Corporate Claude vs Personal Claude: which one is your company actually getting more value from?

Your company pays for the secure, governed, IT-approved Claude seat including audit logs and data protection.

Here's the uncomfortable question: is that the version of Claude doing your employees' best thinking or is the real work happening on the personal account they pay for out of their own pocket?

I believe it's a hot topic, because I prefer to use my own personal account too, just because it understands me and my goals much better.

The numbers are interesting.

• 78% of AI users bring their own AI tools to work (Microsoft & LinkedIn, 2024).
• Nearly half access AI through personal accounts that bypass enterprise controls entirely (Netskope, 2026).
• And even when the company hands them a sanctioned tool, 22% reach for their personal account anyway (TELUS Digital, 2025).

Most security write-ups stop here and yell "data breach." It's fair, but it dodges the more interesting question: why do people keep choosing the worse-protected, self-funded option?

I have 2 theories about it:

1. People won't be fully honest in an account that the boss can read. When employees know management can review their AI interactions, they self-censor and modify their behavior (research summarized in The Conversation, 2025). If you're scared to type "help me figure out if I should quit" or "I don't actually understand this thing I'm supposedly an expert in," you ask weaker questions. Weaker questions, weaker output. Does the corporate account quietly cap how useful the tool can be, not technically, but psychologically?

2. People work harder for a tool that feels like theirs. 35% of employees pay out of their own pocket for AI at work (Writer survey). Nobody buys a tool they're not invested in. When the productivity gain feels like it belongs to you (your skill, your edge, your career) do you push the tool harder than when the upside just flows to the company P&L?

The honest counterpoint: none of this proves personal accounts are actually more efficient.

It proves they're more used and more personally owned. Maybe that's the same thing. Maybe it isn't, and the company is just bleeding confidential data into consumer accounts while feeling clever about "engaged employees." I genuinely don't think anyone has cleanly measured which way this nets out.

So I'll throw it to the people who'd know:

• If your company gave you a managed AI seat, do you still use your personal one? Be honest, for what?
• Do you ask the corporate account different questions than the personal one?
• Owners/managers: have you noticed people doing their best AI work off the books?

I received an interesting question from one of the B2B SaaS brands I help with AI SEO.

"G2 is trying to sell us a package of content based on comparisons. We rank pretty high on a few of these metrics.

If we license the content, we can use those numbers on our site, which they say can boost our AEO scores.

It costs about $3,700 from now until December. Is it worth it or not?"

https://preview.redd.it/n2jx36bay68h1.png?width=2922&format=png&auto=webp&s=c53c980eda9ad3f46bd3171e7de17949a5dc548e

It's interesting how accurately G2 has found its value for brands in relation to the new, growing demand:

1/ Listicles, [brand] alternatives, and [brand] vs [brand] are too popular now.

2/ For many big brands, the goal is not to be visible (they are already visible); the goal is to be recommended as the best option.

But how profitable is this offer?

On the one hand, AI chats love tables, comparisons, and numbers.

On the other hand, AI chats rarely care about the authority of the source and the date of the last update of such a table.

This means that any competitor or third-party website can create the same table, building these numbers based on their fantasy, and without mentioning any sources from where they got them. And LLM can choose to cite this fantasy table instead of the tables from G2.

And here it is important what will happen after December, if the brand stops paying for these comparison tables:

1/ Can a brand leave this embed widget on the website? I assume no.

2/ Can a brand leave this data but not as an embedded widget, but as its own table, just copying the data and showing it without updates? This is more likely, and then you can try it if there are a lot of interesting insights on different competitors.

However, if you have to pay for it every quarter or year to keep the content on the site, it is definitely a bad deal. It is better to spend this money on regular link insertions on pages that have already been cited a lot.

Do you agree?

Я розвиваю агенцію, яка допомагає B2B SaaS будувати видимість в AI-чатах. Одні із ключових факторів які впливають на цю метрику це контент про бренд на Reddit, Medium, LinkedIn, YouTube.

Цікаво поспілкуватись з людьми які хочуть навчитись маркетингу, і вже активні на будь якій з цих платформ.

В мене поки немає готових вакансій для вас. Хочу подивитись, чи є тут взагалі кому це цікаво.

