I wasted a week trying to generate a photorealistic image of a squirrel eating a nut. A whole week. 500 hours sounds like a lot of time, and it is. I dove headfirst into the world of synthetic media, and I’m here to tell you that most of what you read online is wrong. It’s either written by people who have never actually built anything with this tech, or by AI-powered content farms that just rehash the same generic advice.
This is not one of those articles. I’m Sahin Boydas, and I’ve built and sold two companies, and invested in over 200 more, including some of the biggest names in AI like Anthropic and OpenAI. When a new technology comes along, I don’t just read about it. I get my hands dirty. I spent the last few months doing just that with synthetic media. I’ve generated thousands of images, created videos, and even trained my own models. And I’ve made a lot of mistakes.
This article is about the five most important lessons I learned. The things I wish I knew before I started. This is the stuff that will actually help you get professional results and save you from wasting your time like I did with that squirrel.
Lesson 1: Your Prompt is a Suggestion, Not a Command
This was the hardest pill for me to swallow. I'm a programmer. I'm used to giving a computer a command and having it execute it perfectly. If I tell a database to SELECT * FROM users WHERE id = 1, I know exactly what I'm going to get back. That's not how AI works. Not even close.
Your prompt is not a command. It's a suggestion. It's the start of a conversation. You're not telling the AI what to do, you're guiding it. You're whispering in its ear. And sometimes, it completely ignores you.
I learned this the hard way trying to generate a hero image for a landing page. I needed a shot of a diverse team of engineers collaborating around a futuristic interface. I wrote a prompt that was a paragraph long, specifying everything from the lighting to the ethnic makeup of the team. The result? A cartoonish image of three white guys in lab coats looking at a blue screen. It was comical how far off it was.
I spent hours refining that prompt. I tried different phrasings, added negative prompts, and even tried to specify the camera angles. Nothing worked. I was about to give up when I tried something different. I deleted the entire prompt and wrote: "A team of engineers building the future. Cinematic, photorealistic." The result was almost perfect. It wasn't exactly what I had in my head, but it was better. It was more creative, more dynamic, and more interesting.
That's when it clicked. The AI is not a tool for executing your vision with perfect fidelity. It's a creative partner. You have to give it room to breathe. You have to let it surprise you. The best results come from a back-and-forth process of prompting, generating, and refining. It's more like art direction than programming.
Lesson 2: The Model is Everything
There are a million and one AI image generation tools out there. Midjourney, Stable Diffusion, DALL-E 3, and a new one popping up every week. It's easy to get overwhelmed. It's also easy to assume that they're all basically the same. They're not. Not even close.
The model you use is the single most important factor in determining the quality of your output. Each model has its own unique style, its own strengths, and its own weaknesses. Some are better at photorealism, others are better at artistic styles. Some are great at generating faces, others are terrible at it.
I learned this when I was trying to create a set of avatars for a new project. I needed a consistent style, but with a diverse range of characters. I started with a popular free tool, and the results were just awful. The faces were distorted, the hands were mangled, and the style was all over the place. I was about to hire an illustrator, which would have cost me thousands of dollars.
Then, on a whim, I tried a different model. It was a paid tool, but it was worth every penny. The results were stunning. The faces were perfect, the hands were realistic, and the style was exactly what I was looking for. I was able to generate the entire set of avatars in a few hours, for a fraction of the cost of hiring an illustrator.
Don't be afraid to experiment with different models. Don't just stick with the first one you try. And don't be afraid to pay for a good one. The difference in quality is night and day. It's the difference between a professional result and an amateur one.
Lesson 3: Post-Processing is Not a Dirty Word
There's a weird purity culture in the AI art community. A lot of people believe that the image should be perfect straight out of the generator. That any post-processing is cheating. That's just silly. And it's holding you back.
I'm here to tell you that post-processing is not a dirty word. It's a necessary part of the creative process. Even the best AI-generated images can be improved with a little bit of tweaking. A color correction here, a sharpness adjustment there. It can make a world of difference.
I learned this when I was creating a series of images for a blog post. I had a set of images that were good, but not great. They were a little flat, a little dull. I was about to settle for them, but then I decided to try something. I opened them up in Photoshop and started playing around. I adjusted the levels, boosted the saturation, and added a little bit of contrast. The difference was incredible. The images went from good to great. They popped off the page.
Don't be afraid to use Photoshop, or GIMP, or whatever your favorite image editor is. Don't be afraid to crop, to color correct, to sharpen. It's not cheating. It's part of the process. It's how you take a good image and make it great.
Lesson 4: The Uncanny Valley is Real, and It Will Haunt Your Dreams
The uncanny valley is a term used to describe the feeling of unease or revulsion that people experience when they see a robot or an animation that is almost, but not quite, human. It's a very real phenomenon, and it's something you'll have to contend with when you're generating images of people.
I've seen some truly terrifying things come out of AI image generators. Faces that are just slightly asymmetrical. Eyes that are just a little too far apart. Skin that's just a little too smooth. It's the stuff of nightmares. And it's the quickest way to make your project look unprofessional.
I learned this the hard way when I was creating a set of images for a marketing campaign. I needed a series of photos of happy, smiling customers. I thought it would be easy. I was wrong. The first few batches of images were just… off. The smiles were a little too wide, the eyes were a little too dead. They looked like something out of a horror movie.
I was about to give up and hire a photographer, which would have been a huge expense. But then I discovered a few tricks. I learned that it's easier to generate realistic faces if you use a reference image. I learned that it's better to generate a variety of faces and then pick the best ones. And I learned that sometimes, it's better to go for a more stylized look, rather than trying to achieve perfect photorealism.
Don't underestimate the uncanny valley. It's a real and persistent problem. But with a little bit of patience and a few tricks, you can learn to avoid it. And your audience will thank you for it.
Lesson 5: It's a Marathon, Not a Sprint
This is probably the most important lesson of all. