u/Any-Bet9069

Let me start with a disclaimer, because the hype around this topic is getting a bit out of hand. Unlike many others here, I don't think that generative engine optimization, GEO , AEO or whatever you call it- is some magical new discipline.

There is a huge overlap with traditional SEO. If your technical SEO is garbage and your content is thin, no AI hack is going to save you. But it is NOT 100% overlap.

That 10% to 20% difference between SEO and GEO is important and risky enough for a brand like ours to seriously look at the nuances of how to build trust and authority with AI.

My team has spent the last few months testing almost a dozen tools to figure out how to really improve AI visibility of a brand. What we realized is that 90% of the tools out there are just expensive dashboards. They scrape LLM outputs, put them in a pretty pie chart, and tell you that you are losing visibility, ok I get it, marketers wnat to know and always hungry for data (even when it becomes counterproductive). But what do I actually do about it - there is a huge difference between data and actionable insights.

I think that to actually move the needle, you need a holistic approach that covers both content generation and technical infrastructure. You have to control what the bot reads and how the bot behaves when it hits your server.

Here is a breakdown of the stack we tested, what we kept, what we threw out, and what actually worked for us.

1 - The Legacy Giants (Ahrefs / Semrush)
I have to include them because you can’t ignore them. Yes, they are all releasing AI Search features and no, they aren't there yet. It feels to me that they are doing it because the demand is there and they have to add some features anyway. I personally wouldn’t use them for this.
Pros:

• You still need them for backlink profiles and traditional search volume (Google and SEO is very far from dead, and traditional SEO still heavily informs LLM training data).
• Great site audit tools for basic technical hygiene (broken links, toxic domains).
• Cons:
• They are trying to retrofit an old paradigm (10 blue links, search volume) onto a new paradigm (RAG, conversational answers).
• They don't track how AI bots fetch your data in real time, let alone optimize for it.
• Bottom line: Keep your subscription, but don't expect their new features to solve your generative engine optimization problems anytime soon.

2 - Writesonic (and similar AI content factories)
We looked at Writesonic, Jasper, and a few others for the content side of the play. If you want AI visibility, you obviously need entities and topical authority. Writesonic is a beast for content velocity. It’s moved way past just being a basic GPT wrapper and has some genuinely good SEO features built into the workflow now.

Pros:

• Incredible for scaling up glossary pages, FAQs, and top of funnel content.
• The brand voice training actually works pretty well if you feed it good guidelines.
• Very intuitive UI; you can train a junior marketer on it in an hour.
• Good integrations with WordPress and other CMS platforms.
• Cons:
• It is purely a content play. It does absolutely nothing for your technical architecture.
• Just writing AI friendly content isn't enough if the LLM bots can't parse your site properly when they fetch it.
• You still have to figure out what to write on your own. It doesn't tell you where your visibility gaps are in Perplexity or Claude.
• Bottom line: If your only bottleneck is writing words on a page, it’s great. But it won't fix your underlying AI discoverability issues.

3 - LightSite AI (technical + content agent)
This one took us a minute to wrap our heads around because it’s not really a visibility tracker, and it’s not just a content writer. It operates as both a technical and content agent. It gives a pretty complete picture of how to actually build trust and authority with AI at the structural level, this is the closest thing we found to a complete solution. Instead of just giving you a dashboard of mentions, LightSite builds a machine readable technical layer on your site and gives you an agent to execute fixes (both on and off page).
Pros:

• Holistic: It bridges the gap between technical infrastructure and content execution.
• The dynamic technical layer: Shaping bot behavior via skills/endpoints is an advantage over other tools.
• Execution instead of simple observation: The agent identifies a gap (e.g., "ChatGPT thinks your competitor has a better pricing model"), suggests the content fix, and can actually execute the content updates or outreach campaigns.
• Tracks bot logs vs. human traffic, which is critical for real attribution (not vague mentions or SOV etc).
• Cons:
• Integrating it required a buy in from our techcnial team and we had to go through security testing since it plugs into the website.
• The learning curve is steeper because it does require a change in mindset - from keywords only to bot behavior / technical part.
• Bottom line: If you want a system that actually builds the technical infrastructure and acts as an agent to help you execute, this is the strongest platform we tested. But you have to be willing to do the integration work.

