Sports physiologist, PhD. Helping people stay strong, mobile, and healthy for the long game. Research → practical protocols
Joined December 2022
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Dr. Sara Lin retweeted
I didn't need more courage to quit. I needed
proof that leaving wouldn't destroy my life.
So I gave myself 120 days to build it:
For years, I thought leaving my job required one huge leap.
A brilliant idea.
A massive audience.
Enough savings to make fear disappear.
That belief kept me stuck because the first step felt impossibly far away.
What I actually needed was a smaller question.
What problem could I solve with one skill I already had?
That question gave me somewhere to begin.
First, I found a painful problem people were already trying to fix.
Then I spoke with real people before building anything.
I shaped one clear offer and asked a small group to buy it.
I built only what those first customers needed.
I helped them get a real result.
Then I turned what worked into a simple process I could repeat.
That is how an exit becomes more than a dream.
You don't quit first and hope something works.
You create proof, income, and options before you hand in your notice.
You don't need to become a different person to start.
The skills you use every day are already more than enough to build your first offer.
You just need to stop giving all of them to someone else.
Save my infographic - it's the exact plan I used.
If you are ready to turn what you know into something that belongs to you, I created a free toolkit to help you take the first step.
👉 Grab it free here: creatyl.com/toolkit
Your exit does not begin on the day you quit.
It begins the day you stop waiting to be rescued and start building another choice.
Please repost to help others out there! ♻️
Dr. Sara Lin retweeted
You can earn $9000 a month if you have ChatGPT, a laptop, internet, and 1 hour a day.
I usually charge $93 for this guide, but today it's yours 100% free.
Like + reply 'Money' & I'll send you my full guide for FREE.
Must follow me to receive guide in DM
Free for 48 hours
Dr. Sara Lin retweeted
AI was supposed to reduce teams.
Instead, AI is creating new jobs faster than expected.
Sharing interesting insights from @pascal_bornet.
The latest data challenges how many leaders view AI and employment:
@Box surveyed 1,640 IT decision-makers about AI’s impact on organizations.
58% expect their workforce to grow during the next three years.
Among AI-mature companies, that figure rises sharply to 79%.
Only 9% say agents are mainly removing roles today.
The fastest-growing positions are also relatively new to the workplace.
These include agent operators, AI governance experts, and workflow specialists.
Many of these roles barely existed two years ago.
They are not simply replacing jobs lost through automation.
They are emerging because organizations need people to manage AI.
AI adoption is creating entirely new layers of work.
The workforce may not be shrinking the way many predicted.
Instead, job responsibilities are changing alongside technology.
AI may reshape teams more than it reduces them.
The biggest opportunity could be in jobs AI creates.
P.S. Which new AI-driven roles will become essential in your industry?
♻️ Repost to help leaders rethink how AI will reshape work.
——
Get my top 100 infographics for free:
1) Follow me.
2) Subscribe to my free newsletter at WildCapital.co.
You’ll receive them directly in your welcome email.
Dr. Sara Lin retweeted
Escaping rat race in 2010:
• Invest in stocks
• Buy rental properties
• Wait decades for passive income
Escaping rat race in 2027:
Dr. Sara Lin retweeted
Not trying to insult anyone here but...
B2C SaaS operators on X are struggling to keep up with how marketing is changing.
Let’s start with how people are finding software now.
Your customers are increasingly starting with questions like:
“What’s the best budgeting app if I don’t want to track everything manually?”
“What’s the best app for learning Spanish if I only have 15 minutes a day?”
“Is there a cheaper alternative to Dropbox for storing all my photos?”
Those questions are being answered across Google AI Overviews, ChatGPT, Perplexity, Gemini, Bing and traditional search.
That is something SEO Stuff started building around early:
seo-stuff.com/ai-seo
And if you want to see where your SaaS already stands across Google, ChatGPT, Claude, Perplexity and broader AI search, start here:
seo-stuff.com/free-audit
The first step is targeting the way customers actually describe their problems.
Good sources include keyword data, Reddit discussions, app reviews, support forums and anywhere customers explain what they are trying to accomplish in their own words.
Look for specific, commercially relevant searches with manageable competition, then build around the actual problem instead of broad category keywords.
Next, every meaningful feature and use case should have a strong landing page.
If your software helps fitness coaches schedule clients, tutors collect payments and creators manage invoices, those use cases should not be buried inside one generic features page.
Each important page should clearly explain the outcome, who it is for, how the feature works, what proof supports it and where the customer should go next.
Then own the comparison layer.
If customers are searching “[Your Tool] vs [Competitor]” or “best alternatives to [Competitor],” you want your site participating in that decision.
Strong comparison pages should include a clear verdict, pricing and feature differences, screenshots, customer proof, FAQs and a direct explanation of who each option is best for.
Those are extremely high-intent searches because the buyer is already evaluating software.
Video helps too.
Create short demos, workflow walkthroughs, customer stories and direct comparisons, then publish them on YouTube with clear titles and transcripts.
That gives customers another way to discover the product while also creating more indexable information around what the software does and who it serves.
