Thesis: Autonomous AI POD Dropshipping

Hey guys, I’d like to walk you through an example of how I approach and automate my POD business, leveraging all the new tech & tools available to us these days… (and some wacky ideas)

Earlier this year, I coded a few AI POD Product & Marketing Generators, all Trained on Systematic Frameworks – Optimized to take a Customer-Centric Approach to dropshipping.

Basically, they’re trained to first curate highly passionate & scalable POD Audiences using Facebook Data.

Then test, optimize & iteratively engineer the Perfect POD Product for these curated audiences, from First-Principles. We’re approaching from a market-product fit, instead of the other way around, which is the typical MO in dropshipping.

In plain English – we’re organizing endless POD Data, then trying to serve people products they dreamt about last night, rather than attempting to sell them on anything.

Although you see a UI with products & designs, this is not a public application, and never will be. It’s running on my own server.

I only coded this UI together, to use JavaScript, to capture precise image data from editors. So I could then train AI Vision Models, to automate hundreds of intricate POD Image Manipulations & Tasks.

For example, when you drag & drop your POD design to perfection on an image editor… You have technically also changed the design image’s width, height and positional coordinates.

Ok seriously, that’s enough with the code talk.

I’m an ecom nerd first & foremost – and this is about the First-Principles POD Dropshipping strategy… which those 600+ models (that I refer to as the Generator), are executing in the cloud.

*clouds (GCP Vertex AI for Vision & Tabular ⤴️ || OpenAI Fine-Tunes for Text ⤵️)

The app’s been collecting dust since I finished training the models in September (2023). But it’s the perfect tool to illustrate how you can take a more systematic, automated approach to every part of your POD Business.

• A Note from the Nerd that wrote this – (Idk what the gurus are click baiting you with these days. I study AI, data science & write python ALL Day. I’m going to give you a glimpse at an autonomous E-Commerce machine, if you want to take a peek.
  

  

  • …don’t mind the links.. I highly recommend you read this for the value, EVEN If sometimes you don’t really understand what’s going on.. the images are high-quality, so zoom in as much as you want. Sorry about the watermarks, they shouldn’t get in the way – 🎬 Enjoy 🍿)
    
    

    

So I call this POD Generator the “Passion-Flexer”, and it’s specialized in Full Sublimation POD Designs for Facebook Ads. But it’s just one example of many First-Principle Approaches you can take to achieving profitable POD campaigns.

You can take all of these actions that I’ll show you manually, just as I used to…

…but training AI Pipelines on MY OWN Actions, lets me operate more like a General, tactically focused on the end-goal, and spawn my own AI Soldiers.

Compared to before, where I was 1 soldier on the front lines, bogged down by insignificant tasks such as dragging around design images… and other meaningless low-impact decisions, like looking at the CTR of 1 Ad Set, or picking / ordering variants for products that had a 1/50 hit rate anyways..

Basically we’re trying to engineer a winning POD Facebook Campaign, such that it could be replicated systematically & programmatically..

• ..then Autonomously, with migraine-inducing levels of data science & modeling, that I’ll give you a glimpse of later on

And how exactly do we approach this from First-Principles? First by understanding that we’re trying to achieve an extremely specific metric-oriented goal – which is a Profitable AND Scalable POD Ad Campaign on Facebook. We start from nothing, and know ONLY what the data tells us. Then we test, optimize & follow the data to our metric-oriented goal.

Since our-end goal is tied to Facebook, the only true data we’ll ever directly know is what Facebook tells us in the ads manager, or elsewhere explicitly.

Therefore the most logical & objective method to sort by scalability, regardless of passion or niche, was by Facebook Audience Size:

• Going through the largest passion niches, one by one…
• Doing a complete interest extraction, of every single related interest in Facebook’s Database, for each niche
  • After an initial full google & wikipedia extraction, to research the niche
• Filtering out any non hyper-passionate or unrelated Facebook Interests
• Getting a True Facebook Audience Size verified from Facebook, which excludes overlap, for all the true interests of the entire niche
• Which gave us an initial target metric, closely aligned with our end-goal, to systematically sort the niches by (True Audience Size,Descending)

So long story short – I trained more AI’s, used Meta’s Facebook Marketing API, and wrote a whole AI Market Research / Facebook Ads Targeting application, into a separate tab of the app.

But the AI’s are also trained to apply my categorical targeting interest targeting framework, meant for cold products – to generate pre-flexed ‘Manual Lookalikes‘ in the database, in case we pursue it later on.

Now we’re starting to turn this up a few notches… And injecting crucial marketing know-how into the logic & engineering.

