Agentic AI In SEO: AI Agents & Workflows For Audit (Part 2) via @sejournal, @VincentTerrasi

Building on our previous exploration of Agentic SEO’s ideation capabilities, this article takes a closer look at the second pillar: Audit.

As promised, we’ll look at how AI agents can transform the SEO audit process by providing corrections and thorough analysis that would otherwise take hundreds of hours of manual work.

Traditional SEO audits are often time-consuming, involving multiple tools and manual reviews.

With Agentic SEO, however, this process can be streamlined through autonomous AI agents that identify problems and recommend and implement solutions in real time.

AI Agents For Advanced Site Analysis

Full Website Analysis With Real-Time Corrections

Agentic SEO transforms the review process by:

  1. Comprehensive crawling: AI agents can systematically analyze entire websites, including hidden pages and dynamic content that traditional crawlers might overlook.
  2. Intelligent pattern recognition: Unlike rule-based tools, AI agents can detect patterns and anomalies that may indicate deeper structural issues across your site.
  3. Real-time remediation: As well as identifying problems, the agents can generate code fixes, content improvements, and structural adjustments that can be implemented immediately.
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Example: Firecrawl Demo

With advanced AI crawling, Firecrawl can meticulously analyze HTML structures, extract microformats, and provide detailed performance metrics, revealing critical areas that need optimization and might otherwise be missed.

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Example: Similar to tools like Cursor integrated with GitHub, Agentic SEO enables immediate application of code fixes.

When an issue is identified, the agent directly suggests optimized code changes, allowing seamless implementation through direct integration with your repository, ensuring rapid and error-free remediation.

I’m confident that OpenAI’s Codex and Google’s Jules will be equally effective for these tasks.

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Workflow Architecture For Effective Auditing

Similar to our idea workflows, audit workflows consist of specialized components.

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The audit workflow typically includes:

  • Data collection agents: These collect information from your site, competitor sites, and search engine results.
  • Analysis agents: These specialize in identifying technical issues, content gaps, and optimization opportunities.
  • Recommendation agents: They prioritize issues and suggest specific solutions based on potential impact.
  • Implementation agents: Generate corrected code, optimized content, or step-by-step implementation guides directly.

Practical Use Cases

Technical SEO Auditing

AI agents excel at identifying technical issues that are often overlooked:

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The agent doesn’t just flag the problem. It provides contextual recommendations and implementation guidance.

Content Gap Analysis

Beyond traditional auditing, AI agents can identify content gaps by:

  1. Analyzing competitive content structures.
  2. Identifying SERP features you’re missing.
  3. Discovering semantic relationships between existing content.
  4. Suggesting opportunities for content consolidation or expansion.
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Internal Linking Optimization

One of the most powerful applications is internal linking analysis:

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How To Build Your Audit Agent

Creating an effective audit agent requires:

  1. A specialized knowledge base: Provide the agent with SEO best practices, Google guidelines, and industry-specific benchmarks.
  2. Tool integration: Connect the agent to existing tools such as Screaming Frog, Moz, and Semrush, or custom APIs for comprehensive data collection.
  3. Human-in-the-loop checkpoints: Despite automation, human expertise is still needed to validate critical recommendations.

Case Study: Ecommerce Site Optimization

In less than 30 minutes, our Agentic SEO Audit System identified 347 critical technical issues for a mid-sized ecommerce site with 15,000 product pages.

  • It generated optimized title tags and meta descriptions for underperforming pages.
  • It discovered and mapped content gaps in product categories.
  • It created a comprehensive action plan based on revenue impact.

Implementing these recommendations resulted in a 32% increase in organic traffic within 60 days.

Current Challenges And Limitations

Although powerful, Agentic SEO auditing does have its challenges.

  1. Tool integration complexity: Connecting Agentic to all the necessary data sources requires technical expertise. For instance, setting up MCP (or Model Context Protocol) servers can be a challenging task.
  2. Evolving standards: Agents require regular updates to keep pace with changes in search engine algorithms.

Tools to Build Your Own SEO Audit Agent

Here are some practical tools to help you get started:

  • Open-Source Workflow Automation – n8n is a powerful, open-source automation tool that allows you to create complex workflows without coding. It’s ideal for orchestrating SEO tasks like crawling, data extraction, and reporting.
  • Python Framework for Multi-Agent Systems – CrewAI enables the development of multi-agent systems in Python, allowing specialized agents to collaborate on tasks such as data collection, analysis, and implementation.
  • Agentic AI Platform – DNG.ai (Draft & Goal) is a no-code platform designed to automate complex SEO workflows using specialized AI agents. It offers features like:
    • Agentic Workflows: Automate tasks such as keyword optimization, content creation, and data analysis.
    • Multi-Agent Collaboration: Coordinate multiple agents to handle large-scale projects efficiently.
    • Integration with Over 20 Marketing Tools: Seamlessly connect with tools like Google Search Console, Google Ads, Google Analytics, and more.

Resources to Learn and Get Started

To improve your understanding and skills in building SEO audit agents, you can also explore these resources:

Summary: Agentic SEO Is A Fundamental Shift

Agentic SEO’s audit capabilities represent a fundamental shift in how we approach technical optimization.

By combining AI’s pattern recognition abilities with the strategic insight of human experts, we can create audit systems that are more comprehensive and actionable than traditional approaches.

In our next article, we’ll explore the final pillar of Agentic SEO: Generation. We will examine how AI agents can generate missing content, optimize existing assets, and scale content production while maintaining quality and relevance through the “SEO Expert in the Loop” approach.

Stay tuned, and experiment with these techniques to transform your SEO workflow!

More Resources:


Featured Image: Deemerwha studio/Shutterstock

Wix Acquires AI Platform That Enables Anyone To Create Software via @sejournal, @martinibuster

Wix announced it is acquiring Base44, an AI-powered coding platform that enables users to create software and applications with natural language prompts, no coding experience necessary. The acquisition is a bold step because it reimagines what a content management system can be, enabling its users to do more with Wix than with any other platform.

Base44 provides an easy to use chat-based interface that enables users to create any kind of app without having to subscribe to third-party tools, all within the Wix platform. The acquisition is further establishes Wix as a leading platform for Internet entrepreneurship.

Maor Shlomo, CEO of Base44, commented:

“I honestly can’t think of a better fit. Wix is probably the only company that can help Base44 achieve the scale and distribution it needs while maintaining, if not accelerating, our product velocity. Our market is massive. It has the potential to replace entire software categories by enabling people to create software instead of buying it. Wix’s DNA – its customer obsession, innovation, and speed – perfectly aligns with ours, and its scale will catapult Base44 forward at exactly the right time.”

Avishai Abrahami, CEO and Co-founder of Wix observed:

“This acquisition marks a pivotal milestone in Wix’s commitment to transforming creation online. Maor and his team at Base44 bring cutting-edge technology, strong market penetration, and visionary leadership that seamlessly align with Wix’s dedication to enabling users at all levels of expertise to express their intent while intelligent agents manage execution.

Maor’s exceptional talent and innovative mindset will reinforce Wix’s mission to push the boundaries of AI-driven creation and accelerate the evolution of intuitive, intelligent tools that redefine how digital experiences are built and enjoyed.”

Featured Image by Shutterstock/Valery Brozhinsky

CMOs, The Time Is Now To Assign An AI Leader via @sejournal, @dannydenhard

There are three types of marketing leaders right now:

  1. The one worried about performance and just had enough time in leadership meetings to hear what everyone else’s opinion is on AI.
  2. The marketing leader who is having to firefight and has spoken to their team about AI and the implications.
  3. The marketing leader who has played with some AI tools and used a few prompts to see if it’s useful.

There should be a fourth who is planning for the future, trying to work out where AI sits in their organization and how to get ahead, so they do not get lost and can confidently say we have an internal owner.

Right now, I only know a handful of chief marketing officers who are taking it seriously enough.

The Challenge: Trust

The challenge for most is, “Who do I trust enough to do a great job in pulling the department, and often the non-technical parts of the company, on the AI journey?”

As someone who’s held both CMO and chief growth officer titles and now coaches C-Suite leaders and consults, I decided to dedicate the last six months to going deep into AI.

I have worked with companies in and around AI since 2022. However, over the last six months, we have seen AI transition from a set of tools and models to help, to starting to influence the reduction of team headcounts and being responsible for hiring freezes unless you can prove AI cannot do it first.

If you haven’t started, it will become a hotly discussed talking point in board and leadership meetings.