Content still matters, but it needs to be useful and easy to extract.
Good topics include category explainers, workflow guides, templates, common mistakes, comparisons and timely planning content.
A piece like “2026 planning framework for freelancers” is much more useful when it naturally connects back to the product's relevant feature, pricing page or use case.
The goal is covering the questions customers ask before they sign up.
Retention content matters too.
Create onboarding hubs, “how to do X with [Your Tool]” walkthroughs, templates, workflows and useful customer education.
That improves the product experience while creating more branded searches, repeat visits and clear information about how people actually use the software.
Then retarget the people showing real buying intent.
Someone who visits pricing, reads a comparison page or starts signup and leaves is very different from someone who bounced from a broad informational article.
Use customer stories, “why I switched” videos, testimonials and concrete outcomes to bring those users back.
Run the system consistently and you start building visibility around the questions people actually ask instead of the keywords you hope they type.
You also give Google, ChatGPT, Gemini, Perplexity and other systems far more information about what your product does, who it serves and why somebody might choose it.
If you want the done-for-you version so you can stay focused on the product, check out SEO Stuff:
seo-stuff.com
And if you want to see where your SaaS already stands across Google, ChatGPT, Claude, Perplexity and broader AI search, start here:
seo-stuff.com/free-audit
We now have a clear picture of how Muse decides which products and services to recommend.
This is going to open up a new revenue channel for businesses across e-commerce, SaaS and local services.
This week a bunch of Muse’s operating instructions and internal files were extracted, and there is a big takeaway for businesses trying to show up in AI search.
Muse can search the open web AND Meta content across Instagram, Facebook and Threads - which creates two very different discovery surfaces.
Let’s go through it.
By the way, you can see whether your business is appearing across Google AI, ChatGPT, Claude, Perplexity and Grok here.
It’s free:
seo-stuff.com/free-audit
First, some context.
Researchers extracted Muse instructions and internal files through the normal chat interface.
Meta has said those files were intended to be accessible, take that for what it's worth. They say this isn't a "leak" - but the captured search instructions are unusually specific.
First, Muse has an open-web search tool. It also has a semantic content search across Instagram, Facebook and Threads.
The prompt tells Muse to use that social search for things like restaurants, cafes, shops, gyms and salons, fashion and beauty, public opinion, product recommendations, shopping advice and other queries where social content could improve the answer.
And if a question meets the criteria for both web search and Meta content search, Muse is instructed to use both.
That matters for brands, because you may be competing for visibility in the traditional web results Muse can search AND inside Meta’s own content ecosystem.
The social-search tool gets even more interesting.
Its captured instructions expose three ranking modes:
Informational.
Engagement.
Recency.
For reviews, comparisons, recommendations and “best X” queries, the engagement mode can rank posts using signals such as likes, shares and author follows.
This is exactly what SEO Stuff (seo-stuff.com/ai-seo) does for brands on a daily basis.
Mind you, that does NOT mean likes are a universal Muse ranking factor - it just means engagement is explicitly part of one retrieval mode inside Meta’s social-content search.
The tool also says its index is built using content understanding, including captions, visual analysis and transcripts, so this is not simply keyword matching.
Meta’s own public announcements support the broader direction too. Meta says Muse-powered experiences can surface recommendations and content shared across Instagram, Facebook and Threads, and that shopping mode draws from creators, communities and brand content across its apps.
For businesses, the AI-search playbook is getting wider.
Your website still needs clear, crawlable pages around your products, services, locations, comparisons and buyer questions.
Your broader web presence still matters because Muse can search the open web.
But inside Meta’s ecosystem, your Instagram, Facebook and Threads content may become another discovery surface entirely.
Clear category language matters, useful social content matters and freshness matters.
And for some recommendation queries, engagement may matter too.
That is a very different kind of AI search optimization.
Want to increase your sales + leads from ChatGPT, Google and broader AI search?
That is what SEO Stuff was built for:
seo-stuff.com/gold-plan-pack…
And if you want to see whether your business is appearing across Google AI, ChatGPT, Claude, Perplexity and Grok, start here (it's free):
seo-stuff.com/free-audit
Dr. Sara Lin retweeted
If I woke up bankrupt tomorrow, and had to make $10k/month, here's exactly what I'd do.
1. Open Google trends. Search this:
Dr. Sara Lin retweeted
We now have a clear picture of how Muse decides which products and services to recommend.
This is going to open up a new revenue channel for businesses across e-commerce, SaaS and local services.
This week a bunch of Muse’s operating instructions and internal files were extracted, and there is a big takeaway for businesses trying to show up in AI search.
Muse can search the open web AND Meta content across Instagram, Facebook and Threads - which creates two very different discovery surfaces.
Let’s go through it.
By the way, you can see whether your business is appearing across Google AI, ChatGPT, Claude, Perplexity and Grok here.
It’s free:
seo-stuff.com/free-audit
First, some context.
Researchers extracted Muse instructions and internal files through the normal chat interface.
Meta has said those files were intended to be accessible, take that for what it's worth. They say this isn't a "leak" - but the captured search instructions are unusually specific.