Every conversation about trust online ends in the same place lately: "We need to verify people are real." Bots write the reviews, apply for the jobs and astroturf the comments. So the answer everyone's reaching for is digital ID: prove you're a verified human before you post, rate, or apply.

Here's the part nobody wants to sit with: the cure might be worse than the disease.

Think about what we're actually trading. The whole reason online reviews ever mattered is that they were anonymous and cheap. A pissed-off customer or a burned employee could tell the truth with nothing to lose. The moment your honest 1-star review of an employer, a landlord, or a product is tied to your verified legal identity, that review stops existing. Not because it's fake, but because you're not insane enough to torch a reference or invite a defamation threat over a toaster.

So we'd "solve" fake reviews by killing the only reviews that were ever worth reading.

And notice who benefits. Brands have wanted to unmask their critics forever. Employers would love to know exactly who left that Glassdoor bomb. Digital ID hands them the deanonymization they could never get on their own, and we'd be cheering as we install it, because we're tired of bots.

The actual need here was never "prove humans are human." It's "give me one honest signal in a sea of manufactured ones." Those aren't the same problem. Identity verification answers who is talking. It does nothing about whether they're telling the truth, a verified human can be paid to lie just as easily as a bot, and now their lie wears a real name as a badge of credibility.

I don't think the future of trust is a checkpoint where you flash your ID to participate. I think that's the future of trust dying quietly while we call it security.

But I'm genuinely not sure what the alternative is, which is why I'm posting.

If anonymous reviews die, what replaces them? Is there any version of mandatory digital ID that doesn't end with critics getting silenced? Or is some amount of bot noise just the price of being able to speak freely?

You probably hear, that the last week the US gov issued an emergency export-control directive ordering Anthropic to cut off its two newest models Fable 5 and Mythos 5 for all foreign nationals.

In response, Anthropic has blocked all public access to both models, globally, meaning no users around the world can access them at this time, even paying enterprise customers and Anthropic employees internally. That's unprecedented, and the explanations floating around don't agree. Here's how I'd sort them.

Theory 1: "It's just too powerful, so it's government-only now."

This one's half-right but conflates two models. Mythos 5 is the unrestricted version that was never public; it should continue to be used only by government agencies and selected corporate partners.

Fable is the same base model with cybersecurity/bio capabilities locked down for public use. So the "keep the dangerous one for the government" logic already applied to Mythos before this order. What's new is that Fable, the public one, got pulled too, via an export rule about foreign nationals, not a "repurpose it for government" decision.

Theory 2: "It's purely a cybersecurity fix and it'll come back" (the David Sacks read).

Sacks (PCAST co-chair) did say the administration hopes that Anthropic will fix the issue and that Fable 5 can return to public release. The trigger was reportedly a jailbreak a trusted partner demonstrated.

But Sacks's framing was sharper than "friendly fix", he claimed Anthropic "prioritized the continued offering of the consumer model over safety," after allegedly refusing to fix or de-deploy. Worth noting Anthropic disputes the severity entirely, saying the vulnerability is already replicable using other publicly available models like GPT-5.5. So "just a quick security patch" is one side's spin.

Theory 3: "It's a clever Anthropic move to pump its valuation."

This is the spiciest take and it is circulating. Every's CEO suggested the ban could lift fast and only increase demand, which one outlet flatly called a glorified marketing stunt.

The timing fuels it: Anthropic confidentially filed for an initial public offering around June 1 at a valuation near $965 billion. But this is speculation, not anything established, and it ignores the real friction history (Anthropic refused a domestic-surveillance/autonomous-weapons deal earlier this year and got labeled a DoD "supply chain risk"). A company manufacturing a federal shutdown of its own flagship is a stretch.

Where it actually stands

Anthropic complied but is contesting it, and security leaders are reportedly pushing the administration to restore access. Other Claude models are unaffected.

My honest read is that it's less a single clean story than a collision between a real safety dispute and an already-tense Anthropic/White House relationship, with the valuation angle being the most fun and least supported.

Which theory do you find most convincing, and does anyone with export-control experience know whether "block all foreign nationals" is even technically enforceable here?

Nearly a billion people use AI chatbots today. I've been one of them, pasting P&Ls, revenue by my projects, and marketing spend into AI chats to get quick analysis.

Recently, I started asking a question I probably should've asked earlier: what actually happens to that data?

