matters. Reviews still matter. But AI is changing how Google evaluates businesses — and that shift is raising the bar for everyone.

Local SEO isn’t dying. It’s evolving into a deeper game of authority, clarity, and trust.

From Keywords to Entities

Historically, local search leaned heavily on matching keywords, categories, and location signals. If someone searched “plumber near me,” Google primarily evaluated:

Proximity to the searcher
Category match
Basic prominence signals (reviews, citations, links)

Now, AI systems allow Google to understand businesses more like entities rather than just listings. An entity isn’t just a name and phone number — it’s a fully defined business with services, reputation, expertise, and connections across the web.

AI enables Google to analyze:

The specific services mentioned in reviews
The sentiment and context of customer feedback
The depth of service coverage on your website
Consistency of information across platforms
Brand mentions beyond your own website

This means local ranking is becoming less about minimal optimization and more about comprehensive digital presence.

The Rise of “Entity Confidence”

AI systems need confidence before recommending a business — especially in high-intent searches like “best divorce lawyer for high net worth cases” or “emergency roof repair after storm damage.”

Instead of simply displaying three nearby options, Google’s AI-powered experiences may highlight fewer businesses in certain contexts. When that happens, selection criteria become stricter.

What builds entity confidence?

Detailed service pages that clearly explain what you do
Reviews that mention specific services and outcomes
Strong engagement signals (clicks, calls, direction requests)
Consistent branding and information across platforms
Clear alignment between your website and your GBP

A thin profile with only hours, a phone number, and a handful of generic reviews is far less competitive than a fully developed digital footprint.

Reviews: From Star Ratings to Semantic Signals

Reviews have always influenced local rankings. But AI changes how reviews are interpreted.

Instead of simply counting reviews or averaging star ratings, AI can now analyze:

Service-specific mentions (“fixed my tankless water heater”)
Quality indicators (“transparent pricing,” “arrived within 30 minutes”)
Emotional tone and satisfaction signals
Patterns over time

A business with 75 detailed, service-rich reviews may outperform a competitor with 200 vague five-star reviews.

The takeaway isn’t to script keyword-heavy reviews — that’s risky and often against Google’s guidelines. Instead, it’s about delivering strong service experiences that naturally generate detailed feedback.

Review quality and consistency matter more than ever.

Website Depth Is No Longer Optional

Many local businesses have relied on minimal websites for years. A homepage, a contact page, maybe a services list — and that was enough.

AI-driven search changes this dynamic.

Google now cross-references your website with your Google Business Profile. If your GBP lists “commercial HVAC repair,” but your website barely mentions it, that inconsistency can weaken confidence.

Strong local performers increasingly have:

Dedicated service pages
Location-specific pages (when appropriate)
Structured data markup
FAQ sections addressing real customer concerns
Clear internal linking between related services

This doesn’t mean bloated content. It means clarity and completeness.

AI favors businesses that clearly demonstrate expertise in specific services.

Brand Signals Are Gaining Weight

Another quiet shift: Google appears to reward recognizable brands more aggressively in competitive markets.

Brand signals include:

Branded search volume
Direct website traffic
Mentions in local news or blogs
Social engagement
Backlinks from reputable sources

AI systems are good at recognizing real-world authority. If a business is frequently mentioned across trusted sources and generates consistent engagement, that strengthens its entity profile.

This doesn’t mean small businesses can’t compete. It means local marketing can’t rely solely on Google Maps optimization anymore. Broader visibility strengthens local rankings.

Proximity Still Matters — But It’s Not Enough

It’s important to clarify: proximity hasn’t disappeared.

If someone searches “coffee shop near me,” physical closeness still plays a major role. But in more competitive or specialized searches, proximity alone may not secure a top spot.

In the past, a nearby but mediocre listing might appear simply because it was closest. With AI-enhanced evaluation, a slightly farther but more authoritative business may outrank it.

The difference becomes more noticeable in saturated industries like law, medical services, home services, and financial services.

The End of “Set It and Forget It”

There was a time when claiming your GBP, choosing categories, uploading a few photos, and collecting some reviews could sustain rankings for years.

That era is fading.

AI-driven systems favor:

Ongoing review acquisition
Regular updates
Fresh engagement signals
Active reputation management

This doesn’t mean posting daily updates or obsessively geo-tagging photos. Many of those tactics are overstated.

It means maintaining an active, credible presence that reflects a real, operating business.