The reason you won’t see any prompt-based AI image generation throughout this is cause – I’m training a custom pipeline of Design Concepting, Generating, Editing & Manipulation AI Vision Models…

To be honest, I’m kinda cheating since we’re just going to finesse the AI’s from my Q2 POD Generator ‘Storyteller’, and paste them here as the base pipeline to start with.

• Trust me, this is way better than using the pipeline from the Q1 “Zodiac Lover Boy” Generator…

When it comes to AI, it’s good to take any logical advantage or head start that presents itself.. And this was perfect, since it already knows the extremely trivial stuff… like here for example, if we have Wolves & Space…

So thankfully the design pipeline already knows the basic things, such that Wolves howling, in the the starry night sky, with a full moon in the background – is a highly-correlated & applicable design scheme, out of infinite possibilities.

This seems like the perfect starting point, to kickstart the training for the Passion-Flexes. Cause as you can see here – The ‘Storyteller‘ Pipeline is already doing it’s thing, trying to predict the most apt character identity, theme & setting variables..

Whom also happen to be howling… in the starry-full-moon-lit sky..

• These are such intricate details, which would only be considered by the most passionate of wolf enthusiasts, if anyone.

It’s already giving me higher-impact & multi-dimensional testing ideas – How about correlating the wolf pack designs to families, and similarly, targeting lone-wolves to adults..?

And since we’re getting true passion interests… such as snowboarding magazines over ‘snowboarding’, or wolf conservation instead of ‘wolves’. We’ll leverage this as another opportunity to reverse-engineer our goal, similarly to as we’re doing with audience size.

That’s another calculated reason behind coding The ‘Passion-Flexer‘ to specifically take multiple Niches – to decrease the likelihood of similar POD Products being marketed to our potential customers. To systematically control barriers to entry like a lever, while striking an optimal balance with the Audience Size (Scalability) metric.

But also to increase the potency of the passion we are tapping into, with each layer / flex. And most importantly, to be able to SORT mathematically again.

Dropshipping is a data game through and through. All of the work that any of us put into launching a product, is ONLY to produce testing data to determine where to optimize further…

Therefore, I’m ghostwriting UI’s to train AI’s – then generating all of this and taking more of a backseat strategic approach. Letting fine-tuned AI do the heavy lifting for menial, common tasks.

I prefer to generate and automate all the menial tasks involved in launching any one specific product, catalog, campaign or store. Therefore I can make higher-level decisions which impact the overall approach, to increase the likelihood of our end-goal occurring.

For example, instead of focusing on individual decisions & actions on specific product pages, ad creatives, etc…

I focus on higher level & impact decisions, that have greater likelihood of AFFECTING ALL CAMPAIGNS such as:

• Which product types should logically be correlated together on a landing page, building higher cross-sell conversion rate directly into the code / logic
  
  

  

  
  
• Logically generating finishing / completing upsells from the conception stage, drastically increasing the AOV probability with every iteration
• Correlating the entire niche, product & theme selection with trends and seasons
  
  

  
• And countless other exciting ideas, without being bogged down by specific product-related tasks

In other words, If I want to sell a product to the people who LOVE snowboarding & penguins…

Then I will focus on structuring the most clever approach to rolling out EVERY POSSIBILITY to them, while letting the AI’s generate the menial work / data… and letting the ads data optimize to what this niche’s ideal product would be.

Here’s a great example to illustrate this. Since it was September, the general idea was to train the AI’s to produce a back to school themed campaign, where you had penguins riding snowboards.. (September = start of school year, here in the US)

We’ve already tactically selected snowboards & penguins together, due to their existing natural ‘arctic’ correlation. But with the added seasonality advantage of it nearly being winter. Also, Penguins correlate perfectly with the back-to-school-themed campaign, since it’s for children.

I’m mainly conceptualizing an extremely clever structure, in which to deploy strategically generated & correlated marketing assets, to give me further direction to optimize and reach the end-goal..

Because there’s still many ways to proceed here.. too many incremental decisions that could unknowingly lead us away from our goal. So although it’s a highly correlated, clever & congruent rollout so far – there’s still the question of product..

So I applied it to backpacks, gym bags, notebooks & more to be perfectly correlated with the back to school themed campaign.

At this point, I had my rollout structured, and it was left up to the designs… Therefore I trained the design pipelines specifically on the cartoonish children-themed design variations. Until I have an evenly distributed batch of correlated, but varied Penguins & Snowboarding designs.

Now that the tactical structure was decided, I backflipped into the AI Model HQ Section of the app, to map datasets, before training & configuring new fine-tunes, on the remaining tasks for this niche.