For example, Claude's October 2025 policy update defaulted users who didn't respond to a notification into 5-year data retention and model training consent. Paid Pro users are opt-in only, but free users got quietly enrolled.

The question I still can't fully answer: if I shared a P&L, could anything leak through to other users? Probably not directly. But if a model trains on it and someone asks the right question? I don't have a confident answer.

I've started treating AI chats like email: useful, convenient, and not private by default.

What about you, do you have any rules for what stays out of the chat?

P.S. I use Claude Pro subscription. Tested ChatGPT too. Also use Gemini primarily for YouTube video transcription and summarization.

If the query contains multiple "or" rules, it's almost 100% a bot.

Check the example in the screenshot:

A long search query in GSC that is clearly from AI visibility tracking tool

• I'm a 25-34, 45-54, or 35-44 year old
• marketing operations manager or marketing manager
• in the marketing agencies, saas or professional services
• company with 1-249 or 250-1k employees
• and so on

Nobody uses search and AI chats this way. Some AI visibility tracking tool allowed businesses to add some parameters of the ICP to the project.

It's the right move, but only when the tool runs multiple prompts for each unique combination of such parameters.

Of course, it's much more expensive, but with an approach as on the screenshot, the query never represents the real user.

We'll see more and more such long queries in GSC. If you detected some other patterns of queries from bots, share them in the comments. I'll publish a complete list later.

Google announced, "a new profile to help publishers and creators highlight their work on Search".

https://preview.redd.it/33fh12hm6f5h1.png?width=1818&format=png&auto=webp&s=59de92fd84a0a3bca2c9962c25c57b132a4f3021

And I believe this is good news.

Google+ died because it couldn’t build network effects or motivate people to go there every day. The new format will be much better.

Now Google will do what it was created for and what it does best -> aggregate information from different sources in one place.

And, yes, now there is a new motivation to grow followers on the platforms.

So, Google announced a Generative AI performance report in Search Console. Sounds as something cool, because the SEO community has asked for something like this for a long time.

But it's not cool in fact. Impressions by device, country, and pages? It's even worse than Bing's report, released in February 2026, because it doesn't have any data by queries.

I like Google in many spaces, but this report looks like just a defense. It has almost 0 value, because brands fight for being recommended, not being cited with their own pages.

When top AI visibility tracking tools add brand visibility, brand sentiment, top sources used for citations, and so on, Google releases the Impressions report.

On one hand, Google rewards Reddit, YouTube, Medium, and LinkedIn pages and uses them in citations, and on the other hand, it releases a report that says nothing about whether your brand performs well in search.

What's included in AI performance report

Here is what it will look like

Google Search Console AI performance report example

And compare it with the Bing AI Performance report.

Bing AI performance report

With Bing we have at least grounding queries.

What do you think?

P.S. I also don't see this report in any of my GSC properties yet.

There's a new workplace dynamic quietly eroding professional trust, and most people aren't naming it directly: colleagues who use AI to respond to you without disclosing it.

I mean, not AI to draft something they then edit and own, but AI as a reply button when they paste your message in, copy the output, and hit send.

I assume this is a huge problem! When you message a colleague, you're implicitly asking: do you understand this, do you agree, will you be accountable for what you just told me?

An AI-generated reply answers none of those questions. It pattern-matches to what a reasonable response looks like. It sounds confident and it often sounds more professional than the person actually is, and that's exactly the problem.

You think you have a human commitment, but you have a plausible-sounding text artifact.

Some of the signs of such responses you probably noticed too:

• The reply is suspiciously thorough for a 2-minute turnaround
• The tone is oddly formal compared to how this person usually writes
• It uses phrases like "Certainly!", "Great question!", "To summarize:" in a Slack message
• The answer is structurally correct, but somehow misses the actual subtext of what you asked

Some argue it's no different from using Grammarly or a spell-checker.

I don't think so. What are your thought on this and how do you reach to such messages?

As for me, I usually ask the person does he/she reviewed this AI response and sure it's exactly what he/she think.

I opened LinkedIn Ads dashboard and found that CTR of my TL ads dropped.

When I opened one of the paid post from these ads I was surprised a lot. All the comments (29) and reactions (114) disappeared under the post.

Moreover, when I clicked "Turn comments on" it didn't help. When I update the post, the same button is still active and turning comments doesn't work.

So, LinkedIn created 3 problems at the same time:

1/ Changed the design of engagement signals under the post.

