You've got this great idea for an AI video. You
type it in. You hit generate. And, well, it's
a mess. Yeah, a total mess. Your main character's
face just keeps morphing. It turns into someone
else entirely in the background. Right. The visual
style feels incredibly chaotic. What was supposed
to be cinematic looks like a complete and utter
accident. We have all been there. It's incredibly
frustrating. You kind of feel like you're playing
a slot machine. You just pull the lever and hope.
Welcome to the deep dive. Today we are breaking
down a step -by -step guide. We're exploring
exactly how to build AI video from scratch. We're
looking at a specific three tool sequence. We're
talking Cloud AI, ChatGPT, and Google Flow. That's
the stack. This sequence guarantees consistent,
highly cinematic results. It's really about moving
from total randomness to actual directorial control.
Right. It really is a mindset shift. We need
to understand why those initial generations turn
into chaotic messes. It's honestly not about
writing a better, more complex prompt. It is
entirely about the sequence of events. The sequence.
Let's unpack that. The fundamental rule is this.
You must build your visuals as static images
first. You have to do before animating anything
at all. Generating static images is much faster.
It's also significantly cheaper than generating
video. You know, I still wrestle with prompt
drift myself. Oh, yeah. Watching my character
morph into a totally different person halfway
through a scene, it is a really helpless feeling.
Absolutely. Everyone experiences that prompt
drift initially. It's like stacking Lego blocks
of data. You need a solid, unmoving base before
you add the moving pieces. Exactly. If you build
on a shaky foundation, the whole scene just collapses.
Yeah. But why is that? Why is fixing a mistake
in a video so much harder than in a static image?
Because video multiplies variables across time.
Static images isolate those variables. Think
about what a video actually is. Right. A standard
film runs at 24 frames per second. If you generate
a 10 -second clip, the AI isn't just making one
picture. It's making 240 pictures. Exactly. 240
distinct images. And here is the truly difficult
part for the AI. It has to remember what happened
in frame one. It has to apply that exact memory
to frame two. Then it has to guess what naturally
happens in frame three. That is an immense computational
burden. The system has to maintain the physics
of a moving scene. It is massive. Eventually
the machine drops the ball. The math just gets
too heavy. It forgets the color of the character's
jacket. It forgets the exact lighting angle on
the coffee cup. Wow. But an image generator only
has to solve one single frame. It concentrates
all its processing power on that exact moment.
You get a highly detailed, perfectly accurate
picture. So video multiplies the chaos across
time. Images isolate the problem entirely. Exactly.
It pins the butterfly to the board, so to speak.
You lock in the exact visual style. You fix the
character's faces. Right. You perfect the lighting
before a single frame actually moves. Which means
we need a rock solid textual blueprint to start.
Yeah. And that brings us to the first tool in
this sequence. We're talking about Claude AI.
Right. Before you even look at an image generator,
before you open a video tool, you need a very
clear, structured plan. Claude AI handles this
entire blueprint stage. The guide we are looking
at uses a very specific example. It starts with
a remarkably simple story. A father and daughter
escape a sudden volcano eruption. They're driving
around desperately searching for gas to survive.
It's a great example. It has inherent tension,
but visually it's very contained. But let me
push back on that a bit. Doesn't giving the AI
a highly complex story make for a richer video?
Like, if I want a sprawling sci -fi epic, shouldn't
my premise be sprawling, too? It sounds counterintuitive,
but no. A simple premise is actually much better
here. Think about how the AI processes text tokens.
OK. If you give the AI a complex novel with 10
subplots, it won't know what visual elements
to prioritize. Its attention gets scattered.
It loses focus on the actual scene. Precisely.
Two characters and one clear goal is perfect.
It allows the AI to extract very clear visual
directions. It knows exactly who to light and
what they're doing. Keep the core idea incredibly
simple so the AI can extract clear visual directions.
Beat. That's the secret. So you take that simple
story to Claude, then you create an AI video
prompt skill. Let's define that. For someone
new to this, what is an AI video prompt skill?