4 - Brand24 / Mention (The PR Trackers)
We tried using traditional social listening tools that have pivoted to AI Mention Tracking. They basically ping the LLMs with prompts and track if your brand is recommended.
Pros:

• Great for the CMO's weekly report. The charts look beautiful.
• Good for broad sentiment analysis (does the AI think we are expensive, cheap, reliable?).
• Very easy to set up. No dev resources needed.
• Cons:
• Zero actionable insights. Okay, ChatGPT recommends our competitor 60% of the time. Why? And how do I fix it?
• LLM hallucinations make this data incredibly noisy. You can prompt Claude three times and get three different brand recommendations.
• Completely disconnected from your actual website backend.
• Bottom line: Good for benchmarking your PR efforts, practically useless for a technical or content team trying to do actual GEO work.

5 - Surfer SEO / Frase
We still use these, but we had to re evaluate how we use them in an AI first world. These tools are built around NLP and entity optimization.
Pros:

• Still the best way to ensure your content is dense with the right entities.
• If you want an LLM to understand your page, scoring high on Surfer/Frase is a great baseline.
• Excellent workflow for human editors.
• Cons:
• They are still fundamentally built for Google’s traditional ranking algorithm (TF-IDF, keyword frequency, etc).
• They assume the end goal is a human reading a SERP. They do nothing to help headless AI agents interface with your backend data.
• No bot tracking or technical deployment features.
• Bottom line: Essential for your writers, but it’s only half the battle. They optimize the text, but not the delivery mechanism to the AI.

My Takeaway for 2026
If you are just buying a tool that shows you a dashboard of AI Share of Voice, you are wasting your money.

The brands that are actually building trust and authority in AI search right now are doing two things simultaneously:

1. Pumping out highly specific, authentic, helpful, entity rich content (using tools like Writesonic/Surfer).
2. Fixing their technical layer so LLMs can cleanly parse that content as data (using platforms like LightSite AI).

My advice - stop obsessing over rank tracking, stop looking for shortcuts and stop buying dashboards - understand that this is a holistic play, SEO is not dead but there are nuances that have to be handled and honestly no one knows where all this is going so keep creating value for your users on every step of the way and you will be fine.

Let me start with a disclaimer, because the hype around this topic is getting a bit out of hand. Unlike many others here, I don't think that generative engine optimization, GEO , AEO or whatever you call it- is some magical new discipline.

There is a huge overlap with traditional SEO. If your technical SEO is garbage and your content is thin, no AI hack is going to save you. But it is NOT 100% overlap.

That 10% to 20% difference between SEO and GEO is important and risky enough for a brand like ours to seriously look at the nuances of how to build trust and authority with AI.

My team has spent the last few months testing almost a dozen tools to figure out how to really improve AI visibility of a brand. What we realized is that 90% of the tools out there are just expensive dashboards. They scrape LLM outputs, put them in a pretty pie chart, and tell you that you are losing visibility, ok I get it, marketers wnat to know and always hungry for data (even when it becomes counterproductive). But what do I actually do about it - there is a huge difference between data and actionable insights.

I think that to actually move the needle, you need a holistic approach that covers both content generation and technical infrastructure. You have to control what the bot reads and how the bot behaves when it hits your server.

Here is a breakdown of the stack we tested, what we kept, what we threw out, and what actually worked for us.

1 - The Legacy Giants (Ahrefs / Semrush)
I have to include them because you can’t ignore them. Yes, they are all releasing AI Search features and no, they aren't there yet. It feels to me that they are doing it because the demand is there and they have to add some features anyway. I personally wouldn’t use them for this.
Pros:

• You still need them for backlink profiles and traditional search volume (Google and SEO is very far from dead, and traditional SEO still heavily informs LLM training data).
• Great site audit tools for basic technical hygiene (broken links, toxic domains).
• Cons:
• They are trying to retrofit an old paradigm (10 blue links, search volume) onto a new paradigm (RAG, conversational answers).
• They don't track how AI bots fetch your data in real time, let alone optimize for it.
• Bottom line: Keep your subscription, but don't expect their new features to solve your generative engine optimization problems anytime soon.

2 - Writesonic (and similar AI content factories)
We looked at Writesonic, Jasper, and a few others for the content side of the play. If you want AI visibility, you obviously need entities and topical authority. Writesonic is a beast for content velocity. It’s moved way past just being a basic GPT wrapper and has some genuinely good SEO features built into the workflow now.

