How Ori Zilbershtein Turned a JSON Secret Into a Movement

Ori Zilbershtein, Founder @ Maxfusion.ai | +30K followers, recently posted something that made me stop scrolling: "My JSON prompting post blew up to 70K on Linkedin. That's what you get when you reveal an industry secret.

Even Google's official prompt suggestions lean into it, but no one actually giving you the blueprint..." That simple admission captured exactly what many AI practitioners feel: everyone is talking about structured prompts, but almost no one is showing their real system.

As Ori explained, some creators share a flashy JSON prompt, but they never reveal how they designed it, tested it, or scaled it. In response, he spent hundreds of hours experimenting with every JSON method and tool he could find and turned it into what he calls the JSON BIBLE: a collection of templates, tools, and explanations designed to make JSON prompting repeatable and reliable for everyone.

In this post, I want to unpack why that idea resonated so strongly, what makes JSON prompting so powerful, and how you can apply Ori's approach to your own AI workflows.

Why JSON Prompting Matters More Than Ever

Large language models are great at freeform text. They are less great at consistency, precision, and structure. That is where JSON prompting comes in.

Instead of saying, "Write me a marketing strategy," you define the exact fields you want: audience, offer, channels, cadence, KPIs, risks, and more. The model is no longer guessing what matters; you are telling it, in advance, how to think.

JSON prompting gives you:

Structure: Every response arrives in the same shape, ready for downstream tools.
Reliability: You can run the same prompt hundreds of times and still get machine-readable output.
Automation: Once the format is predictable, you can plug it into spreadsheets, CRMs, no-code tools, or your own code.

This is why Ori's claim that his JSON post "blew up to 70K" views makes sense. He is not just talking about prompts; he is talking about turning AI into infrastructure.

The Blueprint Everyone Talks Around (But Rarely Shares)

Ori pointed out that even Google's own prompt suggestions lean into structured formats, yet most people still treat them like a black box. They might share a snippet like:

The mother of JSON templates (this is the blueprint, the secret no one shares)

But they stop there. The underlying system remains hidden.

A true JSON blueprint goes beyond a single template. It answers questions like:

What problem is this schema designed to solve?
Which fields are mandatory, and which are optional?
What ranges, types, or formats are acceptable for each field?
How do you handle errors when the model outputs invalid JSON?

When you think this way, every prompt becomes an interface, not a one-off request. That is the mindset shift behind Ori's "mother of JSON templates" claim: he is not just handing over a prompt; he is handing over a pattern.

Inside a JSON Bible: Templates, Tools, and Breakdown

From his post, Ori highlighted four big components of his JSON BIBLE. Let us expand on why each matters.

1. The Mother of JSON Templates

This is the meta-template that sits above everything else. It usually includes:

A clear role for the model (who it is pretending to be).
Very explicit instructions on how to respond only in valid JSON.
A consistent structure for tasks: goal, constraints, schema, examples, and error handling.

Once you nail this meta-template, you can reuse it across:

Sales email generators.
Content calendars.
Product specs.
User research summaries.

The power is not in one prompt, but in the reusable architecture behind all of them.

2. 15+ Proven JSON Prompt Templates

Ori mentions more than 15 JSON prompts for different goals and styles. In practice, that might include:

Lead-generation workflows: capturing ideal customer profiles, outreach angles, and follow-up sequences.
Content systems: briefs, outlines, posts, and repurposing instructions all in structured fields.
Product and UX: feature breakdowns, acceptance criteria, user stories, and edge cases.

Having a library matters because it short-circuits trial and error. Instead of reinventing the wheel for every use case, you adapt a proven schema and move faster.

3. Free JSON Prompt Tools (Including Image-to-JSON)

One of the most intriguing parts of Ori's post is the mention of "5 Free JSON prompt tools (Including the Image-to-JSON engine, steal any image in one click)." That hints at a future where:
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