The promise of AI is exactly what everyone is looking for: productivity gains (not starting from zero every time), cost savings (on hiring, having to rely on data analysts or agencies), and the ability to leverage competitive advantages. We are seeing some of this play out.

The return on investment of going first and early will mean you are ahead of competitors, you will quickly understand the investment case, and you will be able to calculate ROI early.

The Solution: Two Strategic Approaches

Where to start? Most people struggle with where to start and where it makes sense to kickstart the AI agenda.

With coaching and consultancy clients, I offer two ways to tackle this:

1. Find Your AI Champion: Apply The Owner, Co-Owner, Collaborator Model To AI

You must have an owner – someone who will be there with the team and responsible for championing tech and tools and integrating them into their workflow.

When that owner says something is important, the teams treat it as such. You need an owner for when something breaks, they take control. This is a high-trust role with a lot of status attached.

You have co-owners, those who feel connected – the team members who don’t like being left behind but aren’t confident enough to own it themselves. You might say these are the ones who are likely on the fence about leaving.

Last are the collaborators, the team members who need to learn, need co-workers to help them develop and talk through what the tools have done and where they have likely used AI to get themselves out of missing a deadline or a situation where they’ve missed something.

2. Org Design/Org Redesign

This requires a strong and forward-thinking department leader who requires reshaping your teams to adapt to the new technology shift.

A proactive and visionary department leader is now essential. This leader must restructure teams to embrace and adapt to the significant shift towards new technologies.

You are not just shifting for hires and skills gaps, as most do. You are reshaping for the next two years.

You have to plan out how the next six, 12, and 18 months will change, move team members around, where there will be headcount reshuffles, and in this situation, a new technology that will reach all marketing disciplines.

The Opportunity: You will need to assign a natural long-term leader to AI. AI is not going away and will be the driving force in most businesses for the foreseeable future. You have to get ahead of when boards and C-Suites push you for your plan.

The Threat To Be Ahead Of: You must identify those who just will not naturally fit in the short to mid-term, and reshuffle your team members.

In this “do more with less” era, you will have to be at the front, leading and potentially losing headcount. AI has already seen mass layoffs, and this is unlikely to stop.

You will need to be ahead of the industry shifts. Being ahead is critical. Being close to your new owner or captain is pivotal.

The AI Owner

Who will be the owner of AI? And, how will you reshape your department?

Whether you are a marketing leader or a growth leader, you have to think about where these elements connect and who has the most exposure and muscle memory in big shifts.

Potential AI owners could come from several areas:

  • Social: Is it a marketer from social media? Being led by platforms to change their content types, to understand the subtle algorithmic changes, and in most cases, had to ramp up the quantity of output.
  • Search: Is it a search marketer? Is it a leader from organic search? If you have a strong SEO leader who understands other channels, you have someone who has seen huge changes in their industry. They have likely faced major algorithmic updates and had to adapt to a large number of changes since the early 2010s.
  • Growth: Are you a modern-day growth organization or an evolving marketing department? Do you have growth pros who look after paid, organic, and potential social?

You will know who fits best in your department. However, I predict it’s likely the search or growth team.

You need someone who is used to unpicking shifts – someone who can understand technical aspects and interface with product teams and engineers while teaching their colleagues.

For the top tier of SEO or search professionals, this is something they have had to do for years.

This is an opportunity for your team members, particularly in search, as Carl Hendy and I discussed in a recent podcast: It’s time to reset, mature, and take ownership from across different disciplines.

How To Find Your AI Leader

A core skill to look out for in the right candidate is having the ability to understand the importance of changes for the whole business and be able to hold their own with C-Suite executives.

The AI leader will have to hold strong, informed opinions based on knowledge of what is happening and how they assign budget and resources across the business.

Your AI lead will be a close colleague in many important meetings, so you trusting them and being able to learn and gain reverse mentorship will be essential.

The 90-Day Action Plan

Immediate: Week 1-2

  • Write your AI plan and create a dedicated presentation to guide the team’s success. Have a formalized kickoff: Start with the basics, explainers, examples of what success looks like, a set of approved tools and prompts, and workshops.
  • Assign a budget line for AI initiatives.
  • Address the department’s AI fears through transparent communication.
  • Launch formal AI kickoff workshop.

Short-Term: 30-90 Days

  • Department Problem Solve: List out all of your existing problems within your department and work through how you can identify existing tools, leverage, and build internal tools and processes with AI to address these.
  • Establish bi-weekly AI progress updates.
  • Begin cross-functional AI coordination and start to rebuild roadmaps.
  • Implement weekly team training and development sessions.

The Long-Term Plan: 6-18 Months

  • Develop an AI-focused hiring strategy and plan a reorg with this in mind.
  • Build executive presence for AI champions.
  • Create measurable ROI frameworks.

Remember, in an ever-evolving AI landscape, you can be on top of being proactive and be well prepared for when your business needs to be reactive.

Good luck on your AI journey!

More Resources:


Featured Image: DC Studio/Shutterstock

AIO Hurting Traffic? How To Identify True Loss With GA4, GSC & Rank Tracking [Webinar] via @sejournal, @lorenbaker

Wondering if AI Overviews (AIOs) are stealing your clicks?

Are these AI answer engines eating into our traffic, or just changing the shape of it?

Google’s AI Overviews now appear on up to 40% of search queries, but what impact are they really having?

Stop Guessing. How To Measure AIO’s Real Impact

Get the on-demand webinar, where we explore the three main tools that can help you:

In this tactical on-demand session, Tom Capper, Sr. Search Scientist at STAT, will walk you through a practical framework for assessing AIO impact using three tools you already rely on.

You’ll learn to pinpoint if, where, and how AIOs affect your traffic so that you can respond with clarity, not guesswork.

Start Measuring the Real Impact of AIOs on SERPs Today

Don’t rely on assumptions.

Grab this free on-demand webinar now to accompany the slides below; uncover if AIOs are actually hurting your traffic, and what to do about it.

Join Us For Our Next Webinar!

Lead Local SEO: How To AI-Proof Your Rankings With Reviews

Join Mél Attia, Sr. Marketing Manager at GatherUp, as she shows how consumer trust and AI updates are reshaping Local SEO, and how agencies can lead the way.

seo enhancements
How to find the perfect SEO-friendly WordPress theme

We’ve seen it happen so often. You have a great blog or site, and at some point, you decide to go for a new look and feel. There are a couple of things you’ll look at, usually in the order: layout/look and feel, usability, and optionally, room for advertising. If the theme meets your needs in all three of these points, you might download and install it. If that sounds familiar, this post describes how to find the perfect SEO-friendly WordPress theme!

Table of contents

Finding the right SEO-friendly WordPress theme

An SEO-friendly theme has quite a few things to take care of, and a lot of themes miss out on these. This overview should help to keep you out of trouble when you’re looking for a new theme. If you’re thinking of installing a new theme, please give the following points some thought. Keep in mind, your new theme should be accessible, compatible, customizable, integrable, and standards-compliant.

Define your needs

Whether you are in the market for a free theme, a premium theme, or want to hire a developer to build one especially for you, the first step is always the same: define your needs. Write down what the theme should do, now and in the future. You might not need an eCommerce option at this time, but what about in a year from now? What should your site look like? Which pages do you need? What types of content are you planning to publish? Once you have a clear picture of the requirements, you have a better chance of finding your dream theme.

Find a trusted reseller or developer. How’s the support?

Should you build a theme yourself? Or will a general free theme do? The discussion on whether a premium theme is better than a free theme continues to rage on. Both sides have their merits. There are loads of crappy free themes, but there are just as many crappy premium themes. What you should do is find a reseller or developer that you trust. Look for social proof; how many reviews does a theme get? Is there an active message board? When did it receive its last update?

While themes on WordPress.org undergo initial scrutiny for safety, it remains crucial to perform your own thorough checks. Also, vetting doesn’t mean they’re awesome. Theme resellers offer loads of premium themes in varying degrees of awesomeness. But just because you pay for them, doesn’t necessarily make them better than free themes. In addition to that, since you only receive the files when you pay for a theme, there’s no way to check the quality upfront. Despite social proof, it’s still a leap in the dark.

How flexible is the theme?

A static theme won’t do you any good when you want to change the page layout in a couple of months. Make sure to choose a theme that is flexible in its appearance as well as its functionality. Be sure that it supports blocks so you can use the block editor to fill the design. Don’t choose a design that screams for full-width images when you only need a well-presented place to write your poetry. Check what happens to a theme when you turn off all massive images; does it still function? And is it possible to change colors, fonts, and other visual elements? Many themes, like Total or GeneratePress, come with a number of demo examples that give you an idea of all the different styles they can handle.

