When we talk about building AI applications right now, the conversation usually revolves around the same three things: optimizing email workflows, generating marketing copy, or writing code faster.
Don’t get me wrong, I love productivity. But as a developer watching this space explode, I’m noticing a fascinating trend bubbling under the surface. It’s a niche that is wildly popular, incredibly engagement-heavy, and shockingly low-competition for developers.
I’m talking about the intersection of AI and the esoteric: Tarot reading bots, astrology engines, and AI analysts for ancient texts.
It sounds woo-woo, but from a technical perspective, it’s actually brilliant. And believe it or not, the exact same technology I’m using to build my practical apps, like Solomon’s Spirits or Grimoire Oracle is what powers this digital mysticism.
Here is why this niche works, and how the tech connects.
Why AI is Surprisingly Good at the “Mystical”
If you strip away the spiritual elements of something like Tarot or astrology, what are you left with? Complex systems of pattern recognition and symbolic interpretation.
- Tarot is essentially data visualization. You have 78 cards (data points), each with specific symbolic meanings attached to them. When a user draws three cards, the “reader” must synthesize those three distinct data points into a coherent narrative based on their relative positions (past, present, future).
- Astrology is a massive mathematical rule set. If Planet X is in Position Y at Time Z, then Interpretation A applies.
Large Language Models (LLMs) are incredibly good at exactly this. They don’t “believe” in the stars, but they are masters at ingesting massive sets of rules and symbols and generating human-sounding interpretations based on those rules.
While everyone else is fighting over building the next “Chat for PDF” wrapper for corporate finance, there is a massive, passionate audience waiting for a “Chat for Hermetic Texts” wrapper.
Connecting the Dots: How My Tech Fits In
This is where things get interesting for me as a developer. I’m not currently planning to pivot into building digital ouija boards. But as I build out my portfolio of practical AI tools, I realize the underlying architecture is identical.
Example 1: The RAG Connection
Let’s look at one of my current projects, The AEther Connex.
The goal of that app is to let a business upload their boring internal handbooks and ask questions about company policy. To do that, I use RAG (Retrieval-Augmented Generation). The AI searches the document for relevant info and uses it to answer the question accurately.
Now, imagine swapping that employee handbook for a PDF of a 16th-century Alchemical manuscript or the complete works of Carl Jung. Suddenly, you have a highly specialized “Esoteric Research Assistant” that scholars or enthusiasts would kill for. The code is 90% the same; only the data source changes.
Example 2: Structured Outputs and Rules
Or take a look at Birthday Bonds.
That app is designed to take messy user input and force it into a structured output to trigger specific actions.
An astrology app works the same way. It takes structured input (birth date, time, location), runs it through an API to get planetary positions (the rules engine), and then uses an LLM to generate the “horoscope” text based on those rigid constraints. It’s a structured data pipeline hidden behind mystical language.
The Developer’s Opportunity
I’m highlighting this niche because I think a lot of developers are sleeping on it. We get too focused on B2B SaaS products.
If you are learning to code AI, sometimes the best project isn’t another boring business tool. Sometimes it’s something weird that people are passionately interested in. Building a “Mean Tarot Bot” that roasts users based on their card pulls might teach you more about fine-tuning a model’s personality than building another customer service bot.
The tools I’m building right now are focused on practical productivity. But it’s fascinating to know that the same engine under the hood of my Birthday Bonds app is capable of “reading the stars.” It just depends on where you point the data telescope.
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