What Local Businesses Should Do Now

The shift toward AI doesn’t require gimmicks. It requires maturity.

Here’s a sustainable approach:

Fully complete and regularly update your Google Business Profile.
Build out detailed service pages that match your GBP offerings.
Implement structured data where appropriate.
Create a consistent review generation process.
Respond thoughtfully to every review.
Seek legitimate local press, partnerships, and mentions.
Ensure information consistency across all platforms.

The goal is not to manipulate an algorithm. It’s to remove ambiguity about who you are, what you offer, and why customers trust you.

The Real Opportunity

While some see AI as a threat, it’s also an opportunity.

In the past, lower-quality competitors could rank simply because they were close to the searcher. Now, businesses that invest in depth, reputation, and authority may gain stronger positioning — and hold it longer.

AI amplifies quality differences.

Businesses that build real trust signals will benefit. Businesses relying on shortcuts may struggle.

The Game Hasn’t Changed — The Stakes Have

At its core, Google still wants to show users the most relevant, trustworthy, and useful local options.

What AI changes is how well Google can evaluate those qualities.

The fundamentals of local SEO remain intact:

Relevance
Proximity
Prominence

But prominence increasingly includes semantic depth, authority, and brand strength.

For local businesses, the message is clear: visibility now favors clarity, consistency, and credibility.

The map pack isn’t disappearing. It’s becoming more selective.

And for businesses willing to build real authority, that selectivity can be a competitive advantage rather than a threat.

26Dec

Article Posting Sites

Despite what you may be reading on the Internet, Search Engine Optimization is not dead. It’s still a powerful tool to generate web traffic.

If you’d like to learn the basics of SEO, check out my book, The Three R’s of SEO: Core Principles Workbook, at Amazon.com.

An important component of SEO is acquiring links to your website. I like to create “link magnet” content: pages that people will want to link to. But I also post plenty of content on other sites, linking back to my clients. Here are a few of the link platforms I use:

28Oct

Get Your Website Listed in AI Results

Generative Engine Optimization is not a new discipline, but an intensified version of SEO. GEO focuses on depth, structure, and credibility to help websites earn visibility and citations in AI-generated results.

Why is Generative Engine Optimization Important for Your Website?

As of October 2025, Generative Engines – AI systems – are starting to have a measurable impact on search engine traffic. According to data from NP Digital, users are much less likely to click on conventional search results when presented with an AI Overview. Unfortunately, they are even less likely to click on citations and references in the AI overview. AI is having a negative affect on website traffic. However, users who follow the citations have more focussed intent; they are likely to be looking for products or services.

Search engines still account for the majority of website traffic, but it’s important to begin opimizing content to get listed in AI responses. Fortunately, the things that Generative Engines look for are also strong ranking factors for conventional Search Engine Optimization. Generative Engine Optimization (GEO) is not a different direction; it’s just a stepped-up SEO effort.

GEO is an evolving science, but using the techniques described below, we’re seeing good result getting placement in AI overviews:

Data from AHREFS, a widely-used SEO tool, showing the AI citations for a client website.

What Do AI Engines Look For?

Generative AI systems value:

Comprehensive Content. Citations in AI overviews and responses strongly favor longer, more comprehensive articles. This is increasingly true of search engines as well.
Well-Organized Content. AI looks for structured information, organized into easily digestible chunks.
Authoritative Sources. AI relies heavily on E•E•A•T (Experience, Expertise, Authoritativeness, and Trustworthiness) signals.

Let’s look at each of these factors.

Key Factors to Get Cited In AI Overviews

Why Is Comprehensive Content Important for AI?

Generative AI engines prefer sources that demonstrate depth, evidence, and completeness. Long-form content tends to:

Cover topics from multiple angles
Include context, examples, and data
Answer related sub-questions

These factors increase the likelihood of being judged authoritative and reliable by AI ranking algorithms.

Rather than thinking about your content in terms of an arbitrary word-count, focus on providing in-depth articles. For most topics, the article will naturally be 1,500-2,000 words – or even longer.

Why is Well-Organized Content More Likely to be Cited by AI?

AI doesn’t read pages like humans. It is processing the content, using statistical algorithms, to produce statistical clusters of words. Short sections that focus on specific topics are easy for AI engines to incorporate into their statistical models. Each section should be preceded by a heading that clearly identifies the topic of that section. Use nested headings to organized the overall article. There is some evidence that AI is more likely to pick up on headings that are phrased as questions.