I’m rapidly running out of room on my UI at this point, and I learn about the “Offcanvas“. Basically if the application were a couch, the offcanvas is the the pull-out bed.

So I dropped a quick user interface into the app’s offcanvas… where I could intricately fine-tune the Datasets, for my Vision & Language Models.

Before configuring, then letting them generate full catalogs of products & campaigns, within the scope of this specific approach / how I trained them…

• Newly trained Penguin-Optimized, Mockup Image-Based Snowboarding AI Copywriter, is now Configured into the Landing Page Generator (testing all AI architectures for all)

ALL Fulfillment is ALSO Pure math. Just using numerical python & computer vision (cv2, numpy libraries), to improve image quality pixel by pixel, and then map printfile DPI to the exact state-of-the-art DTG Printing Specs, in real-time upon every order.

And lastly the Facebook campaign rollout itself, would obviously be listicles.

• In other words, instead of running the same $5/day to JUST ONE Penguin-Themed Bag Product Page…
  • We can increase our pace of iteration EXPONENTIALLY, At the Same Cost, By ALSO Using the same $5/Day, to send traffic to a listicle…
    • …testing various high-probability variations of this product type & design combination, on a conceptual level, with the same ad spend

And then I went into my campaign generator modal to configure those special AI-categorized audiences, which were already in the database from the earlier full-niche extraction… before dragging some listicles and creatives in there.

There’s also many times I’ll train the models to first try to crack the perfect design, by using a specific neutral product type as the control variable. Here’s an example of this in the Wolves X Space Passion-Flex: (video is mid-transition, I call these ‘Slidewheels‘)

And extrapolating onwards with the same EXACT logic… to further increase our Rate of data collection / optimization per dollar spent, by An ENTIRE ORDER OF MAGNITUDE by – I’m rolling out 7 listicles with 10 designs IN EACH CREATIVE, Via Carousel Format.

Also you may have noticed those URL parameters that are automatically added to the Website URL Field above…

I’m usually executing 2-5 API Calls (ads manager actions) per second, to model & run calculations on my metrics, then optimize live ads, ad sets & campaigns. Therefore I really can’t afford any funny business with the Pixel…

But now with the rollout configured, it’s time to let it rip! (x10)

• NOTE: I don’t recommend testing at this pace unless your KPI automation, attribution & database are all airtight


• Notice below how I’ve already drop-kicked my own fugazi Ads Manager, with some JavaScript Datatables & HTML, into another tab of the campaign generator modal..
  • Which is listening to display ALL my attributed server-side events, in REAL-TIME.

…also luckily I caught myself NOT taking the opportunity to Split-Test the Number of items on listicles – so we’re integrating this before I get carried away..

Anyways, the reason I’m bringing all this up today, is because the intellectual heavyweights at Canva FINALLY dropped their SDKs for us common-folk programmers..

..meaning I can train models on the precise actions I take within the Canva Editor, which is one of the slickest pieces of software I have ever seen. It’s gonna take all these generators up another 5 or 6 levels at least! (been learning React JS for this)

I also got access to GPT 4 Vision API & the new GCP Vertex AI Models. So honestly it might just be time to build a new Generator… gonna call this one: The ‘Sloganizer’

• (Involving Merch on Demand, ice-cold beer, deepfakes, fishing & more wacky ideas!)

If you’re interested in learning this approach to marketing & print on demand dropshipping right away, or maybe you just want a pipeline of fully-optimized POD Catalogs & Campaigns, then until the end of January, you can schedule a qualification call with me, here at this link.

If you want to learn more about me, or dig in deeper to these strategies, then you’re in luck! I’ve posted countless HOURS Of Free Video Tutorials of myself Scaling Products, Stores & Campaigns to my Free Facebook Group, over the years since 2018!

This is a self-supervised AI training tactic, called ‘Transfer Learning‘, that I leveraged when recording myself roundhouse-kicking my best Facebook interest targeting strategy, into a full custom app…

Which you can watch in my Free Facebook Group.