You probably noticed it in your feed. New design gives less attention to engagement.

It looks like Twitter / Substack style. In the past if you get a lot of likes and comments it was a huge signal for people to stop scrolling and actually pay attention to you post.

With a new design people will decide whether your post worth their attention primarily based on text hook and image / video / carousel.

2/ Removed all organic interactions when you launch TL ads for your post.

It's the biggest issue, and I still think this is a bug.

3/ Clicking "Turn comments on" doesn't even work.

My forecast is that the impact of TL ads for lead generation and brand awareness will decrease dramatically.

Do you see the same?

Along the way, I changed my payment provider, so I can’t verify the $16k amount, but something is visible there.

The revenue stats of my Data Studio templates store from Lemon Squeezy for the last 2 years.

So, here are the lessons:

1/ We often think that the market is saturated and there is no space for new products.

In most cases, it’s false.

We underestimate how much better existing products and services can be. New chart, new custom metric, new unique blending: each of them can become a small innovation.

Some of my small innovations were:

• Potential Rank custom metric ;
• Blending GSC + GA4 and creating custom metrics to forecast revenue from SEO;
• Blending GSC + Google Ads to prioritize landing pages based on conversion data from ads.

2/ Great data visualization is born only at the intersection of 2 things.

Domain knowledge and experiments with actual data visualization. You need both, and the first is even more important. Only the person with domain knowledge understands what a signal is and what is noise.

I didn’t finish any courses on how to visualize data properly; I just tried to answer the questions I had as a marketer.

3/ Even obvious valuable things are adopted over a long time.

GSC, GA4, and Google Ads data sources existed for a long time. Their dimensions and metrics are well known and used, but it took 5-7 years in total to build and distribute good enough reports based on them.

We often overestimate how much business wants innovations. Most of the innovations have expensive side effects, and business owners often don’t rush into big changes.

4/ “Oh man, there are so many free templates, why should I care”?

When people hear about Data Studio templates, some often think about them as a commodity.

My answer:

• You overestimate the depth of penetration of these products;
• You underestimate the number of unique valuable reports on the market;
• You underestimate the difficulty of learning and integrating these templates for many businesses.

When you work with some reporting tool for a long time and become a professional at it, it seems to you that it is so easy to use, and that people can build it all themselves.

The truth is that some people will be able to, 5-10%, but the majority, even among this group of people, will understand that buying an existing template has a better ROI for their time.

5/ There are 2 only business models for the Google Data Studio templates business.

• Sell templates;
• Use templates as free lead magnets for your agency or SaaS business.

Most businesses follow the 2nd way, because the first way is interesting only for indie hackers who consider a $5k/m business as something that is worth the effort.

I’ve chosen the 1st way because I feel it's different. I build better templates when I consider them as a separate product.

However, I always remember that if I can’t build a big business on that, it doesn’t mean it’s impossible.

6/ The biggest bottleneck of this business model is that unit economics doesn’t work in paid channels.

Most of my sales were from organic search, but the existing demand is not big. And for paid ads, this product has a classic dead zone by Peter Thiel: too cheap to sell via direct sales, too expensive to make it viral.

Top channels of traffic and sales for my store

7/ Considering there are many templates on the market and some of them are free, the biggest additional value I see in 3 things.

• Constantly educating people on how to use templates, what their limitations are, and so on, marketing is a huge part of the product here.
• Improve the details like crazy: design, filters, chart title, video guides, etc.
• Add a training or custom development service. This is the hardest. I helped with custom templates, but it’s not a scalable business; this is freelancing.

At the end, I consider this business as valuable training. I built all of these templates for myself at first, and I continue using them for my sites.

So, the 1st lesson of this business is that building for yourself is a good approach to start. Don’t hear marketers who say you aren’t your own audience.

Sometimes you aren’t, but often when you have real pain, this means that many people in your role and situation also feel this pain too, and solving something for yourself is often the most important step to launch a business.

I would be happy if you share whether you are currently using Data Studio and what your biggest pain point with it is.

P.S. All of my templates are paid, except these 3 (they are free).

• GA4 backlinks analysis
• GA4 audience analysis
• YouTube analytics

I've been tracking comments on my LinkedIn posts for the past year. Today, roughly 50% of all comments I receive are AI-generated.

