As a Peak Performance Health Strategist and founder of Supercell Health, I help high-performing founders and executives reverse biological age, boost vitality, and regain control over their health, using precision diagnostics, regenerative protocols, and data-driven optimization.

I work with leaders who are done with guesswork and quick fixes, those who demand results backed by science, not hype. At Supercell Health, we combine cutting-edge biohacking with evidence-based regenerative medicine to build fully personalized health systems tailored to your unique biology.

My mission is to help you reclaim energy, focus, and longevity, so you can lead with clarity, operate at your peak, and stay ahead in every area of life and business.

If you're a founder, investor, or executive looking to future-proof your health and performance, let’s connect..

Nate Rodgers

Joe Nilsen

Machine Learning Engineer 🤖 Revolutionizing E-Commerce with AI

The AI conversation in e-commerce has been hijacked.By people who've never shipped a product. By "experts" who discovered LLMs last year and now talk like they invented them. By creators recycling the same surface-level garbage with a fresh screenshot.They're loud. They're everywhere. And they're getting real operators burned.I've spent 15 years in the Amazon trenches. Built and exited two brands. Architected the systems behind TraceFuse, Seller Strategies, and Selletek.Now I deploy AI inside real operations while the influencers are still workshopping their next thread about it.I'm not here to add noise. I'm here to end it.What I share is the operational reality of AI that nobody else will show you. What to automate and what to never touch. Workflows that hold up under real volume. The mistakes that sink teams. What's working now versus what's already dead.No fluff. No theory. No "exciting updates coming soon."If it isn't deployed, it doesn't exist.

Founder

Our vision is to make the world a more connected place through the art of cooking and passion for food. The platform was launched in 2015 and was built upon challenging the status quo. Over the years, Culinary Connect evolved into a movement celebrating cooking, food, and love. These core principles are the cornerstone of what the modern-day brand is built upon.

Amazon is now hiding reviews from buyers.

I just went to check one-star reviews on a product listing. Standard operating procedure. Nothing unusual.

Instead of reviews, I got a blue info box.

"We're showing a limited selection of reviews. To see more reviews, you can send a request."

Read that again.

Amazon, the company that built its entire marketplace on transparent buyer feedback, is now telling shoppers they need permission to read reviews.

I tested this across multiple listings. Same result. Try to dig past the curated selection and you hit a wall.

This isn't a bug. This is deliberate. 

For sellers, the implications hit immediately.

Your negative reviews are no longer visible to most buyers. Sounds great until you realize your competitors' negative reviews are hidden too. The entire competitive landscape around social proof just shifted overnight.

For buyers, it's worse. Someone spending $50 on a product can't do basic due diligence without submitting a formal request. The friction alone will stop 99% of people from ever seeing the full picture.

Amazon has spent two decades telling the world that customer reviews are sacred. That transparency drives trust. That the review ecosystem is what separates them from every other marketplace.

Now they're gating it behind a request form.

No announcement. No explanation. No public acknowledgment.

The company that built its empire on customer trust just told customers to submit a request to see it.

Founder & Operator @ MajestIQ | AI Systems, E-commerce

Screenshot showing how Amazon is now gating reviews and no longer allowing people to read them. 

Well, this sucks.

Or does it?

Amazon just dropped a new Agent Policy inside the BSA update. Effective March 4.

If an AI agent or automated system touches Amazon Services, it must:
- identify itself as automated
- comply with the policy at all times
- cease access immediately if Amazon requests it

That is not a “policy update.” That is Amazon drawing a line in the sand for automated access and AI tooling.

The conference circuit “AI gurus” charging $3,000 a ticket to teach “AI-Powered Ecom Domination” are going to have some explaining to do.

The “AI automation” agencies are about to find out the difference between a demo and a durable system.

Good.

This is what happens when people build AI on vibes instead of constraints.

They assumed unlimited access.
They ignored guardrails.
They treated policy like a suggestion.

The weekend Lovable vibe-coding ninjas who duct-taped an “Amazon AI tool” together and started calling themselves experts are about to get their skirts pulled up.

No authentication framework.
No API alignment.
No governance.
No kill switch.
No audit trail.

Just a pretty UI, brittle workflows, and wishful thinking.

A lot of these businesses were never building infrastructure. They were renting risk.

Now Amazon has the language, the process, and the enforcement path to shut automated systems down on demand.

This is a massive advantage for operators who built the right way from the start.

- Compliant architecture.
- Proper API access.
- Systems designed to survive policy tightening.

