How AI Helped Kateryna Automate the Technical and Own the Creative

My name is Kateryna and I am a visual designer and AI artist at ELVTR, an Edtech company that bridges the gap between traditional education and real professional demands. I have been working as a designer for six years, but my responsibilities have grown well beyond graphic design.

Before design, I worked as a senior GIS specialist creating and navigating maps for clients, which is about as far from visual art as it gets, but I always knew design was where I wanted to be. I also run a personal project focused on anti-consumerism through marginal pixelated graphics. You can find my professional work on my LinkedIn page and website, and my personal project on the website and on Instagram.

A large part of my role involves creating visuals for social media and marketing materials, and almost all of those are now generated using AI tools. My top tool for hyper-realistic visuals is Nanobanana, which I use for static shots with precise styling.

But the most interesting recent work has been AI video content, where I built a bot that writes prompts to generate seed images and comedy text, which are then animated using tools like Kling or Veo. The whole structure is layered: prompts feed visual bots, visual outputs feed animation tools, and the result is a finished reel. It is a multi-stage pipeline, and it is genuinely fun to build.

One of my favourite recent projects was a series of comedy reels to promote ELVTR's courses. The brief was to make something funny and visually distinctive. I started with the concept and styling direction, built a bot that generated the prompt library, used Nanobanana to create the static frames, and then animated everything using AI video tools.

The layered cake structure of it, where each stage feeds the next automatically, meant I could produce a high volume of polished content in a fraction of the time it would have taken manually. The human input was the idea, the cultural references, and the aesthetic decisions. The technical production was largely automated. That is the balance I aim for in all my work.

I learned entirely on my own through guides, tutorials, and social media tips. It was chaotic at first, jumping between random resources, but working on real tasks at the same time is what actually made it stick. Over time, I tested and refined my process until I had a reliable workflow: start with the concept and reference set, use Nanobanana for static visuals, move to Kling or Veo for animation, add ElevenLabs for voiceover if needed, then combine everything into the final output.

I also built my own prompt library using prompt engineering so that when I need a quick output in a familiar style, the groundwork is already done. Once the workflow is tested and the prompts are saved, an hour of work produces a finished result. That efficiency only comes from having done the hard setup work first.

The biggest misconception I had, and that almost everyone has, is that a well-written prompt will produce exactly what you imagined on the first try. It will not. Prompt engineering takes real time to learn, and getting close to your desired output requires iteration, negative prompts, and a willingness to run the same idea ten different ways before it clicks.

If I were starting again from zero, I would take a structured course first to make the initial learning more systematic rather than piecing it together from scattered tutorials. The chaotic route worked for me, but a clearer starting framework would have saved time.

The creative direction is always entirely mine. I come in with an idea, a set of cultural or aesthetic references, and a clear sense of what I want the output to feel like. AI handles the technical production: generating the frames, animating the movement, processing the voiceover, but it has no access to the imagination or the cultural context behind any of it.

I also work as an illustrator, so for my personal project, I create my own original graphics and then use AI tools to animate them. That means even the source material is mine. The tools accelerate and expand what is possible, but the creative input that makes the work distinctive comes from me.

Mockups are a good example. Choosing the right mockup that fits a brand's visual identity used to mean spending significant time searching specialist sites or creating it manually from scratch. Both are slow.

Now I generate hyper-realistic mockups using AI tools, which means the mockup can be exactly what the concept needs rather than the closest available option from a stock library. The same applies across the production side of design work. Tasks that used to take hours of manual effort now happen in minutes, which frees up the actual design thinking time that the job is really about.

My personal project is a one-woman show with no deadlines, no copywriters, no team. It centres on marginal pixelated graphics with an anti-consumeristic philosophy, inspired visually by artists like Invader. I create original digital illustrations and print them on second-hand textiles only, never ordering new production runs.

Because my professional workflow is so well automated, I have mental and practical capacity left over for personal creative work that operates entirely outside commercial pressures. I post when I have time, roughly two pieces a month, and I am transparent with my audience that this is a personal initiative that runs on my own terms. You can find the project on Instagram and through my personal website linked from my LinkedIn.

Start now. Not because it is easy, but because starting now means you will accumulate a genuine timeline of how these tools have developed, and that history becomes a form of expertise that people who arrive later simply cannot have. I started paying attention to AI tools two years ago and actively using them a year and a half ago, and that progression is already something I can point to as real experience.

For women who feel their current career is too far from AI to make a connection, the tools themselves can help. Build a simple AI assistant in ChatGPT or Gemini, be completely honest with it about what you do now and what you want to move toward, feed it examples and tutorials relevant to your interests, and ask it to build a realistic transition plan. It is the modern version of a five-year strategy, and it works.

The approach I would use is to treat an AI assistant as a thinking partner for the strategy itself. Most people underuse these tools for planning because they give vague inputs and get vague outputs in return.

If you are specific about your current skills, your target field, your available time, and the kind of transition you want, whether gradual or complete, the output becomes genuinely actionable. Attach tutorials, examples, job descriptions, anything concrete that represents where you want to go. Ask for a phased learning plan with milestones. The more honest and detailed the input, the more useful the plan.

This is not a shortcut; it is a way of making the thinking that used to happen in a coach's office accessible to anyone with a browser.