Besides breaking your content into sections, you can use other formatting techniques to organize and structure your content. AI engines love ordered lists, bullet points, and tables.

You can also use the structured html tagsets, defined at schema.org, to help AI engines (and search engines) understand your content.

How Do E•E•A•T Factors Establish Your Credibility for AI?

There are a number of ways to establish Experience, Expertise, Authoritativeness, and Trustworthiness for your content.

Establish your Experience by including first-hand narratives, examples, case studies, and original data.
Establish your Expertise by featuring author bios, and linking to LinkedIn profiles, professional association bios, degrees and certifications, etc. The web is moving away from anonymous content. Build credibility by associating an author with your content, and showcasing the expertise of that author.
Establish your Authoritativeness by getting links and citations from credible sites (including industry round-ups, media outlets, or research papers). Guest-Publish or collaborate with credible partners. Encourage reviews and testimonials on trusted platforms, such as TrustPilot.
Establish your Trustworthiness by including contact information, privacy policy, and editorial guidelines. Cite primary sources, and quote authoritative people. Use structured data markup (Article, Review, Author, Organization) to help AI identify credibility cues.

E•E•A•T Factor	Practical Focus	AI/SEO Impact
Experience	Show firsthand stories, examples, and data	Enhances authenticity
Expertise	Highlight credentials & technical depth	Strengthens topic authority
Authority	Earn mentions, links, recognition	Builds entity trust
Trustworthiness	Be transparent, factual, and ethical	Improves ranking & citation likelihood

Advanced Factors for Getting Cited In AI Overviews

Focus on Questions

The focus of AI engines is generally answering questions from users. Therefore, content that answers questions is more likely to be picked up. This includes:

Frequently Asked Question (FAQ) pages
How-To articles
Subheads in your articles that include specific questions

Organize Your Pages

Use a silo or content hub approach. Write a comprehensive main article or blog post (the silo), and link out to related pages. The related pages should link back to the silo using link anchor text that reinforces the primary topic.

TL;DR

Many writers end their articles with a short summary, but for generative engines, it’s more important to start with an introductory paragraph that helps AI engines understand the focus of the article.

How Is GEO Transforming Web Content?

Generative Engine Optimization (GEO) isn’t a replacement for traditional SEO; it’s more like enhanced SEO. AI-driven search tools like Google’s AI Overviews and other Generative Engines are changing how users get answers to questions. Websites today need to go beyond keyword optimization. GEO emphasizes depth, clarity, and credibility to ensure that web content isn’t just found, but trusted and cited by AI systems.

Successful GEO depends on creating comprehensive, well-structured content that answers user questions while demonstrating authentic expertise and trustworthiness. Sites that showcase firsthand experience, expert authors, authoritative citations, and transparent practices are more likely to appear in AI-generated summaries and overviews.

GEO is about transforming your website into a semantically rich, clearly organized, and verifiably expert resource. Today’s focus needs to be on creating content that AI engines can confidently quote, cite, and recommend to users.

About the Author

Robert Nicholson is a Silicon Valley entrepreneur and consultant with a focus on web-based businesses. He is a Digital Media Consultant for Metro.Agency, and an instructor in the Computer Science, Computer Engineering, and Applied Data Science departments at San Jose State University. He is the author of The Three Rs of SEO, available on Amazon.

07Jul

AI and Your Website: Six llms.txt Plugins Reviewed

As I said in my previous post (Is AI Killing SEO), traditional search is not going away any time soon. However, search traffic is plateauing, and click-through rates for informational searches are falling, as AI systems like ChatGPT and Gemini deliver direct answers to users’ questions. For content websites that depend on traffic, it’s important to be cited, and linked to, and AI search results.

Fortunately, as I’ve previously explained, a good SEO strategy will also help get you listed in those AI snippets.

A New Standard: the llms.txt File

There’s also a new and important tool in the AI landscape: the llms.txt file. This emerging standard gives website owners more control over how AI systems interact with their content: what they can access, what they can’t, and how they should interpret it. While not yet universally adopted, major AI platforms are beginning to support it, and adoption is expected to grow.

If you’re running a WordPress website, there are already several plugins to automatically generate an llms.txt file. I’ve reviewed the current batch of plugins, and found a winner.

Llms.txt Plugins Compared

Website LLMs.txt / version 7.1.4

Author: Ryan Howard

This is a minimal plugin. The Settings allow the user to select the type of content that appears in the llms.txt file (pages / posts), and also specify the frequency of updating the file (daily / weekly / immediate).