The new restrictions on using Amazon materials for AI development and the added protection against reverse engineering will wipe out a chunk of the current tool stack.

If your "AI" was built by having ChatGPT generate prompts for Claude Code or a similar tool, it has an expiration date.

Amazon didn’t kill AI in e-commerce.

They killed the fake version of it.

A screenshot of Amazon's new business solutions agreement outlining how Amazon is going to treat AI agents and how all sellers must comply with these new policies.

I know a tremendous amount about deploying AI in e-commerce operations.

For everything I know, there are a hundred things I don’t.

That second sentence is what this entire space is missing.

Every week, this industry produces more fear merchants. More FOMO profiteers. More people who find the gap between what operators know and what’s possible, then monetize the anxiety instead of closing it.

- Someone reads one Amazon patent and self-proclaims an expert on Rufus.

- A digital marketer steals software and calls himself an authority on review removal.

- A scam artist emails you six times a week. Each one is engineered to make you feel behind. Webinar Access is $300. Another $200 for the slides.

My team was working with AI long before ChatGPT launched.

We were building models in Vertex AI. Training them to detect anomalies across the Amazon platform. Shipping real systems while most of this crowd hadn’t heard “large language model” yet.

We were working alongside some of the largest brands in the world, while this crowd was busy generating AI action figures of themselves with the latest image generator.

ChatGPT has been out for three years.

Even if someone went all-in on day one, three years in a technology this new and this fast does not make you an expert. It makes you early.

The only honest position is this:

You’re building. You’re testing. You’re getting humbled by edge cases. You’re adapting as the models, tools, and platforms change.

The real operators are doing exactly that.

They share what’s working.
They share what failed.
No agenda beyond the work.

They’re not trying to sell you something new every week.
They’re not charging thousands for access to a nonsense summit.
They’re not manufacturing urgency from a LinkedIn post.

They’re too busy doing the deal.

The fear merchants won’t survive another year. This technology will expose them. In the meantime, I will too.

Plan accordingly.

Square image of a parody action figure toy package labeled Fake AI Amazon Guru. Inside the plastic blister packaging is a clown character with a rainbow wig and clown makeup wearing a shirt that says AI Guru. The packaging is styled like a collectible figure and includes several accessories on the side such as a laptop displaying Expert AI Prompts, a book titled AI Prompts for Amazon, a mug that says I love GPT four, a bottle labeled Snake Oil Hustle Formula, headphones, a USB drive labeled AI, and a small Number One Guru trophy. The background features a dark blue circuit board style design.

Two months ago, I exposed the review removal scam industry on this platform.

Since then, more than 15 sellers have reached out to me with horror stories.

One reached out last week, which is why I’m writing this post.

He paid a scam artist “negative review removal” service over $24,000 in the last six months.

When I walked him through the audit process from my original post, his vendor went silent.

No case IDs.
No pre-removal documentation.
Nothing.

Because there was nothing.

Amazon removed those reviews.
His vendor just watched for the 404 errors (dog pages) and sent invoices.

This is not a gray area.
This is fraud.
And it’s worse than I laid out the first time.

Here's the part that makes it nearly impossible to catch:

Amazon’s review enforcement is getting more aggressive, more automated, more proactive.

That doesn’t make these vendors harder to run. It makes them easier.

Because Amazon is doing the clean-up at an industrial scale, every single day, and these people sit downstream collecting “success fees” from removals they did not cause.

The scam is simple:

→ They scrape your branded listings
→ They detect reviews that are already dead (404, dog page, broken link)
→ They send you a “win” report
→ They invoice you $250 to $500 per “removal”
→ You pay them for Amazon’s enforcement

They are not removing anything. They are watching Amazon remove it, then billing you like they caused it.

And the scam gets nearly invisible due to account-level enforcement.

When Amazon bans a buyer account for manipulation, every single review that account ever posted gets wiped.

Not just the bad ones. All of them.

Your removal vendor did not cause that. Amazon did.

But your vendor will invoice you for it anyway.

The problem is not performance-based pricing.

The problem is charging you without proving causation.

If you are currently paying a vendor for review removals, do this today.

Pull every invoice from the last 6 months.

For each “removal” they billed you for, demand:

1. Case ID created BEFORE the review disappeared
2. Timestamped confirmation the case was opened before removal
3. The policy violation cited by Amazon
4. Amazon’s response confirming removal due to that case

Not a screenshot after the fact.
Not a dead link.
Not a report showing the review is gone.

You already know it’s gone.
You need proof they made it go away.