Pros:

• Incredible for scaling up glossary pages, FAQs, and top of funnel content.
• The brand voice training actually works pretty well if you feed it good guidelines.
• Very intuitive UI; you can train a junior marketer on it in an hour.
• Good integrations with WordPress and other CMS platforms.
• Cons:
• It is purely a content play. It does absolutely nothing for your technical architecture.
• Just writing AI friendly content isn't enough if the LLM bots can't parse your site properly when they fetch it.
• You still have to figure out what to write on your own. It doesn't tell you where your visibility gaps are in Perplexity or Claude.
• Bottom line: If your only bottleneck is writing words on a page, it’s great. But it won't fix your underlying AI discoverability issues.

3 - LightSite AI (technical + content agent)
This one took us a minute to wrap our heads around because it’s not really a visibility tracker, and it’s not just a content writer. It operates as both a technical and content agent. It gives a pretty complete picture of how to actually build trust and authority with AI at the structural level, this is the closest thing we found to a complete solution. Instead of just giving you a dashboard of mentions, LightSite builds a machine readable technical layer on your site and gives you an agent to execute fixes (both on and off page).
Pros:

• Holistic: It bridges the gap between technical infrastructure and content execution.
• The dynamic technical layer: Shaping bot behavior via skills/endpoints is an advantage over other tools.
• Execution instead of simple observation: The agent identifies a gap (e.g., "ChatGPT thinks your competitor has a better pricing model"), suggests the content fix, and can actually execute the content updates or outreach campaigns.
• Tracks bot logs vs. human traffic, which is critical for real attribution (not vague mentions or SOV etc).
• Cons:
• Integrating it required a buy in from our techcnial team and we had to go through security testing since it plugs into the website.
• The learning curve is steeper because it does require a change in mindset - from keywords only to bot behavior / technical part.
• Bottom line: If you want a system that actually builds the technical infrastructure and acts as an agent to help you execute, this is the strongest platform we tested. But you have to be willing to do the integration work.

4 - Brand24 / Mention (The PR Trackers)
We tried using traditional social listening tools that have pivoted to AI Mention Tracking. They basically ping the LLMs with prompts and track if your brand is recommended.
Pros:

• Great for the CMO's weekly report. The charts look beautiful.
• Good for broad sentiment analysis (does the AI think we are expensive, cheap, reliable?).
• Very easy to set up. No dev resources needed.
• Cons:
• Zero actionable insights. Okay, ChatGPT recommends our competitor 60% of the time. Why? And how do I fix it?
• LLM hallucinations make this data incredibly noisy. You can prompt Claude three times and get three different brand recommendations.
• Completely disconnected from your actual website backend.
• Bottom line: Good for benchmarking your PR efforts, practically useless for a technical or content team trying to do actual GEO work.

5 - Surfer SEO / Frase
We still use these, but we had to re evaluate how we use them in an AI first world. These tools are built around NLP and entity optimization.
Pros:

• Still the best way to ensure your content is dense with the right entities.
• If you want an LLM to understand your page, scoring high on Surfer/Frase is a great baseline.
• Excellent workflow for human editors.
• Cons:
• They are still fundamentally built for Google’s traditional ranking algorithm (TF-IDF, keyword frequency, etc).
• They assume the end goal is a human reading a SERP. They do nothing to help headless AI agents interface with your backend data.
• No bot tracking or technical deployment features.
• Bottom line: Essential for your writers, but it’s only half the battle. They optimize the text, but not the delivery mechanism to the AI.

My Takeaway for 2026
If you are just buying a tool that shows you a dashboard of AI Share of Voice, you are wasting your money.

The brands that are actually building trust and authority in AI search right now are doing two things simultaneously:

1. Pumping out highly specific, authentic, helpful, entity rich content (using tools like Writesonic/Surfer).
2. Fixing their technical layer so LLMs can cleanly parse that content as data (using platforms like LightSite AI).

My advice - stop obsessing over rank tracking, stop looking for shortcuts and stop buying dashboards - understand that this is a holistic play, SEO is not dead but there are nuances that have to be handled and honestly no one knows where all this is going so keep creating value for your users on every step of the way and you will be fine.

Let me start with a disclaimer, because the hype around this topic is getting a bit out of hand. Unlike many others here, I don't think that generative engine optimization, GEO , AEO or whatever you call it- is some magical new discipline.

There is a huge overlap with traditional SEO. If your technical SEO is garbage and your content is thin, no AI hack is going to save you. But it is NOT 100% overlap.