In addition to page URLs, the llms.txt file generated includes publication data and text. There is no way to control the file content.

LLMs.txt Generator / version 1.0.2

Author: AEOmatic (Pedro Ladeira)

I tested the free version of this plugin. It indexes pages (not posts or other content), and it has no other settings. The llms.txt file generated includes URLs, and also default access rules:

# Custom Rules
Training: allowed
Scraping: limited
APIAccess: restricted

There is a paid version of the plugin, for $49, which I did not test. It claims to add the following features:

Include Posts in your llms.txt file
Daily and Weekly automatic updates
Custom taxonomies support
Custom generation rules
Full Multisite support

LLMs Text Generator for WordPress / version 1.0.5

Author: Fulgid

A new version of this plugin was released the day after my initial tests, so I retested it. The description below is based on version 1.0.5.

The setting allow you to specify the type of content to index (posts / pages / media), and also provide a header block to describe your site in the llms.txt file.

In addition to URLs, the file contains publication data and and a text excerpt.

The plugin can also generate another file: llms-full.txt, which contains the full text of all pages. Although this is a part of the evolving standard, I don’t believe it adds value in this case, since AI engines can simple scan the pages themselves.

LLMs.txt for WP / version 1.0

Author: Balázs Piller

The plugin setting allow the user to specify the type of content to index (posts / pages).

There is also a setting to generate “markdown” (.md) files corresponding to each page on the site. This is part of the proposed llms.txt standard, but I do not expect this to be widely used, since AI engines are perfectly capable of understanding standard web pages.

After choosing the settings, I was unable to find a way to actually generate the files! In its current form – in my opinion – this plugin is useless.

LLMS Full TXT Generator / version 2.0

Author: rankth

The plugin has extension settings. The user can specify the type of content to index (posts / pages / media), and the file update frequency (daily / weekly / manual). The plugin can generate llms.txt and llms-full.txt files.

It’s also possible to use the robots.txt file to restrict site crawling, or to specific a list of URLs to include or exclude. Unfortunately, the URL exclusion feature did not work; URLs I listed still appeared in the llms.txt file.

The llms.txt file also includes default access rules (which cannot be changed in the settings):

# Custom Rules
Training: allowed
Scraping: limited
APIAccess: restricted

Despite the fact that the exclusion feature did not work, this is a powerful plugin with many options.

Recommended with reservations.

Advanced LLMs.txt Generator / version 1.7

Author: Taha Büyüktaş

This plugin has a very clean and attractive user interface. Unfortunately, all of the text on the Settings page is in Turkish! However, I was able to use Google Translate (built in to the Chrome browser) to understand the settings.

Like LLMS Full TXT Generator, this plugin allows the user to The user can specify the type of content to index (posts / pages / media), and the file update frequency (daily / weekly / manual). The plugin generates llms.txt, but not llms-full.txt files.

The plugin allows the user to specify access rules. This is important if you do not want AI bots to index your site.

Like LLMS Full TXT Generator, this plugin allows the user to specific a list of URLs to include or exclude, but as with the previous plugin, the exclusion feature does not work.

Recommended with reservations.

Summary of llms.txt Generators

Plugin	Version	Author	llms.txt	llms-full.txt	Frequency	Content Types	Crawl Permissions	Disable URLs
Website LLMs.txt	7.1.4	Ryan Howard	X		X	X
LLMs.txt Generator / AEOmatic	1.0.2	Pedro Ladeira	X
LLMs Text Generator for WordPress	1.0.4	Fulgid	X
LLMs.txt for WP	1	Balázs Piller	X	X		X
LLMS Full TXT Generator	2	rankth	X	X	X	X	X	X
Advanced LLMs.txt Generator	1.7	Taha Büyüktaş	X	X	X	X	X	X

Conclusions

The llms.txt standard and the plugins that support it are still evolving.

At this point, I think it is worthwhile to have an llm.txt file on your site, and I recommend both Advanced LLMs.txt Generator and LLMS Full TXT Generator for WordPress users.

15Apr

Is AI Killing SEO?

In digital marketing circles, there’s a growing buzz – some might call it panic – that AI engines are replacing traditional search engines. Why click through websites when AI can give you a direct answer?

But let’s pump the brakes.

