JSON Prompting with Nano Banana Pro
Key Points
- The speaker leverages Nano Banana Pro with JSON prompting, using a custom translator that converts plain‑English descriptions into machine‑readable JSON parameters.
- JSON prompts are ideal when you need exact, high‑stakes specifications (e.g., precise marketing images or UI designs) because they give the model clear, structured guidance.
- JSON is not a universal prompting solution; it hinders creativity and is unsuitable for open‑ended “vibe” generation where flexibility is desired.
- Nano Banana Pro’s strength lies in its compositional control—JSON schemas expose stable handles (camera angle, subjects, components) that allow targeted edits without re‑generating the entire scene.
- Unlike “vibe” tools such as Midjourney, Nano Banana Pro focuses on correctness and precision, enabling clean swapping of visual grammars and scoped mutations through its JSON schema.
Sections
- JSON Prompting for Precise Model Control - Nate describes his custom workflow that translates plain‑English requests into JSON for Nano Banana Pro, highlighting its effectiveness for detailed, high‑stakes tasks while noting it isn’t a universal prompting solution.
- JSON Schemas Enable Reproducible Multi‑Domain Generation - The speaker explains how defining core entities with JSON schemas lets Nano Banana Pro reliably create marketing images, diagrams, and UI components, supporting exact replication, version‑controlled diffs, and integration into serious product pipelines.
- From Prompt to Full UI JSON - The speaker demonstrates how a brief instruction to an AI model generates a complete, detailed JSON schema for a creative alien user interface.
Full Transcript
# JSON Prompting with Nano Banana Pro **Source:** [https://www.youtube.com/watch?v=4u48pDYxfHc](https://www.youtube.com/watch?v=4u48pDYxfHc) **Duration:** 00:09:48 ## Summary - The speaker leverages Nano Banana Pro with JSON prompting, using a custom translator that converts plain‑English descriptions into machine‑readable JSON parameters. - JSON prompts are ideal when you need exact, high‑stakes specifications (e.g., precise marketing images or UI designs) because they give the model clear, structured guidance. - JSON is not a universal prompting solution; it hinders creativity and is unsuitable for open‑ended “vibe” generation where flexibility is desired. - Nano Banana Pro’s strength lies in its compositional control—JSON schemas expose stable handles (camera angle, subjects, components) that allow targeted edits without re‑generating the entire scene. - Unlike “vibe” tools such as Midjourney, Nano Banana Pro focuses on correctness and precision, enabling clean swapping of visual grammars and scoped mutations through its JSON schema. ## Sections - [00:00:00](https://www.youtube.com/watch?v=4u48pDYxfHc&t=0s) **JSON Prompting for Precise Model Control** - Nate describes his custom workflow that translates plain‑English requests into JSON for Nano Banana Pro, highlighting its effectiveness for detailed, high‑stakes tasks while noting it isn’t a universal prompting solution. - [00:03:07](https://www.youtube.com/watch?v=4u48pDYxfHc&t=187s) **JSON Schemas Enable Reproducible Multi‑Domain Generation** - The speaker explains how defining core entities with JSON schemas lets Nano Banana Pro reliably create marketing images, diagrams, and UI components, supporting exact replication, version‑controlled diffs, and integration into serious product pipelines. - [00:06:56](https://www.youtube.com/watch?v=4u48pDYxfHc&t=416s) **From Prompt to Full UI JSON** - The speaker demonstrates how a brief instruction to an AI model generates a complete, detailed JSON schema for a creative alien user interface. ## Full Transcript
I want to let you in on a secret. I use
Nano Banana Pro with JSON prompting and
I've had great results. And you might
wonder, well Nate, what is JSON? JSON is
just computer language that defines
parameters. All I'm doing is giving the
model machine readable parameters. And I
wrote a prompt, so you don't have to
know JSON to write JSON for Nano Banana.
