Have you ever had that feeling where you're using
one of these, you know, incredibly powerful AI
image tools, and it feels less like you're designing
something and more like you're just playing a
slot machine? Oh, absolutely. You type in this
perfect prompt, you hit generate, and what comes
back is just completely random. It's pure chance,
and the frustration, it really peaks when you
finally get that one great character. You know,
the lighting's perfect, the mood is there, and
then you just ask it to... Say, move the camera.
And it all falls apart. It all falls apart. Suddenly,
your character looks like a totally different
person. That's that AI slop everyone talks about,
that inconsistency that just kills a project.
Welcome back to the Deep Dive. Today, we're on
a mission, really. We want to guide you through
a very specific workflow to take back directorial
control over AI generation. We are moving beyond
luck. The goal is to turn one single perfect
image into an entire cinematic sequence. That's
it, exactly. We're moving you out of the passenger
seat and into the director's chair. We're going
to break down this workflow using Nano Banana
Pro for the images. It's powered by Gemini 3
and then VO 3 .1, faster the video part. So we'll
cover getting that foundation right, mastering
the language of cinematography, and then the
secret to getting controlled. predictable animation.
Let's just dive right into the core problem.
Okay, let's unpack this. Why are most of these
AI tools so stubborn? The source has kept using
the word inconsistency. Inconsistency is the
root of all evil here. So when you create a character
with some unique detail, right, like a robotic
eye or a specific scar. And then you ask for
a wide shot. Most models just forget those details.
They resample the whole scene. It treats your
new prompt like a brand new request. So it's
not even that it's forgetting. It's that it's
literally starting a whole new drawing from scratch.
It's ignoring the face, the clothes, everything.
Exactly. I mean, you watch a movie, the main
actor doesn't suddenly have a different nose
in the middle of a scene. We need that same level
of consistency. And that's where this reference
workflow comes in. Wait, so is this reference
workflow just a fancy term for image to image?
How is this different? How do we know it's not
just going to copy the lighting and forget the
character? That's the key question. A lot of
those older systems, they just use the reference
as a style guide. But Nano Banana Pro, using
Gemini 3's architecture, is built to hold onto
those key features. OK. So when you upload that
reference image, your master blueprint, and you
ask for a change, the model is forced to anchor
the character's geometry. That robotic eye, for
example, is locked in. It doesn't get washed
away. So this reference workflow, it's basically
the blueprint that forces consistency across
all the other shots you generate. It's the only
way to lock down that character's identity. And
the whole thing hinges on that single foundation.
Yeah. Which brings us to the most important step,
creating the foundation image. If you rush this
part, the whole thing just falls apart later.
Right. This is the image that defines everything.
The character, the lighting, the mood. All of
it, the textures, everything. And the example
in the sources, they didn't just use a simple
portrait. They chose this really complex cyberpunk
street food chef in a rainy Neo -Tokyo, which
seems designed to be difficult. It's intentionally
complex. That's where the real learning is. You
have to deal with steam and puddles and neon
lights. You can't just type cyberpunk chef and
hope for the best. You need precision. Surgical
precision. on the subject, the environment, and
the camera. The sample prompt they gave is basically
a technical checklist. It starts with the subject.
Old Japanese chef. gray beard, and then the key
detail. Robotic cybernetic left eye with a red
lens, stained apron. That red lens, that's the
anchor. That's the non -negotiable detail that
AI has to hold on to. And then the environment
gets just as specific. Ramen stall, heavy steam,
rainy Neo -Tokyo, pink and blue neon signs blurred
in the distance. If you don't lock that in, the
lighting will be all over the place in your other
shots. And finally, the camera. Medium shot,
eye level, cinematic lighting. Photorealistic.
Once you get that perfect image, that one file
will become your North Star. So that's the one
you keep coming back to. It's the one you upload
to the reference section every single time. I
still wrestle with prompt drift myself. I once
spent three hours trying to get consistent shots
because I was too lazy to perfect my first prompt.
An entire afternoon wasted. Exactly. I learned
my lesson. You have to invest the time upfront.
in that foundation image. So extreme specificity
on subject, environment, and camera angle is
what prevents all those inconsistencies down
the line. OK, this is where it gets really interesting.
We're shifting from being a prompt engineer to
being a director. We have our chef. He's consistent.
Now we need to build a shot library around him.
And to do that, we have to learn to speak the
language of cameras, because these tools, like
Nano Banana Pro, they understand cinematic terms
better than just vague descriptions. We need
to start big. The extreme wide shot. This isn't
just about showing the scenery, is it? No. It's
an establishing shot. It tells a story. It shows
the chef as this small human detail against these
massive dark skyscrapers. It sets the stakes.
Then you bring in the drama with a low angle
shot. Right. You want the chef to look powerful,
like a master of his craft. You look up at him.
You prompt for looking up from the counter level.
And the sources said the AI kept that red cybernetic
eye perfectly, even from below. The anchor held.
And you can flip that for a high angle. That's
more for vulnerability or for showing information,
right? Looking down at his hands as he prepares
the food. And my personal favorite for creating
tension is the Dutch angle. The tilted shot.
Yeah, the canted shot. You tell the camera to
tilt 30 degrees and it immediately puts the viewer
on edge. It signals that something is unstable.
