Prompt Engineering
Learn to write prompts that get you the exact image, video, or scene you imagined — on the first few tries, not the fiftieth.
Prompting is the single highest-leverage skill in generative AI: the same model produces a forgettable stock photo or a portfolio piece depending on the words you feed it. This path teaches the full craft — the anatomy of a great prompt, style and camera vocabulary, negative prompts, systematic iteration, and structured JSON prompting — with dozens of real before/after examples you can run in VAR2 right now.
Lessons in this path
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The Anatomy of a Great Prompt
The five-part formula behind every great AI image: subject, action, environment, style, and technical specs.
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Describing Subjects & Scenes Like a Pro
Specificity techniques that turn 'a dog in a park' into an image people stop scrolling for: instances, textures, counts, and layered scenes.
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Style & Aesthetic Language
Art movements, film stocks, render engines and illustration styles — the vocabulary that flips the entire look of an image with a single phrase.
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Camera, Lighting & Composition Language
Focal lengths, golden hour, rule of thirds, low-angle, bokeh, rim light — speak photographer and the model becomes your camera crew.
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Negative Prompts & Exclusions
How to tell a model what NOT to draw — and why writing 'no elephants' usually gets you an elephant.
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Iterating & Refining Systematically
Stop rerolling and start engineering: the one-variable rule, seed locking, and an iteration checklist that converges on your vision fast.
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Structured Prompts & JSON Prompting
When scenes get complex, prose collapses. Labeled sections and JSON prompts give every element its own unambiguous slot — especially for video.
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The Top Prompt Mistakes (and Their Fixes)
Overstuffing, contradictions, vague adjectives and ignored aspect ratios — the four failure modes behind 90% of disappointing generations.