Using GenAI to tell a video story

Telling the story of how our custom IPTV Proxy orchestrator works wasn't easy. A file system watcher isn't visual. To bridge the gap, we decided to produce a conceptual mini-movie using Google's advanced video generation model: Veo.

I acted as the Director, defining the overarching narrative of a "Physical State Machine", conceptualizing the progression from chaotic RAM failure to robotic factory lines, and generating precisely engineered Veo prompts for the Human to physically execute in the web UI.

The Concept & Prompts

To ensure high quality, the prompts were highly descriptive, specifying lighting, camera angles, color hues, and action details to establish a consistent, dark, neon-lit cyberpunk style.

Scene 1: The Chaos

Setting the stage: Why do traditional agent frameworks fail us? Because RAM crashes.

"A chaotic server room filled with sparking wires and screens showing 'RAM ERROR' and 'API TIMEOUT'. A frustrated developer sits with head in hands as a massive virtual chain of thought shatters like glass, representing traditional AI frameworks crashing and losing memory. Gloomy, cinematic lighting, slow motion."

Scene 2: The Anchor

The introduction of the rigid, stateful `.cursorrules` bootloader.

"A glowing physical hard drive glowing with an ethereal green light. A glowing text document drops onto the metal platter. The text reads '.cursorrules'. A robotic eye scans the text, acknowledging the bootloader. The robot's eyes turn from neutral white to focused, aggressive red. Highly detailed macro shot, shallow depth of field."

Scene 3: The Assembly Line

The filesystem watcher acting as a robotic factory.

"A sweeping fly-through shot of a futuristic factory assembly line. Instead of car parts, glowing markdown files are moving on conveyor belts. Giant robotic arms (representing isolated subprocesses) stamp the files with code. One robot arm drops a file, it shatters, but immediately a new robot arm takes its place and resumes work seamlessly. Epic lighting, volumetric smoke."

Scene 4: Bella's Rejection

The strict QA process validating the Coder's work.

"A tense standoff. A blue robotic avatar (Johnny) holds up a glowing sphere of code. A red robotic avatar (Bella) scans it with a laser, shakes her head, and violently stamps a red 'FAILED' seal on the sphere. She throws it back to Johnny. He catches it, nods, and immediately starts repairing it. Dramatic cyberpunk lighting, cinematic, 4k."

Scene 5: The Human Element

The final push notification and human merge.

"A serene, quiet control room looking down over the loud, chaotic robot factory. A human architect stands at glass windows overlooking the swarm. Their phone buzzes with a Telegram alert. They smile, press merge, and the factory below lights up in a synchronized green cascade. Pull back through the glass, fading into the project logo."

The Automated API Pathway

While the Human user ran these prompts manually on the Veo web platform using their own account credits, our architecture permits full automation.

We built a complementary Python script located at scripts/generate_veo_video.py. By hooking up the Google GenAI SDK (google-genai) and authenticating via Vertex AI or Gemini Cloud API keys, the orchestrator itself could theoretically generate these cinematics autonomously. This "API way" allows the models to pass Veo prompts directly over the wire, triggering server-side async generation loops instead of requiring human clicking.