Yes, AI tools like ChatGPT and Google’s Gemini are increasingly being used for quick answers, especially for informational or how-to queries. But here’s the kicker: organic search traffic is still growing. People are still turning to search engines—especially when looking for products, services, or local businesses.

So no, SEO isn’t dying. But it is evolving.

AI is becoming a major information gateway, and it’s smart to start preparing your content for this shift. If you want your content to be cited or surfaced by AI tools, there are a few key strategies that make all the difference:

(1) Go Long with Content

AI models thrive on depth. They favor long-form, comprehensive content – ideally 1,000 to 2,000 words. (Beyond 2,000 word, returns diminish.)

(2) Make It Clear and Readable

Structure matters. Use headers, bullets, and short paragraphs. Tools like Hemingway and Grammarly, or Yoast SEO, can help you hit the right readability level.

(3) Focus on Niche Topics

“Long-tail keywords” aren’t just an SEO hack; they’re AI gold. The more specific your content, the better your chances of being cited by AI for answering nuanced or lesser-known queries.

One of my websites, the California Mission Guide, was cited by Google's AI Overview, — One of my websites, the California Mission Guide, was cited by Google’s AI Overview for a niche question.

(4) Establish Authority

Experience, Expertise, Authority, and Trustworthiness (EEAT). These aren’t just Google buzzwords! They’re becoming essential for AI recognition. Back your claims with credible sources, include author bios, and highlight real-world experience.

Bottom Line:

AI isn’t killing SEO, but it’s changing the game. The core principles of great SEO content still apply, but now there’s a new player on the field. Marketers who adapt early, by crafting high-quality, niche, and authoritative content, will be the ones who thrive in both worlds.

16Nov

The Value of Evergreen Content

Content-based websites and products are rarely glamorous, and are often disparaged by investors and developers. But there is a huge, overlooked advantage of content-based products… they retain their value for a long, long time.

I was a co-developer of Telemark’s Guide to Dogs, which was released on CD-ROM in 1995. The product was originally self-published.

The disk contained all sorts of information about dog activities, profiles and photos of 168 AKC-recognized dog breeds, and a “dog breed selector” that helped users to find the ideal dog breeds based on their lifestyles and preferences. It also included short videos of several dog activities, including police dog training and a Guide Dogs for the Blind “graduation” ceremony.

The content was later licensed to The Learning Company, where it sold over 45,000 copies and won a National Educational Media Network Silver Apple Award in 1997.

When the CD-ROM market began to die, the dog breed selector and profiles were licensed to the IAMs pet food company for use on their website, iams.com. In addition to paying license fees for the product, IAMs paid for regular updates, as the AKC added new breeds and modified breed standards. (In 2017, IAMs changed their branding strategy, and did not renew the license.)

In 2022, the Dog Breed Selector, Dog Breed Comparer, and over 200 dog profiles and photos were sold to Sugar Sweet Georgia Puppies, and are now hosted on their website, georgiapuppiesfromheaven.com. The extensive content continues to have high SEO value.

In short, an information content product has generated revenue for almost 30 years, and still has value. There are very, very few technology products and businesses that can make the same claim.

24Sep

The Future of Remote Employment

Just a couple of years ago, the future of work-from-home (WFH) seemed assured. At the height of the COVID-19 pandemic, in order to continuing operating, companies around the world allowed office workers to work remotely. Major companies including Facebook, Microsoft, Amazon, Zillow and Shopify announced plans to allow permanent remote work.

Until the COVID pandemic began in 2020, work-from-home programs had been gaining ground very slowly. The pandemic accelerated this progress by about 40 years!

Studies quickly claimed that at-home workers were actually more productive than their in-the-office counterparts^{1 2 3 4 5}. Some studies also reported that workers put in more hours when working from home, due to less time being spent commuting.

The benefits of working from home seemed very clear!

Employee Benefits

No daily commutes

Living and working from lower-cost or more desirable communities

Achieving a better balance of work and home responsibilities

Employer Benefits

Reduced expenses for office space

Higher employee satisfaction and retention

Improvements in productivity

But surprisingly, as the pandemic waned, attitudes started to shift. Companies began to order employees back to the office several days per week (a “hybrid” work model). Ex-Google CEO Eric Schmidt famously said, “I don’t know how you build great management virtually.”

Additional studies^{7 8} surfaced showing a decrease in productivity among work-from-home employees.

However, the forced return to the office may be driven more by management attitudes than by actual productivity data.