You can even add heavy rain falling diagonally
to really push that dynamic energy. The AI knows
exactly what Dutch angle means. Whoa. I mean,
just imagine scaling this. If you can generate
10 or 15 perfectly consistent shots like this,
all ready to be dropped into an editor, that's
real cinematic production power. It is. Then
you need connection. So you use the over the
shoulder shot, you prompt for a blurry customer
in the foreground, and it pulls the viewer right
into that interaction as the chef hands over
the ramen. And finally, the really intimate detail
shot, the macro shot. Yeah, the extreme close
-up. For the cybernetic eye, you don't just say
macro. You have to get technical. Increase the
depth of field prompt. Emphasize the texture
of the lens, the reflection of the neon. So the
big takeaway is you're building this library,
this shot library of 10, maybe 15 consistent
angles all anchored to that one North Star image.
Then you're ready for motion. Exactly. And if
you really want to convey that emotional intensity
or instability, the Dutch angle is the classic
cinematic tool for the job. Now we make the move.
We switch over to VO 3 .1 fast because it's quick
and it, well. It understands physics pretty well.
So there are two methods here. The simple one
is method A, the start frame. Right. You give
via one of your images and a really simple prompt
like steam rises or rain falls. It's good for
adding a bit of atmosphere, just pushing the
sled a little. But method B is the real secret
sauce for anything complex. We call it the start
and end frame or laying the train track. OK,
explain that. Well, if you just tell the AI chef
walks away, the model has to guess. It starts
to improvise the physics, the trajectory, and
that's when you get that weird, unpredictable
morphing. The AI slop. The slop comes back. But
if you give it a perfect start frame our chef
standing, and a perfect end frame our chef walking
into the distance, both already generated consistently
in NanoBanana Pro, then I have no choice. It
has no choice but to connect the dots. It's like
a train on a fixed track. It guarantees you have
control over big camera moves, complex actions,
anything like that. So the two -frame method
is so vital because it forces the AI to connect
two consistent states, which stops it from just
making things up and morphing. Let's talk about
a hack here for efficiency. The source is mentioned
using an LLM, like Claude or GPT, to actually
write your prompts for you. This is a huge time
saver. Because trying to describe a subtle camera
move in just the right words can be really hard
for a person. So you upload your two frames,
say, the macro shot of the eye. and medium shot
of the face. And you just ask the LLM to write
a concise prompt that explains the camera move
needed to get from A to B. And you just copy
and paste that directly into Vio. It takes all
the guesswork out of it. And it lets you do really
professional tricks like a rack focus. You generate
image A, where the chef is sharp and the background
is blurry, and image B, where the chef is blurry
and the neon signs are sharp. And the prompt
is just... The prompt is rack focus from the
foreground character to the background neon sign.
And it works perfectly because both of those
states, A and B, came from the same foundation
image. Even with this whole system though, there
have to be common mistakes. What are the big
pitfalls people need to watch out for? Number
one is forgetting the foundation. You get excited,
you try to generate a new shot, but you forget
to put your North Star image in the reference
slot. And the consistency breaks. Instantly.
The fix is just discipline. Always, always use
the foundation image as your anchor. Okay, what's
mistake number two? Being lazy with prompts,
just typing something like different angle or
move camera a bit, it just confuses the model.
You have to be specific. You have to use the
professional language. Low angle, Broca, depth
of field. You have to talk to the tool like a
director talking to a cinematographer. Mistake
three, the morphing hands. Hands are still a
huge challenge for AI, aren't they? They are.
If your chef is doing anything complex, like
chopping or stirring, you absolutely have to
use the start and end frame method for that specific
action. It's the only way to minimize that weird
digital distortion. And the last one, which you
said is the most common reason a video feels
amateur. Ignoring lighting consistency. If your
wide shot is at night, your close -up can't suddenly
look like it's daytime. It breaks the whole illusion.
And the fix is just repetition. Just repetition.
You have to repeat the exact atmospheric keywords
in every single prompt. For our chef, that was
neon lights, rainy night, blue and pink hues
every single time, no matter the camera angle.
That lack of repetition is what makes so much
AI video feel so disjointed. It's the biggest
giveaway of amateur work. You have to lock that
atmosphere down. So when you put it all together,
what does this actually mean? The sources seem
to be saying that the era of AI video looking
like a, you know, weird dream is coming to an
end. It is. We are moving into an era of AI directing.
Control is finally starting to outweigh chance.
The recap is pretty straightforward, then. It
is. One perfect foundation image to lock in your
character. Use that to build a solid shot library
of different cinematic angles and then animate
it all with the start and end frame method for
total control over the motion. It's a much more
deliberate process than just hitting generate
over and over, but the payoff is moving from
random clips to actual controlled storytelling.
Your story told exactly how you see it in your
head. With that cinematic consistency completely
locked in. So the next step for you, the listener,
is to actually try this. Just do the first part.
Open up the tool and spend some real time making
one perfect character, your North Star. And then
just use that one file to generate three consistent
angles, a wide, a medium, and a close up. And
just feel that shift in control. It's a powerful
feeling. And here's a final thought to leave
you with. Now that you understand the cinematic
language that a low angle means power, a Dutch
angle means tension. Try applying that to the
real world. Think about it when you're just taking
a photo with your phone. It really does change
how you see everything around you. Until next
time. Thank you for joining us on this deep dive.