For the last time, I'm shouting it from the hilltops...

Stop paying for the rain and thanking someone for their dance.

Infographic exposing Amazon review removal scam. Shows a 5-step fraud process: 1) Scrape listings, 2) Monitor deleted reviews showing 404 dead links, 3) Send "win" report, 4) Invoice the seller, 5) Collect "success fees" of $250-$500 per "removal." Highlights that Amazon's automated enforcement removes reviews at scale while vendors take credit. Bottom section shows red checkmarks next to "No Case ID, No Proof, No Documentation" with the message "They did not remove anything. Amazon did. They just took the credit."

I was not expecting to cry at my desk before 7 AM today.

Eric Dane died three days ago. ALS. He was 53.

Before he passed, he filmed an episode of Netflix's Famous Last Words. Part of it was directly to his daughters. Four lessons from a disease that was slowly taking his body.

I watched it this morning, and I couldn't move.

Not because it was sad. It was.

Because I felt like he was talking to me.

1. Live in the present.

He said he spent years lost in his head. Worry. Self-pity. Shame. It took a terminal diagnosis to force him into the now. And once he got there, he didn't want to leave.

"The past contains regrets. The future remains unknown. The present is all you have. Treasure it."

2. Fall in love with something.

Not someone. Something. Find the thing that makes you want to get up in the morning and hold onto it.

3. Choose your friends wisely.

Find your people. Let them find you.

"They don't do anything special. They just show up."

4. Fight with dignity.

The disease was taking his body. It was never going to take his spirit.

"Fight until your last breath. Fight, girls, and hold your heads high."

I move fast. I stay locked in on work. That's who I am. I'm not changing that.

But I watched a dying man tell his daughters to treasure the present, and I had to sit with the fact that I don't do that well enough.

I lose sight of what matters more often than I want to admit.

I'm carrying this with me.

More presence.
More intention.
Kinder to the people around me.
Less time in my own head running the next scenario.
More time actually being where I am.

Not because a LinkedIn post told me to.

Because a father's last words made it impossible to ignore.

Five-minute video worth checking out: https://lnkd.in/ekJ3tPPe

Eric Dane speaks directly to his daughters in a final recorded message, sharing four hard-earned lessons from living with ALS: live in the present, fall in love with something, choose your friends wisely, and fight with dignity.

“AI agents that run your Amazon business while you sleep.”

I keep seeing this pitch.

And every time, I think the same thing.

Either these people have never run a store at scale, or they’re selling fantasy to people who haven’t either.

Here’s what happens when you let autonomous agents make pricing, bidding, and inventory decisions without operator oversight:

 • Your repricer tanks margin chasing the Buy Box on a SKU you should have let go
 • Your PPC agent scales spend on a campaign with a 3-day attribution lag it cannot actually read yet
 • Your forecasting agent orders 90 days of inventory off a trend that died on Tuesday

I’ve deployed AI inside real e-commerce operations.

Seven and eight-figure brands.

The systems that work do not replace the operator.

- They surface decisions faster.
- They execute repeatable tasks.
- They flag anomalies.

The operator still makes the calls that matter.

The systems that fail are the ones sold as “set it and forget it.”

Because the person buying them stops paying attention.

And by the time they notice, the damage is already in the P&L.

The problem was never “too many tools.”

The problem was no system connecting those tools to a decision framework.

Replacing disconnected tools with disconnected agents does not fix that.

It just automates the chaos faster.

If someone says AI can run your store while you sleep, they’re packaging negligence as innovation.

Billboard showing AI agents as a sleep solution for e-commerce managers.

I got on a call at 8 pm last night fully expecting to be off in 20 minutes.

An hour later, I was still on the phone. Fired up. Notebook full of ideas. More energy than I had at 9 am.

The founders of Prompt Cowboy from Fourday wanted to connect with some of their users. I've been using the platform daily for a while. Had my whole team sign up and adopt it. So, I took the call.

Two co-founders. Both remarkable. The kind of people who are quietly building something serious while everyone else is out here posting about AI they've never deployed.

The conversation took many turns:

- Real AI pain points in actual operations. 
- Context management challenges that every operator knows, but nobody writes about. 
- The future of how these tools need to work versus how they work today. 
- Ideas bouncing back and forth.

I walked away reminded of something fundamental: The single best thing you can do as a builder is spend time with other builders.

Not content creators talking about building.
Not consultants advising on building.
People who are actually in the trenches, building.

That energy is contagious. It reignites the obsession. It pulls the best thinking out of you. 