Simply put, A saved instruction file for repeated
AI tasks. So you aren't just typing into a blank
chat box every time? Exactly. You are setting
up a permanent framework. You tell Claude how
to behave as a master video director. Nice. You
load this skill automatically whenever you want
to make a video. It saves you from constantly
explaining the rules to the AI. What are we actually
instructing Claude to do with this skill? What
are the outputs we need? This skill demands three
very distinct things from your simple story.
It forces Claude to break the story down systematically.
First, it generates a design sheet prompt. A
design sheet? Kind of like concept art for a
movie. Right. Exactly like concept art. This
prompt outlines the characters, the core environment,
and the color palette. It establishes the visual
roles. Second, Claude generates a storyboard
prompt. This breaks the story down into specific
camera angles for each shot. Close -ups, wide
shots, panning descriptions. Yes, it acts as
the cinematographer. Third, it generates individual
video prompts for every single scene. These are
highly detailed instructions for the final animation
phase. So Claude gives us this perfect structured
text. We have the design sheet prompt, the storyboard
prompt, and the video prompt. Yeah. But text
isn't a movie. We need to actually visualize
these blueprints. This is where we transition
to the second stage. This is where ChatGPT comes
in to lock in the visual style. We're moving
from planning to actual image generation. You
open ChatGPT. Specifically, you want to use the
Deli 3 image generation feature inside it. Your
first move is creating that master design sheet.
We paste the design sheet prompt that Claude
just wrote for us. You do. But the guide emphasizes
a crucial addition here. You must manually add
a specific phrase to the end. OK. You type. High
detail, wide format, every element clearly visible.
Why those exact words? It sounds like an arbitrary
magic spell. Why not just say, make it look good?
Because diffusion models can be lazy. If you
just say, make it look good. The AI focuses on
aesthetics. It might use heavy shadows to look
cinematic. It might blur the background for an
artistic depth of field. Which hides the actual
details we need. Precisely. We are building a
reference document, not a final piece of art.
Those specific words force the AI to prioritize
spatial clarity. Makes sense. We need flat, even
lighting. We need to see the character's exact
face. We need to clearly see the buckle on their
backpack. This image is the anchor for everything
else. So you get this design sheet back, you
look it over, but what happens if chat GPT gets
a small detail wrong? Say the daughter's backpack
is the wrong color, or a photograph on the table
is facing the wrong way. The instinct is to just
rewrite the whole prompt and try again. That
is the biggest mistake people make. Do not rewrite
the whole prompt. Why not? Because rewriting
changes the underlying seed noise, the AI will
generate a completely different image from scratch.
Oh, wow. The lighting will change. The faces
will change. You lose all the good stuff just
to fix one tiny detail. So how do you fix it
without destroying the image? You add one specific
localized correction sentence. If the photograph
is wrong, you literally just type only the back
of the photograph is visible. You just replied
the image with that one sentence. Yes. The AI
understands localized constraints much better.
It keeps the original context window intact.
It just surgically alters that one specific element
you mentioned. Let me play devil's advocate here.
Why not just skip this design sheet entirely?
Okay. If we have the text prompts, why not generate
the storyboard right away. Because without that
visual anchor, the AI is just guessing. It will
hallucinate a new visual style for every single
panel. The dreaded prompt drift again. Exactly.
In panel one, your character is wearing a clean
blue jacket. In panel two, it's suddenly a dirty
denim vest. Right. The lighting shifts from overcast
to bright sunlight. It looks amateurish. The
design sheet is the exact visual anchor keeping
the AI from hallucinating. It absolutely is.
So once that design sheet is perfectly locked
in, once the character is looking Exactly right.
Then, and only then, do you generate the storyboard.
You take the storyboard prompt Claude wrote earlier,
you paste it into ChatGPT. But here is the critical
step. You must attach that perfect design sheet
image to the prompt. You are literally feeding
the image back into the AI. You tell ChatGPT
to match those exact characters and colors. You're
giving it visual reference, not just text. Yes.