Your SEO-friendly WordPress theme should have room for widgets, plus it should support featured images and offer multi-language support. Lots of themes have a page builder on board; these help you construct your bespoke layout. But, this is something you should be careful with because these could generate less than stellar code that hinders your SEO. Do check if your theme works well with site builders like Elementor. Also, modern themes like the Twenty Twenty-Five default theme work with block patterns that let you fine-tune your design.

Make sure your WordPress theme plays nicely with third-party plugins to boost your site’s functionality and SEO. Themes often come with built-in features, but these can sometimes clash with essential plugins. Make sure your chosen theme is flexible and well-coded to work smoothly with popular plugins like Yoast SEO, WooCommerce, and Elementor. This compatibility lets you enhance your site without dealing with conflicts or performance dips. Checking for plugin support makes sure that you can easily add features while keeping your site running securely and efficiently.

Which post and page templates does the theme support?

Another way to keep things flexible is for an SEO-friendly WordPress theme to offer multiple posts and page templates. That way, you could start off using a basic template with a main content area and a left sidebar, but have the flexibility to change to a full-width content area or one of the many other options. If a theme has only two choices, that might become problematic in the future. Pick a theme with enough sensible templates.

Does it function as a parent/child theme?

Parent and child themes are a great combo. If you use any of the theme frameworks like heavy-hitter Genesis, you know how powerful these are compared to regular themes. A child theme gets its functionality from a parent theme. So if you’re making changes to your child theme, the parent won’t see these. You won’t break the parent theme if you make a mistake. The same goes for updates; if you update your parent theme, which happens often, it won’t wipe the changes you’ve made to your theme because it’s a child and doesn’t contain the functionality.

Whether you need a theme framework depends on your needs. Almost all WordPress projects will benefit from a theme framework, but it might be overkill if you only need a tiny amount of its functionality and you know exactly what kind of theme you need.

Watch out for theme bloat

Many themes are bloated, which increases loading time. If the developer of a particular theme included everything but the kitchen sink, you might get a feature-complete product but an extremely complicated one as well. Try to find a theme that offers everything you need instead of everything there is. Your theme should be lean and mean.

Prioritize security

When choosing a WordPress theme, don’t overlook the importance of security. It’s important to select a theme that is well-maintained and regularly updated to fix vulnerabilities. Check if the theme has a solid security reputation by reading user reviews and checking update logs. Make sure it complies with secure coding standards and supports two-factor authentication and other security measures. Using themes directly from the official WordPress repository or trusted marketplaces adds an extra layer of assurance. Always test the theme with security plugins like Sucuri to identify potential issues before going live.

Check site speed and mobile-readiness

Your website should be mobile-friendly from the start. Its theme should load swiftly and provide an excellent page experience, reflected in strong Core Web Vitals scores. Opting for a lightweight, efficient theme could help you achieve this.

Begin by evaluating the theme’s responsiveness. Use tools like the Google Lighthouse to verify compatibility across various devices. Additionally, input the theme’s demo site URL into Google PageSpeed Insights to uncover any loading issues that might affect performance.

Remember, these tests offer a starting point, but they only provide part of the picture. For a complete assessment, test the theme’s speed on your actual server setup, as server performance can significantly influence load times.

Is the theme really SEO-friendly?

While Yoast SEO fixes a lot of WordPress’s SEO issues, a good theme helps a lot. Most WordPress themes will claim that they are SEO-friendly, but make sure to check them. One of the good examples is Twenty Twenty-Five, which offers a clean design that performs really well. Find out if the theme’s code is nice and clean or an intangible mess. Has it been updated recently? And will it be supported in the future? How many JavaScript libraries does the theme depend on? Does it support Schema.org structured data? If you’re eyeing a free theme, make sure there are no hidden links to the developer’s website, as this can hurt your SEO efforts. In general, keep Google’s Search Essentials documentation in mind when hunting for SEO-friendly WordPress themes.

Is the theme’s code valid?

Some theme authors are more designers than coders, and thus, they sometimes hack around until it finally looks the way they want without bothering to check whether the code they’ve written is valid HTML. If it’s not, current or future browsers might have issues rendering the content correctly. You can check whether the code is valid by using the W3C’s validator.

Test, test, and test again

Once you’ve chosen your favorite new SEO-friendly WordPress theme, it’s time to kick it into gear. Start with a development setup to test your new theme through and through. Run every type of test you can think of. This might be a security check with the Sucuri plugin or a theme check with the Theme Check plugin. Load your site with dummy data from wptest.io to see if every element is represented and functioning. Run pagespeed and mobile-friendliness tests to see if problems arise. Fix the issues, or find a new theme.

Bonus checks

That’s just to get you going. There’s a lot of stuff you can check before you install your brand-new theme. Start with these three checks, if you will:

Hooks

WordPress plugins use so-called “hooks” to be able to perform their designated tasks. These hooks allow, for instance, to add extra output, tracking codes, etc. A lot of issues with plugins will arise for you when a theme author forgets to add these hooks. This is how to check for them:

1. In header.php, it should have a small piece of PHP code that looks exactly like this wp_head(); or this do_action('wp_head');, usually just before a piece of HTML that looks like this: .

2. In footer.php, it should have another small piece of PHP like this wp_footer();, or this do_action('wp_footer');

3. In comments.php and/or comments-popup.php, there should be a piece of code like this: ID); ?>, just before the HTML tag.

Template files

Another wise thing to do when you’re changing themes is to compare theme files. If, for instance, your current theme has an author.php file, which contains the template for your author profiles, and your new one doesn’t have that, that might be an unpleasant surprise when you install the theme. The files you should be checking for in your old and new themes:

  • home.php: the homepage template.
  • single.php: the template for single posts.
  • page.php: the template for pages.
  • category.php: the template for category indexes.
  • author.php: the author template, used when someone wants to find all posts by a certain author.
  • date.php: the date template, used when someone tries to look at, for instance, a certain month of posts on your blog.
  • archive.php: this template is used when either category.php, author.php, or date.php isn’t there.
  • search.php: used when someone searches on your blog, a very important template to look at if you’re concerned about usability, and whether people can find posts on your blog.
  • 404.php is used when WordPress can’t find a certain post or page. It’s a very important template file to have!

How is your theme handling titles?

It’s essential to modernize how your theme manages page titles. While older practices involve directly altering the  tag in header.php, consider utilizing add_theme_support('title-tag'); in your theme’s functions.php. This setup allows WordPress and plugins like Yoast SEO to handle titles optimally, ensuring a flexible and SEO-friendly title structure.

// Add to your theme's functions.php
add_action('after_setup_theme', function() {
add_theme_support('title-tag');
});

Now, Yoast SEO can take care of all the titles. We have a great article on crafting good titles if you want to learn more.

A guide to finding SEO-friendly WordPress themes

If the theme you are looking at fits your goals and the points made in this article, you should be quite okay. For those of you with more tech skills, it’s also an option to go headless with WordPress if you want more flexibility. Good luck with your new theme!

Read more: Need help with WordPress? 10 tips to avoid common mistakes »

Yoast SEO WordPress Plugin Adds Support For LLMs.Txt via @sejournal, @martinibuster

Yoast announced the addition of llms.txt capability to both the premium and free versions of their SEO plugin. Users can now add llms.txt files to their sites to future-proof them for AI search engines.

LLMS.Txt

llms.txt is a proposal for a new standard that will enable large language models (LLMs) to access a publisher’s content in a way that is easy for LLMs. The main content is presented to LLMs without advertising and other page elements that target humans.

The proposed standard uses markdown in pages with the .md file name, duplicates of existing pages that only contain the main content. Google’s John Mueller has alluded to the inherently untrustworthiness of the proposed standard because there’s nothing to stop unscrupulous SEOs from adding whatever they want to the LLMs.txt web pages.

It simply makes more sense to just grab the content from the normal web pages. Additionally, LLMs aren’t currently looking for those pages and it’s quite likely that they will continue to use the normal web pages.

Yoast’s announcement states:

  • “Helps AI tools understand your site better: Guides large language models like ChatGPT and Gemini to your most relevant content.
  • Highlights your key content automatically: No need to decide what to include. Yoast SEO detects your most important and recently updated pages.
  • No technical setup required: The file is generated and refreshed weekly, no coding or manual work needed.
  • Future-proof your website for AI search: Make sure your site is ready for how people find information today, and tomorrow.
  • Built into Yoast SEO, free for everyone: Available in one click, no upgrade needed.”

