Generation, editing, and consistency — what's genuinely usable right now and what still needs a human finishing pass.
Understanding the diffusion process behind most AI image tools explains a lot about why prompts behave the way they do.
For a current example or reference point in visual production, Pexels provides additional context.
The specific, well-known weaknesses in AI image generation share a common underlying cause worth understanding directly.
AI video generation is genuinely capable and genuinely earlier-stage than AI image generation. Calibrating expectations to that gap matters.
The same discussion also raises questions about transparency and workplace data; the complete article provides related context for evaluating those trade-offs.
Brand consistency is one of AI image generation's harder problems by default. A few specific techniques close most of the gap.
AI design tools genuinely lower the floor for non-designers. They don't raise the ceiling nearly as much, and confusing the two produces real disappointment.
Legal questions around AI-generated images remain genuinely unsettled in several jurisdictions. This is a general orientation, not legal advice.
Full-image generation gets most of the attention. Targeted editing tools are where a lot of the practical, everyday value actually lives.
The choice between stock photos and AI-generated images isn't a simple upgrade in either direction. Each has a specific, different set of trade-offs.
How you frame AI-generated work to a client shapes their expectations more than the work itself does. A few specific habits keep that framing honest.