A study conducted by Microsoft⁶in September 2022 found that “85% of leaders say that the shift to hybrid work has made it challenging to have confidence that employees are being productive” and “49% of managers of hybrid workers struggle to trust their employees to do their best work.”

This lack of trust in worker productivity has led to what Microsoft researchers termed productivity paranoia, where leaders fear that lost productivity is due to employees not working, even though hours worked, number of meetings, and other activity metrics have increased.

Another survey, conducted by Citrix, found that half of all business leaders believe that when employees are working “out of sight,” they don’t work as hard.

In addition to issues of productivity, manager’s report that “Supervising, training, mentoring, and building firm culture is much harder” with fully remote workers than with workers who come in a few times per week⁷.

Today, a plurality of companies seem to be settling on a hybrid model, requiring office employees to be onsite several days per week. This model offers some of the advantages of full-time WFH programs, but doesn’t allow employees to work far from the office, or allow companies to take advantage of lower salaries in other parts of the country. A few companies have committed to permanent, full-time remote employment. This can be a significant advantage in recruiting and retaining employees who prefer remote work.

There are many studies and statistics about work-from-home, and the conclusions differ. One thing is clear: WFH has become a significant part of the jobscape in the United States. According to Forbes⁹, as of July 2023, 12.7% of employees worked remotely full time, and 28.2% worked in a hybrid job (split between remote and in-office work).

So, Is WFH More or Less Productive?

As a data scientist, I can’t draw any conclusions about WFH productivity. I’ve reviewed the articles listed in the references, and many others. Most of the “studies” are informal surveys. All use different methodologies, ask different questions, and even have different definitions for productivity. It appears that work-from-home can be more productive than in-the-office work, and it can be less productive, depending on many factors.

As a manager, I believe that remote workers pose significant challenges, and require new skills. Management’s commitment to mastering these skills will be a big factor in determining if a remote workforce can be successful and productive.

Managing Work-From-Home

Remote management is still evolving, but there are already a few key principles and techniques that have proven effective. None of these things should come as a surprise to a good manager. We are not re-inventing management – we’re simply adapting the things we already know to a different environment. But the specific skills and tools required to manage a remote workforce are changing. While many managers are resisting this change, the ability to lead remotely will be key to a management team’s success in the future.

Here are some of the best practices that have been established for remote management:

Make rules, policies, procedures, and expectations clear. Publish everything on an internal website, and review policies and procedures with employees regularly. Even terms like “complete tasks within two days” can be ambiguous when dealing with a distributed workforce, so don’t make assumptions.

Overcommunicate. Communication isn’t as effective when we can’t rely on social cues and body language, so double-down on communicating important information. Use websites, email, group meetings, and one-on-one meetings to convey and repeat important messages.

Facilitate informal communication. In a traditional office environment, employees often drop in on one another to ask quick questions or share ideas. It’s a little harder to make this happen in a remote environment. Two things are important:

Overlapping hours (“core hours”). There should be days and times when everyone is expected to be working.
Don’t make this too stringent! If everyone is expected to be online M-F, 9:00-5:00, many of the advantages of remote work are lost. Instead, choose something like MWF, 9-12:00 and 1-5:00. Most employees will still be available at other times, but outside the core hours, they’re free to run errands or take breaks.
Select an online chat tool for everyone to use. It must be easy to fire off a quick question, or to set up a phone conversation or video chat if more discussion is needed. Small companies often start with Skype, while larger companies often graduate to Slack.

Use collaborative tools. Collaborative tools allow team members to contribute to shared projects, to give input and feedback on one another’s work, to merge work from several team members, and to “release” finished work-products.

This is an area where the software industry is well ahead of other businesses. Some of the largest software projects in the world have been run remotely for decades. This includes the Linux kernel, an open-source operating system consisting of over 27 million lines of code, contributed by 13,500 remote developers from over 1,000 companies!

Schedule brainstorming. Despite what proponents of in-the-office work will tell you, brainstorming and problem solving rarely happen in informal hallway meetings. Such conversations are more likely to be about kids’ ball teams, or favorite recipes. Actual brainstorming and problem solving usually take place when people meet specifically to discuss ideas. But some studies have shown that online meetings are less likely to produce creative solutions^{10 11}.

To foster creativity, schedule meetings specifically for brainstorming, and stimulate creativity with color, humor, games and challenges. Skip the PowerPoint presentation!