Read the Yoast SEO announcement here:

Future proof your site for LLMs llms.txt

Featured Image by Shutterstock/Cagkan Sayin

When AIs bargain, a less advanced agent could cost you

The race to build ever larger AI models is slowing down. The industry’s focus is shifting toward agents—systems that can act autonomously, make decisions, and negotiate on users’ behalf.

But what would happen if both a customer and a seller were using an AI agent? A recent study put agent-to-agent negotiations to the test and found that stronger agents can exploit weaker ones to get a better deal. It’s a bit like entering court with a seasoned attorney versus a rookie: You’re technically playing the same game, but the odds are skewed from the start.

The paper, posted to arXiv’s preprint site, found that access to more advanced AI models —those with greater reasoning ability, better training data, and more parameters—could lead to consistently better financial deals, potentially widening the gap between people with greater resources and technical access and those without. If agent-to-agent interactions become the norm, disparities in AI capabilities could quietly deepen existing inequalities.

“Over time, this could create a digital divide where your financial outcomes are shaped less by your negotiating skill and more by the strength of your AI proxy,” says Jiaxin Pei, a postdoc researcher at Stanford University and one of the authors of the study.

In their experiment, the researchers had AI models play the roles of buyers and sellers in three scenarios, negotiating deals for electronics, motor vehicles, and real estate. Each seller agent received the product’s specs, wholesale cost, and retail price, with instructions to maximize profit. Buyer agents, in contrast, were given a budget, the retail price, and ideal product requirements and were tasked with driving the price down.

Each agent had some, but not all, relevant details. This setup mimics many real-world negotiation conditions, where parties lack full visibility into each other’s constraints or objectives.

The differences in performance were striking. OpenAI’s ChatGPT-o3 delivered the strongest overall negotiation results, followed by the company’s GPT-4.1 and o4-mini. GPT-3.5, which came out almost two years earlier and is the oldest model included in the study,  lagged significantly in both roles—it made the least money as the seller and spent the most as a buyer. DeepSeek R1 and V3 also performed well, particularly as sellers. Qwen2.5 trailed behind, though it showed more strength in the buyer role.

One notable pattern was that some agents often failed to close deals but effectively maximize profit in the sales they did make, while others completed more negotiations but settled for lower margins. GPT-4.1 and DeepSeek R1 struck the best balance, achieving both solid profits and high completion rates.

Beyond financial losses, the researchers found that AI agents could get stuck in prolonged negotiation loops without reaching an agreement—or end talks prematurely, even when instructed to push for the best possible deal. Even the most capable models were prone to these failures.

“The result was very surprising to us,” says Pei. “We all believe LLMs are pretty good these days, but they can be untrustworthy in high-stakes scenarios.”

The disparity in negotiation performance could be caused by a number of factors, says Pei. These include differences in training data and the models’ ability to reason and infer missing information. The precise causes remain uncertain, but one factor seems clear: Model size plays a significant role. According to the scaling laws of large language models, capabilities tend to improve with an increase in the number of parameters. This trend held true in the study: Even within the same model family, larger models were consistently able to strike better deals as both buyers and sellers.

This study is part of a growing body of research warning about the risks of deploying AI agents in real-world financial decision-making. Earlier this month, a group of researchers from multiple universities argued that LLM agents should be evaluated primarily on the basis of their risk profiles, not just their peak performance. Current benchmarks, they say, emphasize accuracy and return-based metrics, which measure how well an agent can perform at its best but overlook how safely it can fail. Their research also found that even top-performing models are more likely to break down under adversarial conditions.

The team suggests that in the context of real-world finances, a tiny weakness—even a 1% failure rate—could expose the system to systemic risks. They recommend that AI agents be “stress tested” before being put into practical use.

Hancheng Cao, an incoming assistant professor at Emory University, notes that the price negotiation study has limitations. “The experiments were conducted in simulated environments that may not fully capture the complexity of real-world negotiations or user behavior,” says Cao. 

Pei, the researcher, says researchers and industry practitioners are experimenting with a variety of strategies to reduce these risks. These include refining the prompts given to AI agents, enabling agents to use external tools or code to make better decisions, coordinating multiple models to double-check each other’s work, and fine-tuning models on domain-specific financial data—all of which have shown promise in improving performance.

Many prominent AI shopping tools are currently limited to product recommendation. In April, for example, Amazon launched “Buy for Me,” an AI agent that helps customers find and buy products from other brands’ sites if Amazon doesn’t sell them directly.

While price negotiation is rare in consumer e-commerce, it’s more common in business-to-business transactions. Alibaba.com has rolled out a sourcing assistant called Accio, built on its open-source Qwen models, that helps businesses find suppliers and research products. The company told MIT Technology Review it has no plans to automate price bargaining so far, citing high risk.

That may be a wise move. For now, Pei advises consumers to treat AI shopping assistants as helpful tools—not stand-ins for humans in decision-making.

“I don’t think we are fully ready to delegate our decisions to AI shopping agents,” he says. “So maybe just use it as an information tool, not a negotiator.”

Correction: We removed a line about agent deployment

What does it mean for an algorithm to be “fair”?

Back in February, I flew to Amsterdam to report on a high-stakes experiment the city had recently conducted: a pilot program for what it called Smart Check, which was its attempt to create an effective, fair, and unbiased predictive algorithm to try to detect welfare fraud. But the city fell short of its lofty goals—and, with our partners at Lighthouse Reports and the Dutch newspaper Trouw, we tried to get to the bottom of why. You can read about it in our deep dive published last week.

For an American reporter, it’s been an interesting time to write a story on “responsible AI” in a progressive European city—just as ethical considerations in AI deployments appear to be disappearing in the United States, at least at the national level. 

For example, a few weeks before my trip, the Trump administration rescinded Biden’s executive order on AI safety and DOGE began turning to AI to decide which federal programs to cut. Then, more recently, House Republicans passed a 10-year moratorium on US states’ ability to regulate AI (though it has yet to be passed by the Senate). 

What all this points to is a new reality in the United States where responsible AI is no longer a priority (if it ever genuinely was). 

But this has also made me think more deeply about the stakes of deploying AI in situations that directly affect human lives, and about what success would even look like. 

When Amsterdam’s welfare department began developing the algorithm that became Smart Check, the municipality followed virtually every recommendation in the responsible-AI playbook: consulting external experts, running bias tests, implementing technical safeguards, and seeking stakeholder feedback. City officials hoped the resulting algorithm could avoid causing the worst types of harm inflicted by discriminatory AI over nearly a decade. 

After talking to a large number of people involved in the project and others who would potentially be affected by it, as well as some experts who did not work on it, it’s hard not to wonder if the city could ever have succeeded in its goals when neither “fairness” nor even “bias” has a universally agreed-upon definition. The city was treating these issues as technical ones that could be answered by reweighting numbers and figures—rather than political and philosophical questions that society as a whole has to grapple with.

On the afternoon that I arrived in Amsterdam, I sat down with Anke van der Vliet, a longtime advocate for welfare beneficiaries who served on what’s called the Participation Council, a 15-member citizen body that represents benefits recipients and their advocates.

The city had consulted the council during Smart Check’s development, but van der Vliet was blunt in sharing the committee’s criticisms of the plans. Its members simply didn’t want the program. They had well-placed fears of discrimination and disproportionate impact, given that fraud is found in only 3% of applications.

To the city’s credit, it did respond to some of their concerns and make changes in the algorithm’s design—like removing from consideration factors, such as age, whose inclusion could have had a discriminatory impact. But the city ignored the Participation Council’s main feedback: its recommendation to stop development altogether. 

Van der Vliet and other welfare advocates I met on my trip, like representatives from the Amsterdam Welfare Union, described what they see as a number of challenges faced by the city’s some 35,000 benefits recipients: the indignities of having to constantly re-prove the need for benefits, the increases in cost of living that benefits payments do not reflect, and the general feeling of distrust between recipients and the government. 

City welfare officials themselves recognize the flaws of the system, which “is held together by rubber bands and staples,” as Harry Bodaar, a senior policy advisor to the city who focuses on welfare fraud enforcement, told us. “And if you’re at the bottom of that system, you’re the first to fall through the cracks.”

So the Participation Council didn’t want Smart Check at all, even as Bodaar and others working in the department hoped that it could fix the system. It’s a classic example of a “wicked problem,” a social or cultural issue with no one clear answer and many potential consequences. 

After the story was published, I heard from Suresh Venkatasubramanian, a former tech advisor to the White House Office of Science and Technology Policy who co-wrote Biden’s AI Bill of Rights (now rescinded by Trump). “We need participation early on from communities,” he said, but he added that it also matters what officials do with the feedback—and whether there is “a willingness to reframe the intervention based on what people actually want.” 