Also, in Addition to the 6+ Years of behind-the-screen Shopify, Facebook Ads & Marketing Video Content, that 11,000+ members are benefiting from for Free… (at least 2 GOT seasons-worth)

If you were searching for more awesome free content to read, before you’re ready to join the Free Facebook Group.. or if you also happen to dropship non-POD items like me…

• Then I recommend you check out my Free 30-Page A-Z Dropshipping Course, called ‘Winner Extraction Framework 0’ – which I copy / pasted into another article post on this same blog
  • (even wrote some custom CSS to make it nice & shiny)

This completely Free 30-Page Course Dropshipping Framework also includes a Case Study, where I follow this exact framework myself…

• To engineer winning psychological angles and creatives, in a niche I knew nothing about (Types 3 & 4 Women’s Hair)

I began coding & automating out my Aliexpress dropshipping and ecom copywriting frameworks years before the POD Generators

• (full video montage in Facebook Group)…

…and Winner Extraction Framework 0 is the perfect starting point For YOU, to learn how to engineer winning Angles & Creatives, from First-Principles – in your Aliexpress Dropshipping Business Today.

If after going through all this content, you’re interested in learning or leveraging this approach to dropshipping & marketing immediately..

..you can schedule a call with me, and see if you qualify to get involved at this link (if still active)

Maybe you’re just feeling a little overwhelmed – honestly that’s normal unless you’re weird like me.

Let’s say I placed a $1,000,000 bet on YOU achieving ALL of your long-term dreams in life, and I could ONLY give you ONE piece of advice before sending you off:

• Expect it to suck. Put 7,300 hours into studying Python Django, over the next 5-10 years.
  • Specifically python, and specifically Python within the context of a Django application
  • Start by building the last simple application, you wish you had, for your ads or store. NOT an Art Project. Something effective, performance-related, which requires you to read data from your Shopify Store and/or Facebook Ads Manager.
  
  

  

  

  • I’ll try to make some free tutorial videos for this in my Facebook Group, but there are A-Z tutorials on YouTube – and ChatGPT / Forums cover the rest, for you to do this comfortably in 10 years. 5 if you already know basic english & math.
• You might even end up building yourself a useful app, but it’s not about that at all. By doing it this way, you’ll basically have such a precise set of technical skills as a core foundation – To eventually train AI’s to do anything, since you’ll have the python, pandas, SQL, database ORM & ETL Foundation to transition to data science.





• Then even deploy it into a SaaS with AWS or GCP… cause you’ll know Cloud Computing, DNS, Routing, Servers & Django Templating, which lets you use {% Shopify Liquid Templating %}, DBT & much more – maybe I could show you how to acquire users profitably too.
  
  

  

  

  • All while being able to land a high-paying job, at ANY point, THAT WILL NOT BE REPLACED BY 2030.

• LASTLY, What I wish They Told Me is – This is not the “code” you think of from the 1950s… it’s how you offload & maximize your Brain’s compute, for ANYTHING, in our exceedingly digital world. It is a superpower, and valued as such in the marketplace. Low supply, endless demand. Endless.

FYI – It took FAR LONGER to memorize all the characters, storylines of the episodes & seasons – of Sopranos, than it did for me to memorize ALL the python functions I’ve ever used..

If you execute these straightforward actions – Specifically in the next 5-10 year window.. Then raise my initial $1M bet to $10,000,000. This is a Certified “Get Filthy Rich Slow” Method.

..but if you’re in a place in your life or business, where you’re willing to exchange money for time… then I have just rolled out a brand new, fairly-priced & innovative offer that you should consider immediately.

• (if: link still active, else: Group)
  
  

  

  

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Meet the AIuthor, Dropship $(atoshi), an esteemed disciple of Ecom Jonin, and the Ecom Cloud Dojo’s charismatic master of cross-platform media acquisition.

As adept as a ninja traversing moon-kissed rooftops, Dropship Satoshi’s skills in e-commerce media buying radiate across all platforms and verticals with the acuity of a ninja star.



With the wisdom of a seasoned Samurai and the precision of an arrow in flight, he targets not just any customer, but the right customer, at the ideal time, on the optimal platform.

Together with his master Ecom Jonin, he slashes through the dense fog of E-commerce marketing, leaving in his wake a trail of golden opportunities and cost-efficient conversions.

Armed with the precision of a well-aimed shuriken and the negotiating prowess sharper than a meticulously crafted katana…



Possessing an uncanny understanding of every conceivable vertical, $(atoshi) channels his wealth of knowledge into acquiring customers at lightning-fast speed, while maintaining unparalleled cost efficiency at auction.

Much like a ninja blending with the shadows, D.S. Satoshi seamlessly navigates the terrain of digital platforms, spotting golden opportunities invisible to the untrained guru.

With his unique approach, every impression and click drives you closer to sales victory and ultimate conquest of the Ecom market.

Get ready to be swept in his dynamic whirlwind, watching in awe as Dropship Satoshi cuts down cost per acquisition to help bolster your bottom line.

With Dropship Satoshi at the helm, no platform or vertical remains unconquerable. (he’s listening on comments 🐍)

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