Encourage social interactions. Employees work and communicate better with one another when they have a sense of personal connection. Use a variety of tools to help team members connect with one another. This can include personal profile pages on an internal website, a group chat application, and even online social meetings. (I know of one company that has a weekly online “beer bust.”)

Track progress and productivity. Productivity is an issue, whether employees are in the office or remote. Use tools to track key productivity metrics for individuals and team. It’s important to position this correctly. Don’t look at tracking tools as monitoring employees. Rather, share the data and discuss it regularly with team members. Use it as a tool for identifying problems early, and working together to solve them.

Plan for onboarding. Managers often comment that it’s very hard to bring new employees up to speed in a remote environment. Successfully incorporating new people into a remote team requires planning.

Make sure all important information is online, and that someone is available to answer questions or clarify written information. Update the information when there are questions.
Have new employees “shadow” a more senior employee while they come up to speed.
Assign a mentor to each new employees, and schedule regular chats with the new employee and the mentor.

Understand issues. Managers should always be understanding of issues faced by employees. Some unique challenges that surface in a remote workforce include:

Distractions while working at home.
Poor understanding of tasks and objectives.
Lack of communication with teammates.
“Video burnout.”
Feelings of isolation, stress, or depression arising from remote work.

Give employees opportunities to talk about concerns and issues, and work with them to find solutions.

Be ready to support home office conversions. Recognize that not everyone has a suitable place to work at home, and have a policy to provide assistance. This could range from payments for noise-cancelling headphones, to office furniture, to computer loans.

Invest in training. Remote work requires new management and communication skills, as well as specific knowledge of technologies, tools, and techniques. Investing in training is important to ensure success.

Conclusions

The COVID pandemic greatly accelerated the adoption of work-from-home, but it has now been accepted into the mainstream employment market. Studies show that employees strongly prefer the flexibility of WFH.

In July 2023, 11% of the job listings posted on LinkedIn were fully remote, but those listings attracted 50% of all applications¹². In 2023, an incredible 98% of all workers expressed a desire to work from home at least part time⁹, and 32% said they would take a pay cut to work remotely.

Companies that learn how to build and manage a remote workforce will have a significant competitive advantage in hiring and retaining staff, as well as substantial savings on office space and salaries.

About the Author

Robert Nicholson has managed distributed, remote, and off-shore staff for over two decades. More recently, he has taught entirely remote classes and advised remote graduate students as an instructor at San Jose State University.

References

Study: Teleworkers More Productive—Even When Sic k. Aliah D. Wright. Society for Human Resource Management (SHRM). February 13, 2015.
Is a mobile workforce your business’s best strategy for boosting productivity? Avast. November 14, 2018.
State of Remote Work 2021. OWL Labs. September, 2021.
Executives feel the strain of leading in the ‘new normal.’ Future Forum. October 2022.
Working from Home Increases Productivity. Shayna Waltower. Business News Daily. May 26, 2023.
Hybrid Work Is Just Work. Are We Doing It Wrong? Microsoft. September 22, 2022.
WFH’s Staunchest Proponents Just Dropped a Bomb: Fully Remote Workers Are Officially Less Productive. Jane Thier. Fortune. July 6, 2023.
The Evolution of Working from Home. Jose Maria Barrero, Steven J. Davis, Nicholas Bloom. Stanford Institute for Economic Policy Research (SIEPR). July, 2023.
Remote Work Statistics And Trends In 2023. Kathy Haan. Forbes Advisor. June 12, 2023.
Workers Think Less Creatively in Zoom Meetings, Study Finds. Iam Sample. Society for Human Resource Management (SHRM). June 8, 2022.
Thinking Inside the Box: Why Virtual Meetings Generate Fewer Ideas. Edmund L. Andrews. Stanford Graduate School of Business. June 29, 2022.
Remote and hybrid jobs are making a comeback. Jennifer Liu. CNBC. July 17, 2023.

04Mar

Eight Reasons to Hire an “Older American”

As the population in the United States ages, business leaders are discovering that older workers are not only “up to the job,” but may in many cases be better at it than younger employees. According to the US Bureau of Labor Statistics¹, the over-65 age group is the fastest growing segment of the job market, and more than 13 million Americans in this age group are still working.

Here are a few of the reasons why older workers can be a great choice for employers:

(1) Focus on the Job

Early- and mid-career workers are often preoccupied with career advancement. Their focus is on the things they need to do in order to move on to the “next job.”

Older workers tend to be less concerned with advancement, and more focused on satisfaction and accomplishment in their current job.