You can describe in plain English what
you want, and the translator I wrote
will render it right back into JSON,
which will give Nano Banana a lot of
structure. But why, right? You're like,
"Well, Nate, is this a universal prompt
act?" The answer is no. It's not a
universal prompt tack. And the reason
why is that prompting specification only
works when you are sure about what you
want. In so many cases with models, what
we want is actually to leave the model
room to be creative. JSON is actively
bad in that situation. It's also
objectively not true that JSON is the
only correct way to prop models. I have
seen some Twitter hypsters claiming
that. That's just not the case. models
are trained on lots and lots of
languages. They prompt well lots of
different ways. What is useful about
JSON is being clear about what you want
for a high stakes proposition. So if you
need a marketing image that has a
particular look for the can of beverage
and you have to have the model wearing a
particular thing and you have to have
the lighting in a particular way, that's
a JSON prompt. I know it sounds funny,
but that's a JSON. If you have a UI and
you want to define it very specifically
and get the colors exactly right, it's a
JSON prompt. That is why Nano Banana Pro
is so interesting with JSON and we're
not talking about it enough because Nano
Banana Pro is a renderer. It is not a
vibes machine. Midjourney is a vibes
machine. You can say I want a neon
cyberpunk schema and and Midjourney will
just vibe that. Nano Banana Pro thinks
about what it's doing and is very
precise. It lives and dies on
correctness. JSON gives it correctness.
It gives it the clarity. One of the
things that makes Nano Banana most
powerful is its compositional control.
You can pivot a camera around the same
scene. You can use different themes,
different layouts, different notations.
JSON makes all of that explicit so that
there are actual human readable
properties that you can vary to control
the camera around the scene. This gives
gives each important thing in the image
a stable handle, right? You can have a
subject that's different from an
environment. You can have a component ID
in a UI that's distinct. And once those
handles exist, which is really all the
JSON schema is, you can say regenerate,
but only touch this one thing. And
that's where Nano Banana shines, right?
I'm not turning the whole scene over to
the model again. I'm just asking for a
very scoped mutation through a computer
schema that Nano Banana will understand.
Nano Banana also spans many many visual
grammars and schemas let you swap those
grammars really cleanly. So Nanobanana
isn't just a photo app. It's not just a
UI app. It spans multiple grammars. It
can be photo, it can be diagram, it can
be UI. Each of those visual grammars has
almost no shared surface level
vocabulary, but they do share a pattern.
Each domain has a set of core entities
and a rigid way that those entities
relate. and JSON schemas help you pin
down the visual grammarss that underly
marketing images that underly diagrams
and UI. In other words, all three of
them respond to the idea that you will
get a structured blob with named fields
and your job is to honor those fields.
Nano Banana can work with that to create
a photo. It can work with that to create
a diagram and it can work with that to
create a UI. What's particularly
valuable is that Nano Banana Pro
effectively can use this ability to
render correctness to work across all of
these domains. And with JSON, you can
work across all these domains, too. I
can create cool marketing images using
JSON. I didn't think I could create cool
marketing images, but apparently I can
because I understand how to manage Nano.
Schemas basically turn Nano Banana Pro
into a tool instead of a toy. Right? If
Nano Banana Pro is going to sit inside a
really serious product stack with design
tools, with code generation, you need
reproducibility. So, give me the exact
same screen again needs to be possible.
You need diff. So, show me what changed
in this prompt between V3 and V4. You
need the ability to actually test
whether a prompt worked in a reliable,
reproducible way. That is what JSON
schemas offers because you can version
control the JSON and say, "We added this
one thing to the JSON. Look what
happened." looked what look what
differed between the last run and this
run. You can enforce rules like you know
don't reduce your tap target for this UI
below 44 pixels and that becomes a part
of your JSON schema. You can actually
encode things like accessibility into a
JSON schema. Nano Banana effectively
becomes something you can reason about
and govern instead of the designer type
to prompt into a nice screen. And I
guess we have something that looks good
but no one knows why. You want to have a
more deterministic set of specifications
and the combination of an image renderer
that values correctness in Nano Banana
Pro and JSON schemas help you get there.
Let me show what the flow practically
looks like. The human will say something
messy. I need a mobile habit tracker app
app with a dark theme and I have three
screens in my mind and a calendar view.
