While detailed prompts are useful, starting with simple, open-ended prompts can unlock more creative and strategic responses from AI models. Experimenting with different levels of prompt detail across various models often yields surprising and superior results.

Forget complex 'prompt engineering.' When a new AI model is released, find the official prompting guidelines from the creator. Feed this document into a chatbot like ChatGPT and have *it* construct the perfect prompt for you based on your reference image and goals, saving significant time and effort.

Avoid writing long, paragraph-style prompts from the start as they are difficult to troubleshoot. Instead, begin with a condensed, 'boiled down' prompt containing only core elements. This establishes a working baseline, making it easier to iterate and add details incrementally.

With models like Gemini 3, the key skill is shifting from crafting hyper-specific, constrained prompts to making ambitious, multi-faceted requests. Users trained on older models tend to pare down their asks, but the latest AIs are 'pent up with creative capability' and yield better results from bigger challenges.

Seedance V2's multi-input capability—combining images, videos, and audio—makes it function more like an advanced video editor than a simple text-to-video tool. This reframes its use case from pure creation to complex modification and composition, enabling tasks like character and background replacement within existing footage.

The quality and vision of an AI-generated video are determined more by the source reference images and videos than by the text prompt itself. Providing a strong visual reference gives the model a clear understanding of taste, style, and desired outcome, acting as a more powerful input than descriptive text alone.

While a multi-model approach—using the best AI for each specific task—is theoretically optimal, its practical implementation is difficult. A major roadblock is the need to create and maintain different optimized prompts for each model. This overhead leads users to default to a single, powerful model for simplicity.

When generating AI avatars, avoid generic emotional prompts like "the character is sad." To achieve more realistic and controllable results, describe the specific muscle movements, shifts in body language, and transitions in tone associated with that emotion. This gives the model concrete physical instructions, leading to more nuanced performances.

Genspark's 'auto prompt' function takes a simple user request and automatically rewrites it into more detailed, optimized prompts for different underlying image and video models. This bridges the gap between simple user intent and the complex commands required for high-quality generative AI output.