(2) Good Interim Workers

Older workers have the experience and skills to fill many positions. They can be an excellent choice to fill a position on a temporary basis, while you conduct a search for a permanent hire.

(3) Great Learners

Older workers have had to re-invent themselves many times over the course of their careers. They know how to go about acquiring new knowledge and skills.

While short-term recall and rapid recall decline as the brain ages, studies show that older brains are actually better at integrating new knowledge with existing knowledge. Studies also show that the decline in rapid recall is largely due to the fact that older people simply know more, so there is more knowledge for the brain to sift through.

(4) Strong Work Ethic

According to a 2010 Pew Research Center survey², “Nearly six in 10 respondents cited work ethic as one of the big differences between young and old. Asked who has the better work ethic, about three-fourths of respondents said that older people do.”

(5) Loyal

According to a report published by the US Bureau of Labor Statistics³, “the length of time a worker remains with the same employer increases with the age at which the worker began the job.” The report found that tenure for workers with their current employer was highest for the oldest workers at 10.2 years. For those between the ages of 55 and 64, this number was 9.9 years and 7.6 years for those between 45 and 54 years old.

(6) Strong Networks

Older workers have larger networks of colleagues and associates to draw on. A study conducted by The Center on Aging and Work at Boston College found that 46.3 percent of employer respondents said that their older employees have stronger professional networks and client networks compared to younger workers.

(7) More Productive

Surprisingly, studies have shown that productivity increases as workers age⁴. This may be due to greater knowledge and experience, or to better focus.

(8) Better Leaders

Older workers score high on tasks requiring leadership, detail-orientation, organization, listening, writing skills and problem solving — even in cutting-edge fields like computer science.

Businesses are Taking Note

These are a few of the reasons why companies are turning to older workers. In G7 countries, over 150 million jobs are expected to shift to workers over 55 by 2030, accounting to more than a quarter of the workforce⁵. In Japan, workers over 55 are expected to account for 40% of the workforce⁶.

References

Who’s Working More? People Age 65 and Older. Kenneth Terrell. AARP. November 22, 2019.
Millennials: Confident. Connected. Open to Change . Pew Research Center. February 14, 2010.
Number of Jobs, Labor Market Experience, Marital Status, and Health for those Born 1957-1964. US Bureau of Labor Statistics. August 22, 2023.
Productivity in older versus younger workers: A systematic literature review. C A Viviani et al. Work. 2021.
Better with Age: The Rising Importance of Older Workers. James Root et al. Bain & Company, 2023.
How can Japan turn its ageing workforce into an advantage? Kate Birch. Business Chief Asia. July 24, 2023,

27Nov

Moving a WordPress Multisite Network

WordPress Multisite is a very powerful tool. It allows you to manage multiple WordPress sites from a single admin panel.

Pages and posts on each site are still managed separately, but themes, plugins, backups and security are managed centrally. This makes it much easier to manage a group of related websites.

In addition to the basic Multisite capabilities, I highly recommend a few plugins that extend the multisite paradigm:

Network Shared Media – allows you to share media files across your websites.
Multisite Plugin Manager – improves plugin management; allows you to mass activate/deactivate plugins across your network of sites.
Multisite User Sync – synchronizes users across your network of sites.

The downside of WordPress Multisite is that moving a multisite network from one hosting server to another can be difficult.

I recently moved a network of websites (chinatown-directory.com and 18 associated sites) from BlueHost to SiteGround. I found a pretty painless, step-but-step process for making the move, which I describe below.

Go to your current Multisite dashboard. Install and activate the UpdraftPlus Premium plugin. This is a paid plugin… but believe me, it’s worth it!
Do a complete backup of your website, and download all the files to your desktop computer.
Go to your new host. Add the domain for the root (or original) site of your multisite network.
Change the DNS pointers to your root site to point to the new hosting server, and wait for the changes to propagate.
Go to the control panel for your new host. Install WordPress, and be sure to check the “enable multisite” checkbox.
Install and activate the UpdraftPlus Premium plugin on the new host.
Upload the backup files from your desktop computer, and run a restore.
Verify that the root site is working correctly on your new server.
For each of the additional sites in your multisite network:
- Add the domains on your new server; point them to the base domain directory.
- Change the DNS pointers for each of the additional domains.
Don’t forget that, if you have email accounts associated with the domains in your network, you’ll need to move the email accounts to your new hosting service as well.