I want it to feel sort of like notion
meeting Dolingo, right? If you have a
prompt like what I'm building here, the
LLM will interpret that. It will apply
your design convention. It will fill out
a JSON schema with the screens, the
components, the tokens, and the layout
primitives, and it will let you review
it. You can then look at it and say,
"Oh, yeah, okay. I think this looks
good." And then you can pass that to
Nano Banana Pro to render. And all of
that detail is there for Nano Banana Pro
to pick up. And if you want changes, you
can just swap out one field at a time.
And one of the beautiful things about
this approach is it helps people not
familiar with JSON learn one of what I
believe is the most valuable skills in
the world which is learning to read
pseudo code. Pseudo code like J this
JSON blob is not real code. It just
looks like code. All it is is a fancy
list that an AI can read and understand
and take seriously. If you can learn to
read it, you become someone who can read
the kinds of structured inputs that AI
values. As you'd expect, that helps your
career these days. But the larger value
from a workflow perspective is that you
as a human can retain your current
preference. Right? If you like to write
paragraphs to describe your work, you
can do that. If you like to write
bullets, you can do that. And then you
can pass it to an LLM with the JSON
converter prompt that I've built and you
can actually get
a complete output where the JSON is
going to be there and then you can read
it. You can modify it. You can just pass
it right to the model. Now you might be
wondering, Nate, how does this all work?
Can you show me an example? You're just
talking to the camera. Yes, I can. Let
me show you how I turned a very, very
short piece of text for me. one that
would be shorter than I would normally
use into a really interesting new
creative interface. Okay, here we are.
This is an actual JSON schema. All I've
given it is please respond with a filled
out JSON template that is for a very
creative UI about aliens. Only respond
with the JSON. That is like eight tokens
on the UI. I would normally give so much
more, but I'm showing you how much power
you have just by appending it. And then
I give the JSON template and it is a
lengthy JSON template, right? Like it
goes and goes and goes and goes. You get
the idea. It responds with a full JSON
template. It's filled it all the way
out. It has imagined what an alien UI
looks like. If I had wanted to be more
specific, it would have filled more
specifics in here. But you can see it's
being extremely clear about what all of
these things are for. Um, and then it
goes all the way down and it says we're
done. And this is what I get the first
time. So, we're going to actually show
you. So, I I went through the first time
and I said, "What do you think about
this?" And you'll notice, by the way,
that I said initiate first contact or
the JSON did. It has it right there.
This is a very faithful rendition and
the model actually graded it as very
faithful and perfectly on brief. I
thought it could be better. I went over
to Google AI Studio and I pasted this in
and I said, "Hey, I would like you to
faithfully follow this JSON and produce
a buildable wireframe of this design."
Because I thought the angle being tilty
was actually not what I wanted and I
wanted to remind it to be professional.
That is me adding a little bit of
instruction over the top, but it's the
exact same JSON. Look at how I get a
very nice, faithful JSON response. It
reads all of this. It's a long response.
It thinks it through and now it's given
me a perfect highfidelity. This is
exactly what it looks like wireframe
that is reproducible. Look how
reproducible this is. This this is
essentially the exact same image. It is
just done tilted forward as a
professional wireframe. I get
reproducibility. I can hit initiate
first contact in both of these very very
easily. My point here is not that you
build alien user interfaces. My point is
that if you use JSON and if you take it
seriously as a tool, you are going to be
able to get farther with professional
use cases for Nano Banana Pro because it
responds to the precision because it
values correctness. So, I'm going to put
a bunch of prompts in the Substack that
get into this JSON piece, the JSON
translator, because I want you to be
able to do this for yourself. I want you
to be able to do this for photos, for
marketing photos, for other kinds of
photos. I want you to be able to do this
for user interfaces and I want you to be
able to do this for diagrams. I think
it's important that we be able to
actually use the tools that we're given
and part of it is discovering how they
work and I think that JSON is an
undersold value ad for Nano Banana Pro.
So hop in. Don't be afraid of the code.
It's not really code. It's pseudo code
and the LLM translator will help you so
much. Cheers.