Below is an example of one of the last posts.

I reply with screenshots of their last comments, when it's clear that's impossible to leave 3 detailed comments in 1 minute

I noticed that what changed isn't the number, it's who's doing it.

A year ago, AI comments came almost exclusively from junior roles and accounts from developing markets: people who may have less time, less language confidence, or less platform experience. You could write it off as grinding for visibility.

Now I'm seeing it from:

• Founders and CEOs with 10k+ followers
• People based in the US, UK, Germany, Scandinavia
• Accounts with strong, verified professional histories

Which raises a question I can't stop thinking about: did these people stop caring about their reputation, or did the definition of "reputation" just change?

My working theory: we're seeing a split in how people think about professional reputation online.

One camp still treats every comment as a signal, part of a long-term personal brand (I belong to this camp).

The other camp has decided LinkedIn engagement is just a distribution game, and authenticity is a cost they're willing to cut.

A few questions for the community:

• Have you noticed the same shift in your feed?
• Does an AI comment from a business owner feel like a red flag to you, or are you past caring?

On Monday, I will publish the first benchmark report on how agencies use Claude for SEO automation.

There are some interesting insights there. One of them is that Dataforseo is popular for integrations, just like Ahrefs.

Which SEO tools people connect to Claude

I thought it might be a small sample (30 agencies). But when I looked at the financial data for their Estonian company, I realized it's close to reality.

Revenue dynamics of Dataforseo Estonian company

Yes, the Dataforseo team is pumping marketing more and more, but AI chats have become the tailwind that fills their sails to the maximum.

What do you prefer for keywords, backlinks and competitor data: Ahrefs vs Dataforseo? and why?

In the previous post I shared that I found a spike in ChatGPT referral traffic for 3 B2B SaaS websites I have access to GA4.

I hypothesized that it was because of a new model ChatGPT released on May 5, but I didn't know the exact mechanism of this traffic increase.

Now we have a clear answer. Josh Blyskal shared on LinkedIn his own research and found that ChatGPT changed how it links to brands. New model show links for brands.

https://preview.redd.it/vsu1t9kwyf2h1.jpg?width=1536&format=pjpg&auto=webp&s=80b5a9364e9f2921642686d9e42f1399ff3a3e6a

This is good news, because it gives more value for each recommended brand.

I checked AI traffic for 3 B2B SaaS sites ( r/Sitechecker, r/TangoAI, r/favikon) and found that after May 5, all of them have spikes of traffic from ChatGPT.

AI traffic for TangoAI

AI traffic for Sitechecker

I assume that the last GPT-5.5 model, released on May 5, is responsible for this.

Pay attention to \"and when ChatGPT decides to search the web\"

I don't know whether more links to sites were a planned move by ChatGPT, to get more attention from site owners or just a side effect of them deciding to improve the end-user experience.

But it looks like this is one of many counterattacks that ChatGPT has delivered to the fast-growing Claude and Gemini.

Did you see this spike in your GA4 properties? Note that such a spike is easy to detect only on websites that already have solid AI traffic every day.

The news that Google deprecated FAQ rich results on May 7, 2026, raises a more important question than just structured markup for FAQs -> do we need this type of content at all?

For a long time, people implemented FAQs only in 2 cases:

- when it was a real value for a user and conversion rate (for example on a pricing page).
- when they found that they could get the x2 area in Google SERP because of the FAQ rich snippet.

Considering that the second case doesn't make sense anymore, I believe we have to place FAQs only by thinking about users.

It means that on some pages, FAQs look organic and improve user satisfaction, on other pages, they look completely unnecessary and strange.

For example:

1/ On the product page on an e-commerce website, it's worth adding FAQs because:

- most product descriptions look generic and the same;
- but people often have multiple super-specific questions about whether this product help with ..., or integrates with ..., and so on.

2/ At the end of the blog article, it looks strange, because you:

- just repeated what you said in the body of the article
- or even worse, didn't include answers to important questions in the body

However, I'm not sure about how much value FAQs create for visibility and recommendations in LLMs.

It definitely creates value if you add unique questions and answers to the page that were presented before in the body. It's a basic concept of content improvement. We also know that LLMs prefer to cite fresh content.

But what if you just rewrite your page content in FAQs? It's the same content but in a different format. Is there any value, considering LLMs understand what you already said in the body?