Had the city started with a different question—what people actually want—perhaps it might have developed a different algorithm entirely. As the Dutch digital rights advocate Hans De Zwart put it to us, “We are being seduced by technological solutions for the wrong problems … why doesn’t the municipality build an algorithm that searches for people who do not apply for social assistance but are entitled to it?” 

These are the kinds of fundamental questions AI developers will need to consider, or they run the risk of repeating (or ignoring) the same mistakes over and over again.

Venkatasubramanian told me he found the story to be “affirming” in highlighting the need for “those in charge of governing these systems”  to “ask hard questions … starting with whether they should be used at all.”

But he also called the story “humbling”: “Even with good intentions, and a desire to benefit from all the research on responsible AI, it’s still possible to build systems that are fundamentally flawed, for reasons that go well beyond the details of the system constructions.” 

To better understand this debate, read our full story here. And if you want more detail on how we ran our own bias tests after the city gave us unprecedented access to the Smart Check algorithm, check out the methodology over at Lighthouse. (For any Dutch speakers out there, here’s the companion story in Trouw.) Thanks to the Pulitzer Center for supporting our reporting. 

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

Puerto Rico’s power struggles

At first glance, it seems as if life teems around Carmen Suárez Vázquez’s little teal-painted house in the municipality of Guayama, on Puerto Rico’s southeastern coast.

The edge of the Aguirre State Forest, home to manatees, reptiles, as many as 184 species of birds, and at least three types of mangrove trees, is just a few feet south of the property line. A feral pig roams the neighborhood, trailed by her bumbling piglets. Bougainvillea blossoms ring brightly painted houses soaked in Caribbean sun.

Yet fine particles of black dust coat the windowpanes and the leaves of the blooming vines. Because of this, Suárez Vázquez feels she is stalked by death. The dust is in the air, so she seals her windows with plastic to reduce the time she spends wheezing—a sound that has grown as natural in this place as the whistling croak of Puerto Rico’s ubiquitous coquí frog. It’s in the taps, so a watercooler and extra bottles take up prime real estate in her kitchen. She doesn’t know exactly how the coal pollution got there, but she is certain it ended up in her youngest son, Edgardo, who died of a rare form of cancer.

And she believes she knows where it came from. Just a few minutes’ drive down the road is Puerto Rico’s only coal-fired power station, flanked by a mountain of toxic ash.

The plant, owned by the utility giant AES, has long plagued this part of Puerto Rico with air and water pollution. During Hurricane Maria in 2017, powerful winds and rain swept the unsecured pile—towering more than 12 stories high—out into the ocean and the surrounding area. Though the company had moved millions of tons of ash around Puerto Rico to be used in construction and landfill, much of it had stayed in Guayama, according to a 2018 investigation by the Centro de Periodismo Investigativo, a nonprofit investigative newsroom. Last October, AES settled with the US Environmental Protection Agency over alleged violations of groundwater rules, including failure to properly monitor wells and notify the public about significant pollution levels. 

Governor Jenniffer González-Colón has signed a new law rolling back the island’s clean-energy statute, completely eliminating its initial goal of 40% renewables by 2025.

Between 1990 and 2000—before the coal plant opened—Guayama had on average just over 103 cancer cases per year. In 2003, the year after the plant opened, the number of cancer cases in the municipality surged by 50%, to 167. In 2022, the most recent year with available data in Puerto Rico’s central cancer registry, cases hit a new high of 209—a more than 88% increase from the year AES started burning coal. A study by University of Puerto Rico researchers found cancer, heart disease, and respiratory illnesses on the rise in the area. They suggested that proximity to the coal plant may be to blame, describing the “operation, emissions, and handling of coal ash from the company” as “a case of environmental injustice.”

Seemingly everyone Suárez Vázquez knows has some kind of health problem. Nearly every house on her street has someone who’s sick, she told me. Her best friend, who grew up down the block, died of cancer a year ago, aged 55. Her mother has survived 15 heart attacks. Her own lungs are so damaged she requires a breathing machine to sleep at night, and she was forced to quit her job at a nearby pharmaceutical factory because she could no longer make it up and down the stairs without gasping for air. 

When we met in her living room one sunny March afternoon, she had just returned from two weeks in the hospital, where doctors were treating her for lung inflammation.

“In one community, we have so many cases of cancer, respiratory problems, and heart disease,” she said, her voice cracking as tears filled her eyes and she clutched a pillow on which a photo of Edgardo’s face was printed. “It’s disgraceful.”

Neighbors have helped her install solar panels and batteries on the roof of her home, helping to offset the cost of running her air conditioner, purifier, and breathing machine. They also allow the devices to operate even when the grid goes down—as it still does multiple times a week, nearly eight years after Hurricane Maria laid waste to Puerto Rico’s electrical infrastructure.

Carmen Suárez Vázquez clutches a pillow with a portraits of her daughter and late son Edgardo. When this photograph was taken, she had just been released from the hospital, where she underwent treatment for lung inflammation.
ALEXANDER C. KAUFMAN

Suárez Vázquez had hoped that relief would be on the way by now. That the billions of dollars Congress designated for fixing the island’s infrastructure would have made solar panels ubiquitous. That AES’s coal plant, which for nearly a quarter century has supplied up to 20% of the old, faulty electrical grid’s power, would be near its end—its closure had been set for late 2027. That the Caribbean’s first virtual power plant—a decentralized network of solar panels and batteries that could be remotely tapped into and used to balance the grid like a centralized fuel-burning station—would be well on its way to establishing a new model for the troubled island. 

Puerto Rico once seemed to be on that path. In 2019, two years after Hurricane Maria sent the island into the second-longest blackout in world history, the Puerto Rican government set out to make its energy system cheaper, more resilient, and less dependent on imported fossil fuels, passing a law that set a target of 100% renewable energy by 2050. Under the Biden administration, a gas company took charge of Puerto Rico’s power plants and started importing liquefied natural gas (LNG), while the federal government funded major new solar farms and programs to install panels and batteries on rooftops across the island. 

Now, with Donald Trump back in the White House and his close ally Jenniffer González-Colón serving as Puerto Rico’s governor, America’s largest unincorporated territory is on track for a fossil-fuel resurgence. The island quietly approved a new gas power plant in 2024, and earlier this year it laid out plans for a second one. Arguing that it was the only way to avoid massive blackouts, the governor signed legislation to keep Puerto Rico’s lone coal plant open for at least another seven years and potentially more. The new law also rolls back the island’s clean-energy statute, completely eliminating its initial goals of 40% renewables by 2025 and 60% by 2040, though it preserves the goal of reaching 100% by 2050. At the start of April, González-Colón issued an executive order fast-­tracking permits for new fossil-fuel plants. 

In May the new US energy secretary, Chris Wright, redirected $365 million in federal funds the Biden administration had committed to solar panels and batteries to instead pay for “practical fixes and emergency activities” to improve the grid.

It’s all part of a desperate effort to shore up Puerto Rico’s grid before what’s forecast to be a hotter-than-­average summer—and highlights the thorny bramble of bureaucracy and business deals that prevents the territory’s elected government from making progress on the most basic demand from voters to restore some semblance of modern American living standards.

Puerto Ricans already pay higher electricity prices than most other American citizens, and Luma Energy, the private company put in charge of selling and distributing power from the territory’s state-owned generating stations four years ago, keeps raising rates despite ongoing outages. In April González-Colón moved to crack down on Luma, whose contract she pledged to cancel on the campaign trail, though it remains unclear how she will find a suitable replacement. 

Alberto Colón, a retired public school administrator who lives across the street from Suárez Vázquez, helped install her solar panels. Here, he poses next to his own batteries.
ALEXANDER C. KAUFMAN
close up of a hand holding a paper towel with a gritty black streak on it
Colón shows some of the soot wiped from the side of his house.
ALEXANDER C. KAUFMAN

At the same time, she’s trying to enforce a separate contract with New Fortress Energy, the New York–based natural-gas company that gained control of Puerto Rico’s state-owned power plants in a hotly criticized privatization deal in 2023—all while the company is pushing to build more gas-fired generating stations to increase the island’s demand for liquefied natural gas. Just weeks before the coal plant won its extension, New Fortress secured a deal to sell even more LNG to Puerto Rico—despite the company’s failure to win federal permits for a controversial import terminal in San Juan Bay, already in operation, that critics fear puts the most densely populated part of the island at major risk, with no real plan for what to do if something goes wrong.