Every operator I know who stays sharp over the long haul has this in common. They stay connected to people building at a high level.

This call was a perfect example. I showed up tired. I left inspired.

About the platform itself: Prompt Cowboy is significantly more than a prompt tool. The team had the foresight to build around context management and features that operators actually need as AI usage matures.

It's powerful. And from everything the founders shared, it's about to get a lot more powerful.

Do yourself a favor by checking the platform out.

I have no affiliation. You'll be glad you did.

Screenshot of the prompt cowboy platform shows how you can build different prompts and have the prompt type selection. It's in dark mode, a very powerful platform. 

A founder having their hands in every detail isn't a strategy.

It usually means the operation is still too fragile to run on its own.

Many founders I work with on automation hit the exact same wall. It’s rarely a technical wall. It’s an identity wall.

They believe the work is good simply because they are the ones doing it.

They assume their personal involvement is the only real quality control and that stepping back means the quality will inevitably drop.

I see this play out constantly with AI adoption in e-commerce. A team gets excited to automate a workflow.

But a week later, the founder is still right there, reviewing every generated listing, double-checking every report, and handling every edge case.

At that point, nothing has actually been built. You’ve just invented a more complicated way to bottleneck your own company.

What actually makes your output good isn't your physical presence. It’s a set of decisions you’ve internalized so deeply you forgot you were making them.

It's the standards you apply on autopilot and the pattern recognition you’ve built up over the years.

None of that requires your hands on a keyboard. All of it can be documented, systematized, and deployed.

The real work of scaling isn't just "adding AI." It's doing the hard job of pulling your intuition out of your head and turning it into a repeatable system.

• Standards: Clear definitions of acceptable work.
• Examples: Concrete before-and-after benchmarks.
• Rules: The absolute non-negotiables.
• Thresholds: Strict parameters for auto-publishing versus human review.
• Escalation paths: Defined routes for edge cases that don't rely on you.

We proved this across e-commerce, insurance, and legal operations this year. Different industries, same founder resistance, same result.

Once we extracted the logic from the founder's head and built it into a system, the output quality held.

In most cases, it actually improved. Systems don't skip steps when they're tired, and algorithms don't have off days.

Founders who scale fastest figure out exactly where their expertise actually lies. It never lives in their calendar.

It lives in the process they haven't bothered to write down yet.

Quality is protected by systems, not founder heroics.

If the machine stops the moment you step away, you aren't the engine.

You are the bottleneck.

A conceptual blueprint illustration titled "Founder Intuition (Tacit Knowledge)." A stylized brain representing the founder feeds data into a machine labeled "Logic Extraction Engine." The engine processes this tacit knowledge and outputs a structured blueprint divided into five key operational pillars: Standards, Examples, Rules, Thresholds, and Escalation Paths. Arrows show these five pillars flowing into a final, glowing circular schematic at the bottom labeled "Repeatable Process & Automation Schematic," featuring a robotic icon to represent fully automated, systematized business operations.

The Amazon space just minted more “AI experts” in six months than MIT has in twenty years.

Same people who were toggling bids six months ago now have AI in their headline, a Canva carousel about prompt engineering, and a masterclass launching next week.

Clown behavior.

They have never deployed a real AI system in production.
They have never measured hallucinations against a ground truth dataset.
They have never built a pipeline that runs unattended on live inventory without blowing up.

But they are selling “AI strategy” to $5M sellers like they invented electricity.

This is how operators get burned.
Not by AI.
By grifters.

A real AI system for e-commerce is not a prompt template.
It is not a screenshot of Claude output with a red circle around the “good part.”

It is infrastructure.

Evals.
Monitoring.
Retries.
Guardrails.
Rollback logic for when the model spits out nonsense at 2 a.m. and your catalog update is halfway done.

Most of these AI Amazon gurus cannot talk about any of that because they have never shipped anything.

They are tourists.
They are selling vibes.
They are taking your money and leaving you with broken workflows and a mess your team has to clean up.

Here is the 30-second truth test.

Ask them:

→ What model are you running in production right now
→ What is your fallback path when output is wrong, missing, or unsafe
→ How do you measure output quality over time, and what metric trips a failure
→ What gets logged, what gets retried, and what triggers a rollback

If the answer is “game-changing” and “revolutionary,” you have your answer.

No system.
No numbers.
No accountability.

If someone is selling you AI and cannot describe their evals, they are a clown with a Stripe account.

Operators who survive 2026 stop paying clowns.

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