And you add one more specific phrase here. You
type, high detail, each panel clearly separated
and readable. Because a storyboard is a grid
of multiple images. Right. It's usually a two
by six grid, 12 panels total. If the AI blends
the borders of those panels together, it becomes
a mess. You need clean, distinct shots because
you will be isolating them soon. We're going
to take a quick pause right here. We don't go
anywhere. And we are back. So far, we have planned
our text in Claude. We have locked in our visual
style with a design sheet in ChatGPT. And we
just generated a perfectly consistent 12 -panel
storyboard. Everything matches. You have a comic
book version of your film. It is static, but
it is visually perfect. Now comes the magic.
We finally breathe life into it. We are moving
to the third tool. Google Flow. This is the animation
phase. Google Flow uses an underlying technology
called VO3. Let's define VO3 for the listener.
An AI engine that turns static images into moving
clips. Simple enough, how do we actually use
it? You take that full 12 -panel storyboard image.
You upload that single image file directly into
Google Flow. OK. Then you paste those 12 specific
video prompts, the ones Claude wrote for us back
in Stage 1. So we are giving Flow the static
visual grid plus the text instructions of how
things should move. Exactly. And you add a master
instruction to the top of the prompt. You tell
Flow, generate a scene using shots in the uploaded
film storyboard sequence. The guide mentions
adding one more strict constraint here. You have
to explicitly tell the AI, no subtitles, and
no music. Why do we need to specify that? We
obviously want sound and text in our final video
eventually, right? We do. But AI video generators
have a really bad habit. If they try to generate
audio or text alongside the video, it bakes it
directly into the file. It's permanently attached
to the visuals. Yes. AI -generated text often
looks like alien gibberish. It hallucinates weird
letters. AI -generated music might have tempo
changes you hate. That makes sense. If that audio
is baked into your raw video file, you cannot
separate it later. You ruin your non -linear
editing options. Blank audio and clean frames
give you total control during the final edit.
It beat. Exactly. Keep the raw footage as clean
as possible so you hit generate and flow goes
to work. It processes the grid. It does. And
whoo! Imagine turning a flat 12 -panel grid into
15 seconds of cinematic motion instantly. Yeah.
It analyzes the spatial relationships in the
static image. It calculates the temporal consistency
required to make it move. It just blows my mind
every time I see it work. It's pretty wild to
think about. You are taking a flat static comic
strip and getting a living, breathing movie out
of it. Absolutely. It feels like something straight
out of a sci -fi novel. But wait. We have 12
distinct panels, and flow generates a 15 -second
clip. That math is pretty tight. It is very tight,
averaging just over one second per shot. Some
of those shots must flash by incredibly quickly.
They absolutely do. Some shots will feel rushed.
Occasionally, the AI might even skip a panel
entirely if the transition is too complex. Oh,
really? Yeah, but that is OK. This initial generation
is basically an animatic. It is a rough cut.
It shows you the overall pacing and flow. So
you watch this rough 15 second clip, what are
we looking for? You are checking for temporal
consistency. Do the warm orange tones of the
volcano ash stay consistent into the final gas
station scene? Does the camera pan smoothly?
If it feels too fast, or if a transition is jarring,
how do we fix it? We aren't in a traditional
editing timeline here. Flow has a feature called
the describe your edits box. It uses natural
language processing to adjust the timeline. You
literally just type smooth the transition between
each shot, or you type maintain consistent pacing
throughout the video. You just ask it nicely
to fix the edit. Exactly. The engine recalculates
the latent space between the frames. It generates
new transitional frames to smooth out the motion.
Wow. It adjusts the pacing without changing the
core visual assets you establish. That is incredible
control. You are directing the edit with text.
And because you did the hard work in stage one
and two. Because you built that perfect design
sheet. Right. The final motion clip maintains
its integrity. The characters look right. The
lighting matches. It feels intentional. The Claude
to chat GPT to flow pipeline is undeniably powerful.
But let's look at the bigger picture. Not everyone
uses those specific tools. Maybe they don't have
access. Maybe the subscription costs for three
different premium AI services are just too high.
That is a very valid concern. Generating images
and video at scale gets expensive quickly. The
beauty of this specific framework is its modularity.