Those contracts infamously offered Luma and New Fortress plenty of carrots in the form of decades-long deals and access to billions of dollars in federal reconstruction money, but few sticks the Puerto Rican government could wield against them when ratepayers’ lights went out and prices went up. In a sign of how dim the prospects for improvement look, New Fortress even opted in March to forgo nearly $1 billion in performance bonuses over the next decade in favor of getting $110 million in cash up front. Spending any money to fix the problems Puerto Rico faces, meanwhile, requires approval from an unelected fiscal control board that Congress put in charge of the territory’s finances during a government debt crisis nearly a decade ago, further reducing voters’ ability to steer their own fate. 

AES declined an interview with MIT Technology Review and did not respond to a detailed list of emailed questions. Neither New Fortress nor a spokesperson for González-Colón responded to repeated requests for comment. 

“I was born on Puerto Rico’s Emancipation Day, but I’m not liberated because that coal plant is still operating,” says Alberto Colón, 75, a retired public school administrator who lives across the street from Suárez Vázquez, referring to the holiday that celebrates the abolition of slavery in what was then a Spanish colony. “I have sinus problems, and I’m lucky. My wife has many, many health problems. It’s gotten really bad in the last few years. Even with screens in the windows, the dust gets into the house.”

El problema es la colonia

What’s happening today in Puerto Rico began long before Hurricane Maria made landfall over the territory, mangling its aging power lines like a metal Slinky in a blender. 

The question for anyone who visits this place and tries to understand why things are the way they are is: How did it get this bad? 

The complicated answer is a story about colonialism, corruption, and the challenges of rebuilding an island that was smothered by debt—a direct consequence of federal policy changes in the 1990s. Although they are citizens, Puerto Ricans don’t have votes that count in US presidential elections. They don’t typically pay US federal income taxes, but they also don’t benefit fully from federal programs, receiving capped block grants that frequently run out. Today the island has even less control over its fate than in years past and is entirely beholden to a government—the US federal government—that its 3.2 million citizens had no part in choosing.

What’s happening today in Puerto Rico began long before Hurricane Maria made landfall over the territory, mangling its aging power lines like a metal Slinky in a blender.

A phrase that’s ubiquitous in graffiti on transmission poles and concrete walls in the towns around Guayama and in the artsy parts of San Juan places the blame deep in history: El problema es la colonia—the problem is the colony.

By some measures, Puerto Rico is the world’s oldest colony, officially established under the Spanish crown in 1508. The US seized the island as a trophy in 1898 following its victory in the Spanish-American War. In the grips of an expansionist quest to place itself on par with European empires, Washington pried Puerto Rico, Guam, and the Philippines away from Madrid, granting each territory the same status then afforded to the newly annexed formerly independent kingdom of Hawaii. Acolytes of President William McKinley saw themselves as accepting what the Indian-born British poet Rudyard Kipling called “the white man’s burden”—the duty to civilize his subjects.

Although direct military rule lasted just two years, Puerto Ricans had virtually no say over the civil government that came to power in 1900, in which the White House appointed the governor. That explicitly colonial arrangement ended only in 1948 with the first island-wide elections for governor. Even then, the US instituted a gag law just months before the election that would remain in effect for nearly a decade, making agitation for independence illegal. Still, the following decades were a period of relative prosperity for Puerto Rico. Money from President Franklin D. Roosevelt’s New Deal had modernized the island’s infrastructure, and rural farmers flocked to bustling cities like Ponce and San Juan for jobs in the burgeoning manufacturing sector. The pharmaceutical industry in particular became a major employer. By the start of the 21st century, Pfizer’s plant in the Puerto Rican town of Barceloneta was the largest Viagra manufacturer in the world.

But in 1996, Republicans in Congress struck a deal with President Bill Clinton to phase out federal tax breaks that had helped draw those manufacturers to Puerto Rico. As factories closed, the jobs that had built up the island’s middle class disappeared. To compensate, the government hired more workers as teachers and police officers, borrowing money on the bond market to pay their salaries and make up for the drop in local tax revenue. Puerto Rico’s territorial status meant it could not legally declare bankruptcy, and lenders assumed the island enjoyed the full backing of the US Treasury. Before long, it was known on Wall Street as the “belle of the bond markets.” By the mid-2010s, however, the bond debt had grown to $74 billion, and a $49 billion chasm had opened between the amount the government needed to pay public pensions and the money it had available. It began shedding more and more of its payroll. 

The Puerto Rico Electric Power Authority (PREPA), the government-­owned utility, had racked up $9 billion in debt. Unlike US states, which can buy electricity from neighboring grids and benefit from interstate gas pipelines, Puerto Rico needed to import fuel to run its power plants. The majority of that power came from burning oil, since petroleum was easier to store for long periods of time. But oil, and diesel in particular, was expensive and pushed the utility further and further into the red.

By 2016, Puerto Rico could no longer afford to pay its bills. Since the law that gave the US jurisdiction over nonstate territories made Puerto Rico a “possession” of Congress, it fell on the federal legislature—in which the island’s elected delegate had no vote—to decide what to do. Congress passed the Puerto Rico Oversight, Management, and Economic Stability Act—shortened to PROMESA, or “promise” in Spanish. It established a fiscal control board appointed by the White House, with veto power over all spending by the island’s elected government. The board had authority over how the money the territorial government collected in taxes and utility bills could be used. It was a significant shift in the island’s autonomy. 

“The United States cannot continue its state of denial by failing to accept that its relationship with its citizens who reside in Puerto Rico is an egregious violation of their civil rights,” Juan R. Torruella, the late federal appeals court judge, wrote in a landmark paper in the Harvard Law Review in 2018, excoriating the legislation as yet another “colonial experiment.” “The democratic deficits inherent in this relationship cast doubt on its legitimacy, and require that it be frontally attacked and corrected ‘with all deliberate speed.’” 

Hurricane Maria struck a little over a year after PROMESA passed, and according to official figures, killed dozens. That proved to be just the start, however. As months ground on without any electricity and more people were forced to go without medicine or clean water, the death toll rose to the thousands. It would be 11 months before the grid would be fully restored, and even then, outages and appliance-­destroying electrical surges were distressingly common.

The spotty service wasn’t the only defining characteristic of the new era after Puerto Rico’s great blackout. The fiscal control board—which critics pejoratively referred to as “la junta,” using a term typically reserved for Latin America’s most notorious military dictatorships—saw privatization as the best path to solvency for the troubled state utility.

In 2020, the board approved a deal for Luma Energy—a joint venture between Quanta Services, a Texas-based energy infrastructure company, and its Canadian rival ATCO—to take over the distribution and sale of electricity in Puerto Rico. The contract was awarded through a process that clean-energy and anticorruption advocates said lacked transparency and delivered an agreement with few penalties for poor service. It was almost immediately mired in controversy.

A deadly diagnosis

Until that point, life was looking up for Suárez Vázquez. Her family had emerged from the aftermath of Maria without any loss of life. In 2019, her children were out of the house, and her youngest son, Edgardo, was studying at an aviation school in Ceiba, roughly two hours northeast of Guayama. He excelled. During regular health checks at the school, Edgardo was deemed fit. Gift bags started showing up at the house from American Airlines and JetBlue.

“They were courting him,” Suárez Vázquez says. “He was going to graduate with a great job.”

That summer of 2019, however, Edgardo began complaining of abdominal pain. He ignored it for a few months but promised his mother he would go to the doctor to get it checked out. On September 23, she got a call from her godson, a radiologist at the hospital. Not wanting to burden his anxious mother, Edgardo had gone to the hospital alone at 3 a.m., and tests had revealed three tumors entwined in his intestines.

So began a two-year battle with a form of cancer so rare that doctors said Edgardo’s case was one of only a few hundred worldwide. He gave up on flight school and took a job at the pharmaceutical factory with his parents. Coworkers raised money to help the family afford flights and stays to see specialists in other parts of Puerto Rico and then in Florida. Edgardo suspected the cause was something in the water. Doctors gave him inconclusive answers; they just wanted to study him to understand the unusual tumors. He got water-testing kits and discovered that the taps in their home were laden with high amounts of heavy metals typically found in coal ash. 

Ewing’s sarcoma tumors occur at a rate of about one in one million cancer diagnoses in the US each year. What Edgardo had—extraskeletal Ewing’s sarcoma, in which tumors form in soft tissue rather than bone—is even rarer. 

As a result, there’s scant research on what causes that kind of cancer. While the National Institutes of Health have found “no well-established association between Ewing sarcoma and environmental risk factors,” researchers cautioned in a 2024 paper that findings have been limited to “small, retrospective, case-control studies.”