That 10% to 20% difference between SEO and GEO is important and risky enough for a brand like ours to seriously look at the nuances of how to build trust and authority with AI.

My team has spent the last few months testing almost a dozen tools to figure out how to really improve AI visibility of a brand. What we realized is that 90% of the tools out there are just expensive dashboards. They scrape LLM outputs, put them in a pretty pie chart, and tell you that you are losing visibility, ok I get it, marketers wnat to know and always hungry for data (even when it becomes counterproductive). But what do I actually do about it - there is a huge difference between data and actionable insights.

I think that to actually move the needle, you need a holistic approach that covers both content generation and technical infrastructure. You have to control what the bot reads and how the bot behaves when it hits your server.

Here is a breakdown of the stack we tested, what we kept, what we threw out, and what actually worked for us.

1 - The Legacy Giants (Ahrefs / Semrush)
I have to include them because you can’t ignore them. Yes, they are all releasing AI Search features and no, they aren't there yet. It feels to me that they are doing it because the demand is there and they have to add some features anyway. I personally wouldn’t use them for this.
Pros:

• You still need them for backlink profiles and traditional search volume (Google and SEO is very far from dead, and traditional SEO still heavily informs LLM training data).
• Great site audit tools for basic technical hygiene (broken links, toxic domains).
• Cons:
• They are trying to retrofit an old paradigm (10 blue links, search volume) onto a new paradigm (RAG, conversational answers).
• They don't track how AI bots fetch your data in real time, let alone optimize for it.
• Bottom line: Keep your subscription, but don't expect their new features to solve your generative engine optimization problems anytime soon.

2 - Writesonic (and similar AI content factories)
We looked at Writesonic, Jasper, and a few others for the content side of the play. If you want AI visibility, you obviously need entities and topical authority. Writesonic is a beast for content velocity. It’s moved way past just being a basic GPT wrapper and has some genuinely good SEO features built into the workflow now.

Pros:

• Incredible for scaling up glossary pages, FAQs, and top of funnel content.
• The brand voice training actually works pretty well if you feed it good guidelines.
• Very intuitive UI; you can train a junior marketer on it in an hour.
• Good integrations with WordPress and other CMS platforms.
• Cons:
• It is purely a content play. It does absolutely nothing for your technical architecture.
• Just writing AI friendly content isn't enough if the LLM bots can't parse your site properly when they fetch it.
• You still have to figure out what to write on your own. It doesn't tell you where your visibility gaps are in Perplexity or Claude.
• Bottom line: If your only bottleneck is writing words on a page, it’s great. But it won't fix your underlying AI discoverability issues.

3 - LightSite AI (technical + content agent)
This one took us a minute to wrap our heads around because it’s not really a visibility tracker, and it’s not just a content writer. It operates as both a technical and content agent. It gives a pretty complete picture of how to actually build trust and authority with AI at the structural level, this is the closest thing we found to a complete solution. Instead of just giving you a dashboard of mentions, LightSite builds a machine readable technical layer on your site and gives you an agent to execute fixes (both on and off page).
Pros:

• Holistic: It bridges the gap between technical infrastructure and content execution.
• The dynamic technical layer: Shaping bot behavior via skills/endpoints is an advantage over other tools.
• Execution instead of simple observation: The agent identifies a gap (e.g., "ChatGPT thinks your competitor has a better pricing model"), suggests the content fix, and can actually execute the content updates or outreach campaigns.
• Tracks bot logs vs. human traffic, which is critical for real attribution (not vague mentions or SOV etc).
• Cons:
• Integrating it required a buy in from our techcnial team and we had to go through security testing since it plugs into the website.
• The learning curve is steeper because it does require a change in mindset - from keywords only to bot behavior / technical part.
• Bottom line: If you want a system that actually builds the technical infrastructure and acts as an agent to help you execute, this is the strongest platform we tested. But you have to be willing to do the integration work.

4 - Brand24 / Mention (The PR Trackers)
We tried using traditional social listening tools that have pivoted to AI Mention Tracking. They basically ping the LLMs with prompts and track if your brand is recommended.
Pros:

• Great for the CMO's weekly report. The charts look beautiful.
• Good for broad sentiment analysis (does the AI think we are expensive, cheap, reliable?).
• Very easy to set up. No dev resources needed.
• Cons:
• Zero actionable insights. Okay, ChatGPT recommends our competitor 60% of the time. Why? And how do I fix it?
• LLM hallucinations make this data incredibly noisy. You can prompt Claude three times and get three different brand recommendations.
• Completely disconnected from your actual website backend.
• Bottom line: Good for benchmarking your PR efforts, practically useless for a technical or content team trying to do actual GEO work.