The tools are completely swappable. Let's dig
into the tool built. What are the alternatives
for stage one, the prompt writing phase? If you
don't want to use Claude, Gemini, is a fantastic
alternative. Google's Gemini has a very capable
free tier. It handles large context windows beautifully,
which is great for building those skills. What
about Grok? Grok is another great option for
the text phase. It is incredibly fast. It also
has fewer safety restrictions, which can be helpful
if your story involves action or conflict that
other AIs might mistakenly flag as inappropriate.
What about stage two, generating the static images?
We need tools that excel at building consistent
design sheets. Ideogram is a phenomenal alternative
to chat GPT and Dale E3. Why ideogram specifically?
Two reasons. First, it is currently the best
in the market at rendering visible text accurately.
Oh, nice. If your scene requires a neon sign
or a newspaper headline, ideogram nails it. Second,
it has unique built -in tools for maintaining
strict character consistency across different
prompts. Any other image alternatives? Leonardo
AI. It has an amazing free tier. It gives you
an incredible amount of granular control. over
the artistic style. If you want a highly stylized,
painted look rather than photorealism, Leonardo
is brilliant. Now for the heavy hitter. Stage
three, the video generation. This is almost always
the most computationally expensive step. What
can we use instead of Google Flow and VO3? Kling
3 .0 is a massive contender right now. I have
seen a lot of clips from Kling online. This looks
very cinematic. It is. Kling 3 .0 handles physics
simulations remarkably well. Water splashing,
smoke billowing. It's often cheaper than enterprise
solutions, and the quality is stunning. What
else is out there for video? Pix4C1 is another
strong option. It is specifically optimized for
taking storyboard reference panels and translating
them into consistent motion. Good to know. And
if you are on a strict $0 budget, Hylua AI is
perfect for completely free experimentation.
So you have all these clips, but we still need
to put it all together. We need to add the music
and subtitles we avoided earlier. For final editing,
CapCut is the dominant choice for creators. Right.
It's free, incredibly intuitive, and there is
no watermark if you use the desktop version.
If you want Hollywood level control, DaVinci
Resolve offers professional color grading. It
is a massive complex program, but the base version
is entirely free. And obviously Adobe Premiere
if you are already in that ecosystem. But let
me ask you this. If we swap out the software,
if we use Gemini instead of Claude and Kling
instead of Flow, does the quality of this specific
sequence degrade? Does the magic disappear? Not
at all. The discipline of the sequence is what
creates the quality. It is absolutely not about
the specific brand of AI. It's the architecture
of the workflow. Precisely. The AI models will
change. A new tool will launch next week that
makes VO3 look old. But the logic of the pipeline
remains. Right. You must build the textual blueprint
first. You must lock in the static image second.
You only animate as the absolute final step.
The sequence is universal, even if the exact
software you decide to use changes. Two -sex
silence. That is the big takeaway here. Building
an AI video from scratch feels like magic. When
you watch a finished high -quality AI film, it
looks like a miracle of prompting, but it isn't
magical prompting at all. No, it's just a structured
process. It is about having a clear, methodical
sequence. You start with a simple story. You
let the text tool structure your prompts. You
build your static visuals to anchor the AI. Only
then do you hit the animate button. Each tool
handles one specific job. You isolate the variables.
You fix problems while they are still flat images.
Because fixing a moving target is nearly impossible.
Exactly. You become a director, carefully setting
up the shot. You stop being a gambler just pulling
the slot machine lever. It changes everything.
Yeah. I want to leave everyone with a final thought
to chew on today. We have been talking about
this specific AI video workflow. But think about
your own workflows outside of video creation.
Oh, it applies to almost everything. It really
does. Think about analytical business projects
or writing code or even designing a presentation.
This methodology building the design sheet first
is universal. How often do we rush to the final
moving product? We jump straight into the execution
phase. blindly because it feels productive, we
try to animate our ideas before we have actually
designed them. We skip the blueprint because
we want to see the house. Exactly. And then we
spend twice as long fixing structural errors
that never should have happened. Right. Next
time you start a complex new project, stop and
ask yourself, did I build my static design sheet
first or am I just hoping the sequence works
itself out? Thank you for joining The Deep Dive.
We will see you next time.