Dependable sun

The push to give control over the territory’s power system to private companies with fossil-fuel interests ignored the reality that for many Puerto Ricans, rooftop solar panels and batteries were among the most dependable options for generating power after the hurricane. Solar power was relatively affordable, especially as Luma jacked up what were already some of the highest electricity rates in the US. It also didn’t lead to sudden surges that fried refrigerators and microwaves. Its output was as predictable as Caribbean sunshine.

But rooftop panels could generate only so much electricity for the island’s residents. Last year, when the Biden administration’s Department of Energy conducted its PR100 study into how Puerto Rico could meet its legally mandated goals of 100% renewable power by the middle of the century, the research showed that the bulk of the work would need to be done by big, utility-scale solar farms. 

worker crouching on a roof to install solar panels
Nearly 160,000 households—roughly 13% of the population—have solar panels, and 135,000 of them also have batteries. Of those, just 8,500 have enrolled in a pilot project aimed at providing backup power to the grid.
GDA VIA AP IMAGES

With its flat lands once used to grow sugarcane, the southeastern part of Puerto Rico proved perfect for devoting acres to solar production. Several enormous solar farms with enough panels to generate hundreds of megawatts of electricity were planned for the area, including one owned by AES. But early efforts to get the projects off the ground stumbled once the fiscal oversight board got involved. The solar farms that Puerto Rico’s energy regulators approved ultimately faced rejection by federal overseers who complained that the panels in areas near Guayama could be built even more cheaply.

In a September 2023 letter to PREPA vetoing the projects, the oversight board’s lawyer chastised the Puerto Rico Energy Bureau, a government regulatory body whose five commissioners are appointed by the governor, for allowing the solar developers to update contracts to account for surging costs from inflation that year. It was said to have created “a precedent that bids will be renegotiated, distorting market pricing and creating litigation risk.” In another letter to PREPA, in January 2024, the board agreed to allow projects generating up to 150 megawatts of power to move forward, acknowledging “the importance of developing renewable energy projects.”

“There’s no trust. That creates risk. Risk means more money. Things get more expensive. It’s disappointing, but that’s why we weren’t able to build large things.”

But that was hardly enough power to provide what the island needed, and critics said the agreement was guilty of the very thing the board accused Puerto Rican regulators of doing: discrediting the permitting process in the eyes of investors.

The Puerto Rico Energy Bureau “negotiated down to the bone to very inexpensive prices” on a handful of projects, says Javier Rúa-Jovet, the chief policy officer at the Solar & Energy Storage Association of Puerto Rico. “Then the fiscal board—in my opinion arbitrarily—canceled 450 megawatts of projects, saying they were expensive. That action by the fiscal board was a major factor in predetermining the failure of all future large-scale procurements,” he says.

When the independence of the Puerto Rican regulator responsible for issuing and judging the requests for proposals is overruled, project developers no longer believe that anything coming from the government’s local experts will be final. “There’s no trust,” says Rúa-Jovet. “That creates risk. Risk means more money. Things get more expensive. It’s disappointing, but that’s why we weren’t able to build large things.”

That isn’t to say the board alone bears all responsibility. An investigation released in January by the Energy Bureau blamed PREPA and Luma for causing “deep structural inefficiencies” that “ultimately delayed progress” toward Puerto Rico’s renewables goals.

The finding only further reinforced the idea that the most trustworthy path to steady power would be one Puerto Ricans built themselves. At the residential scale, Rúa-Jovet says, solar and batteries continue to be popular. Nearly 160,000 households—roughly 13% of the population—have solar panels, and 135,000 of them also have batteries. Of those, just 8,500 households are enrolled in the pilot virtual power plant, a collection of small-scale energy resources that have aggregated together and coordinated with grid operations. During blackouts, he says, Luma can tap into the network of panels and batteries to back up the grid. The total generation capacity on a sunny day is nearly 600 megawatts—eclipsing the 500 megawatts that the coal plant generates. But the project is just at the pilot stage. 

The share of renewables on Puerto Rico’s power grid hit 7% last year, up one percentage point from 2023. That increase was driven primarily by rooftop solar. Despite the growth and dependability of solar, in December Puerto Rican regulators approved New Fortress’s request to build an even bigger gas power station in San Juan, which is currently scheduled to come online in 2028.

“There’s been a strong grassroots push for a decentralized grid,” says Cathy Kunkel, a consultant who researches Puerto Rico for the Institute for Energy Economics and Financial Analysis and lived in San Juan until recently. She’d be more interested, she adds, if the proposals focused on “smaller-­scale natural-gas plants” that could be used to back up renewables, but “what they’re talking about doing instead are these giant gas plants in the San Juan metro area.” She says, “That’s just not going to provide the kind of household level of resilience that people are demanding.”

What’s more, New Fortress has taken a somewhat unusual approach to storing its natural gas. The company has built a makeshift import terminal next to a power plant in a corner of San Juan Bay by semipermanently mooring an LNG tanker, a vessel specifically designed for transport. Since Puerto Rico has no connections to an interstate pipeline network, New Fortress argued that the project didn’t require federal permits under the law that governs most natural-gas facilities in the US. As a result, the import terminal did not get federal approval for a safety plan in case of an accident like the ones that recently rocked Texas and Louisiana.

Skipping the permitting process also meant skirting public hearings, spurring outrage from Catholic clergy such as Lissette Avilés-Ríos, an activist nun who lives in the neighborhood next to the import terminal and who led protests to halt gas shipments. “Imagine what a hurricane like Maria could do to a natural-gas station like that,” she told me last summer, standing on the shoreline in front of her parish and peering out on San Juan Bay. “The pollution impact alone would be horrible.”

The shipments ultimately did stop for a few months—but not because of any regulatory enforcement. In fact, it was in violation of its contract that New Fortress abruptly cut off shipments when the price of natural gas skyrocketed globally in late 2021. When other buyers overseas said they’d pay higher prices for LNG than the contract in Puerto Rico guaranteed, New Fortress announced with little notice that it would cease deliveries for six months while upgrading its terminal.

“The government justifies extending coal plants because they say it’s the cheapest form of energy.”

Aldwin José Colón, 51, who lives across the street from Suárez Vázquez

The missed shipments exemplified the challenges in enforcing Puerto Rico’s contracts with the private companies that control its energy system and highlighted what Gretchen Sierra-Zorita, former president Joe Biden’s senior advisor on Puerto Rico and the territories, called the “troubling” fact that the same company operating the power plants is selling itself the fuel on which they run—disincentivizing any transition to alternatives.

“Territories want to diversify their energy sources and maximize the use of abundant solar energy,” she told me. “The Trump administration’s emphasis on domestic production of fossil fuels and defunding climate and clean-­energy initiatives will not provide the territories with affordable energy options they need to grow their economies, increase their self-sufficiency, and take care of their people.”

Puerto Rico’s other energy prospects are limited. The Energy Department study determined that offshore wind would be too expensive. Nuclear is also unlikely; the small modular reactors that would be the most realistic way to deliver nuclear energy here are still years away from commercialization and would likely cost too much for PREPA to purchase. Moreover, nuclear power would almost certainly face fierce opposition from residents in a disaster-prone place that has already seen how willing the federal government is to tolerate high casualty rates in a catastrophe. That leaves little option, the federal researchers concluded, beyond the type of utility-scale solar projects the fiscal oversight board has made impossible to build.

“Puerto Rico has been unsuccessful in building large-scale solar and large-scale batteries that could have substituted [for] the coal plant’s generation. Without that new, clean generation, you just can’t turn off the coal plant without causing a perennial blackout,” Rúa-Jovet says. “That’s just a physical fact.”

The lowest-cost energy, depending on who’s paying the price

The AES coal plant does produce some of the least expensive large-scale electricity currently available in Puerto Rico, says Cate Long, the founder of Puerto Rico Clearinghouse, a financial research service targeted at the island’s bondholders. “From a bondholder perspective, [it’s] the lowest cost,” she explains. “From the client and user perspective, it’s the lowest cost. It’s always been the cheapest form of energy down there.” 

The issue is that the price never factors in the cost to the health of people near the plant. 

“The government justifies extending coal plants because they say it’s the cheapest form of energy,” says Aldwin José Colón, 51, who lives across the street from Suárez Vázquez. He says he’s had cancer twice already.

On an island where nearly half the population relies on health-care programs paid for by frequently depleted Medicaid block grants, he says, “the government ends up paying the expense of people’s asthma and heart attacks, and the people just suffer.” 

On December 2, 2021, at 9:15 p.m., Edgardo died in the hospital. He was 25 years old. “So many people have died,” Suárez Vázquez told me, choking back tears. “They contaminated the water. The soil. The fish. The coast is black. My son’s insides were black. This never ends.” 

Customers sit inside a restaurant lit by battery-powered lanterns. On April 16, as this story was being edited, all of Puerto Rico’s power plants went down in an island-wide outage triggered by a transmission line failure.
AP PHOTO/ALEJANDRO GRANADILLO

Nor do the blackouts. At 12:38 p.m. on April 16, as this story was being edited, all of Puerto Rico’s power plants went down in an island-wide outage triggered by a transmission line failure. As officials warned that the blackout would persist well into the next day, Casa Pueblo, a community group that advocates for rooftop solar, posted an invitation on X to charge phones and go online under its outdoor solar array near its headquarters in a town in the western part of Puerto Rico’s central mountain range.

“Come to the Solar Forest and the Energy Independence Plaza in Adjuntas,” the group beckoned, “where we have electricity and internet.” 

Alexander C. Kaufman is a reporter who has covered energy, climate change, pollution, business, and geopolitics for more than a decade.

AI copyright anxiety will hold back creativity

Last fall, while attending a board meeting in Amsterdam, I had a few free hours and made an impromptu visit to the Van Gogh Museum. I often steal time for visits like this—a perk of global business travel for which I am grateful. Wandering the galleries, I found myself before The Courtesan (after Eisen), painted in 1887. Van Gogh had based it on a Japanese woodblock print by Keisai Eisen, which he encountered in the magazine Paris Illustré. He explicitly copied and reinterpreted Eisen’s composition, adding his own vivid border of frogs, cranes, and bamboo.

As I stood there, I imagined the painting as the product of a generative AI model prompted with the query How would van Gogh reinterpret a Japanese woodblock in the style of Keisai Eisen? And I wondered: If van Gogh had used such an AI tool to stimulate his imagination, would Eisen—or his heirs—have had a strong legal claim?  If van Gogh were working today, that might be the case. Two years ago, the US Supreme Court found that Andy Warhol had infringed upon the photographer Lynn Goldsmith’s copyright by using her photo of the musician Prince for a series of silkscreens. The court said the works were not sufficiently transformative to constitute fair use—a provision in the law that allows for others to make limited use of copyrighted material.

A few months later, at the Museum of Fine Arts in Boston, I visited a Salvador Dalí exhibition. I had always thought of Dalí as a true original genius who conjured surreal visions out of thin air. But the show included several Dutch engravings, including Pieter Bruegel the Elder’s Seven Deadly Sins (1558), that clearly influenced Dalí’s 8 Mortal Sins Suite (1966). The stylistic differences are significant, but the lineage is undeniable. Dalí himself cited Bruegel as a surrealist forerunner, someone who tapped into the same dream logic and bizarre forms that Dalí celebrated. Suddenly, I was seeing Dalí not just as an original but also as a reinterpreter. Should Bruegel have been flattered that Dalí built on his work—or should he have sued him for making it so “grotesque”?

During a later visit to a Picasso exhibit in Milan, I came across a famous informational diagram by the art historian Alfred Barr, mapping how modernist movements like Cubism evolved from earlier artistic traditions. Picasso is often held up as one of modern art’s most original and influential figures, but Barr’s chart made plain the many artists he drew from—Goya, El Greco, Cézanne, African sculptors. This made me wonder: If a generative AI model had been fed all those inputs, might it have produced Cubism? Could it have generated the next great artistic “breakthrough”?

These experiences—spread across three cities and centered on three iconic artists—coalesced into a broader reflection I’d already begun. I had recently spoken with Daniel Ek, the founder of Spotify, about how restrictive copyright laws are in music. Song arrangements and lyrics enjoy longer protection than many pharmaceutical patents. Ek sits at the leading edge of this debate, and he observed that generative AI already produces an astonishing range of music. Some of it is good. Much of it is terrible. But nearly all of it borrows from the patterns and structures of existing work.

Musicians already routinely sue one another for borrowing from previous works. How will the law adapt to a form of artistry that’s driven by prompts and precedent, built entirely on a corpus of existing material?

And the questions don’t stop there. Who, exactly, owns the outputs of a generative model? The user who crafted the prompt? The developer who built the model? The artists whose works were ingested to train it? Will the social forces that shape artistic standing—critics, curators, tastemakers—still hold sway? Or will a new, AI-era hierarchy emerge? If every artist has always borrowed from others, is AI’s generative recombination really so different? And in such a litigious culture, how long can copyright law hold its current form? The US Copyright Office has begun to tackle the thorny issues of ownership and says that generative outputs can be copyrighted if they are sufficiently human-authored. But it is playing catch-up in a rapidly evolving field. 

Different industries are responding in different ways. The Academy of Motion Picture Arts and Sciences recently announced that filmmakers’ use of generative AI would not disqualify them from Oscar contention—and that they wouldn’t be required to disclose when they’d used the technology. Several acclaimed films, including Oscar winner The Brutalist, incorporated AI into their production processes.

The music world, meanwhile, continues to wrestle with its definitions of originality. Consider the recent lawsuit against Ed Sheeran. In 2016, he was sued by the heirs of Ed Townsend, co-writer of Marvin Gaye’s “Let’s Get It On,” who claimed that Sheeran’s “Thinking Out Loud” copied the earlier song’s melody, harmony, and rhythm. When the case finally went to trial in 2023, Sheeran brought a guitar to the stand. He played the disputed four-chord progression—I–iii–IV–V—and wove together a mash-up of songs built on the same foundation. The point was clear: These are the elemental units of songwriting. After a brief deliberation, the jury found Sheeran not liable.

Reflecting after the trial, Sheeran said: “These chords are common building blocks … No one owns them or the way they’re played, in the same way no one owns the colour blue.”

Exactly. Whether it’s expressed with a guitar, a paintbrush, or a generative algorithm, creativity has always been built on what came before.

I don’t consider this essay to be great art. But I should be transparent: I relied extensively on ChatGPT while drafting it. I began with a rough outline, notes typed on my phone in museum galleries, and transcripts from conversations with colleagues. I uploaded older writing samples to give the model a sense of my voice. Then I used the tool to shape a draft, which I revised repeatedly—by hand and with help from an editor—over several weeks.

There may still be phrases or sentences in here that came directly from the model. But I’ve iterated so much that I no longer know which ones. Nor, I suspect, could any reader—or any AI detector. (In fact, Grammarly found that 0% of this text appeared to be AI-generated.)

Many people today remain uneasy about using these tools. They worry it’s cheating, or feel embarrassed to admit that they’ve sought such help. I’ve moved past that. I assume all my students at Harvard Business School are using AI. I assume most academic research begins with literature scanned and synthesized by these models. And I assume that many of the essays I now read in leading publications were shaped, at least in part, by generative tools.

Why? Because we are professionals. And professionals adopt efficiency tools early. Generative AI joins a long lineage that includes the word processor, the search engine, and editing tools like Grammarly. The question is no longer Who’s using AI? but Why wouldn’t you?

I recognize the counterargument, notably put forward by Nicholas Thompson, CEO of the Atlantic: that content produced with AI assistance should not be eligible for copyright protection, because it blurs the boundaries of authorship. I understand the instinct. AI recombines vast corpora of preexisting work, and the results can feel derivative or machine-like.

But when I reflect on the history of creativity—van Gogh reworking Eisen, Dalí channeling Bruegel, Sheeran defending common musical DNA—I’m reminded that recombination has always been central to creation. The economist Joseph Schumpeter famously wrote that innovation is less about invention than “the novel reassembly of existing ideas.” If we tried to trace and assign ownership to every prior influence, we’d grind creativity to a halt.

From the outset, I knew the tools had transformative potential. What I underestimated was how quickly they would become ubiquitous across industries and in my own daily work.

Our copyright system has never required total originality. It demands meaningful human input. That standard should apply in the age of AI as well. When people thoughtfully engage with these models—choosing prompts, curating inputs, shaping the results—they are creating. The medium has changed, but the impulse remains the same: to build something new from the materials we inherit.


Nitin Nohria is the George F. Baker Jr. Professor at Harvard Business School and its former dean. He is also the chair of Thrive Capital, an early investor in several prominent AI firms, including OpenAI.

MIT Technology Review’s editorial guidelines state that generative AI should not be used to draft articles unless the article is meant to illustrate the capabilities of such tools and its use is clearly disclosed.