First, Muse has an open-web search tool. It also has a semantic content search across Instagram, Facebook and Threads.
The prompt tells Muse to use that social search for things like restaurants, cafes, shops, gyms and salons, fashion and beauty, public opinion, product recommendations, shopping advice and other queries where social content could improve the answer.
And if a question meets the criteria for both web search and Meta content search, Muse is instructed to use both.
That matters for brands, because you may be competing for visibility in the traditional web results Muse can search AND inside Meta’s own content ecosystem.
The social-search tool gets even more interesting.
Its captured instructions expose three ranking modes:
Informational.
Engagement.
Recency.
For reviews, comparisons, recommendations and “best X” queries, the engagement mode can rank posts using signals such as likes, shares and author follows.
This is exactly what SEO Stuff (seo-stuff.com/ai-seo) does for brands on a daily basis.
Mind you, that does NOT mean likes are a universal Muse ranking factor - it just means engagement is explicitly part of one retrieval mode inside Meta’s social-content search.
The tool also says its index is built using content understanding, including captions, visual analysis and transcripts, so this is not simply keyword matching.
Meta’s own public announcements support the broader direction too. Meta says Muse-powered experiences can surface recommendations and content shared across Instagram, Facebook and Threads, and that shopping mode draws from creators, communities and brand content across its apps.
For businesses, the AI-search playbook is getting wider.
Your website still needs clear, crawlable pages around your products, services, locations, comparisons and buyer questions.
Your broader web presence still matters because Muse can search the open web.
But inside Meta’s ecosystem, your Instagram, Facebook and Threads content may become another discovery surface entirely.
Clear category language matters, useful social content matters and freshness matters.
And for some recommendation queries, engagement may matter too.
That is a very different kind of AI search optimization.
Want to increase your sales + leads from ChatGPT, Google and broader AI search?
That is what SEO Stuff was built for:
seo-stuff.com/gold-plan-pack…
And if you want to see whether your business is appearing across Google AI, ChatGPT, Claude, Perplexity and Grok, start here (it's free):
seo-stuff.com/free-audit
Just a little heads up:
You can now block crawlers from using your content for AI training *without* completely blocking those crawlers from Search.
If you want to continue showing up in ChatGPT, Claude, Google's AI family, etc - pay attention.
Some site owners are going to misunderstand what is happening and play this wrong
Cloudflare just made an important change to its AI crawler controls.
A few weeks ago I wrote about the problem with blocking AI crawlers.
Basically, some companies use the same crawler for both Search and AI training, which meant blocking training could also mean blocking the crawler helping customers find you.
Cloudflare introduced a new setting designed specifically around that problem: it is called Disallow AI Training.
Let’s go through it.
By the way, you can see whether your business is appearing across Google AI, ChatGPT, Claude, Perplexity and Grok here. It’s free:
seo-stuff.com/free-audit
Cloudflare now lets website owners tell supported crawlers not to use their content for AI training without completely blocking those crawlers from Search.
Applebot, Googlebot and Bingbot are what Cloudflare calls mixed-use crawlers because the same crawler infrastructure can serve multiple purposes.
With the new setting, Cloudflare publishes the appropriate no-training preference in robots.txt while continuing to allow what it calls “Accountable” crawlers to access the site for Search.
Cloudflare says Apple, Google and Microsoft currently qualify as Accountable.
For OpenAI, Anthropic, Amazon and Meta, Cloudflare says Search and Training already use separate crawlers, so it can block the training crawler without blocking the Search crawler.
There is one very important warning: do not confuse Disallow AI Training with Block.
Cloudflare changed what Block means.
If you select Block for Training, mixed-use crawlers including Googlebot, Bingbot and Applebot can now be blocked completely, including their Search access.
If you want Search access to remain, Cloudflare says to use Disallow AI Training instead.
Worth keeping in mind - Google-Extended can be disallowed without affecting Google Search rankings, but Google says that control also affects whether your content can be used for grounding in Gemini Apps.
And Bing does not yet support Cloudflare's new robots.txt no-training preference automatically. Microsoft says that support is targeted for early 2027.
So this still is not a giant “turn off AI training with zero tradeoffs everywhere” button, but it is a big improvement.
Businesses can increasingly make separate decisions about traditional Search, AI training, AI agents and, eventually, AI summaries.
That is the direction this needed to go.
For most businesses, the goal shouldn't be to blindly block every AI crawler so much as it should be to understand which systems create discovery, which ones help customers take action, and which ones are simply using your content for training.
If you don't know how to make sure you're handling this correctly, SEO Stuff (seo-stuff.com) can help.
And if you're curious whether your business is appearing across Google AI, ChatGPT, Claude, Perplexity and Grok right now, check here. It’s free:
seo-stuff.com/free-audit
Dr. Sara Lin retweeted
Amazon KDP is literally a money-printing machine.
I made $65K last month selling AI eBooks on it.
I usually charge $91, but today it’s 100% FREE
Like + comment "SEND" & I'll DM it you a free training breaking down my training with you.
Must follow me to get DM
Free for 48 hours