5 - Surfer SEO / Frase
We still use these, but we had to re evaluate how we use them in an AI first world. These tools are built around NLP and entity optimization.
Pros:

• Still the best way to ensure your content is dense with the right entities.
• If you want an LLM to understand your page, scoring high on Surfer/Frase is a great baseline.
• Excellent workflow for human editors.
• Cons:
• They are still fundamentally built for Google’s traditional ranking algorithm (TF-IDF, keyword frequency, etc).
• They assume the end goal is a human reading a SERP. They do nothing to help headless AI agents interface with your backend data.
• No bot tracking or technical deployment features.
• Bottom line: Essential for your writers, but it’s only half the battle. They optimize the text, but not the delivery mechanism to the AI.

My Takeaway for 2026
If you are just buying a tool that shows you a dashboard of AI Share of Voice, you are wasting your money.

The brands that are actually building trust and authority in AI search right now are doing two things simultaneously:

1. Pumping out highly specific, authentic, helpful, entity rich content (using tools like Writesonic/Surfer).
2. Fixing their technical layer so LLMs can cleanly parse that content as data (using platforms like LightSite AI).

My advice - stop obsessing over rank tracking, stop looking for shortcuts and stop buying dashboards - understand that this is a holistic play, SEO is not dead but there are nuances that have to be handled and honestly no one knows where all this is going so keep creating value for your users on every step of the way and you will be fine.

I’m an IT manager at a mid sized company, around 700 employees, mostly managed Windows laptops, Intune, Entra, normal web filtering and too many SaaS apps.

Our security team is getting more nervous about browser-based AI tools now. HR and marketing are using ChatGPT for docs, devs keep asking about Claude / Claude Code workflows, some people use Perplexity, some use Gemini, and I’m sure there are random AI writing extensions sitting in browsers that nobody approved.

I’m not trying to become the AI police. I also don’t want to be the guy who tells leadership “yeah we had a policy” after someone pasted customer data into a personal AI account.

So I’m trying to build a simple evaluation checklist before we buy another tool or just block everything and pretend the problem is solved.

The basic issue is this. If the laptop is managed, we can do some things with Intune, browser policy, web filtering, CASB/SSE, extension allowlists, etc. Not perfect, but at least there is a control path.

If the user is a contractor or on BYOD, it gets ugly fast.

Most AI usage happens in the browser, so normal network visibility does not always answer the question I actually care about. I don’t only care that someone went to chatgpt.com. I care if they pasted sensitive text, uploaded a file, used a personal account, used an extension that can read page content, or opened the same app from an unmanaged profile.

Things I’m checking so far:

Can we see browser-based AI usage clearly, or only domains/categories?

Can we separate approved AI tools from random shadow AI tools?

Can we control file uploads and copy/paste into AI tools without breaking normal work?

Does it work with Chrome and Edge, or only one browser?

Does it depend on a browser extension, and if yes can we actually enforce that through Intune?

What happens if someone uses a personal Chrome profile, guest profile, or another browser?

Does it help with AI extensions and permission changes, or only normal web traffic?

Does it support SAML / Okta / Entra properly, or are we creating another login mess?

Can we apply different policies for employees vs contractors?

Can we secure access for unmanaged devices without installing agents on personal laptops?

How noisy is the reporting? I do not want another dashboard full of alerts nobody reads.

What happens if we cancel, do we get logs/export, and how long do they keep the data?

Right now I’m seeing a few categories and none of them feel perfect.

CASB/SSE helps with broad visibility and policy, but sometimes feels too far away from the browser action.

Browser extension tools seem useful if you can enforce the extension properly, but that depends on how clean your managed fleet is.

Enterprise browsers seem strong if you can force users into the browser, but I can already hear the complaints from devs and contractors.

Agentless SSE / secure web access tools look interesting for contractor and unmanaged device access, because they focus more on securing the session/access path instead of owning the endpoint, but then I assume you give up some local machine telemetry.

I’m not looking for vendor pitches. I want the checklist from people who already had to deal with this.

What did you check before approving browser-based AI tools, and what did you miss that became painful later?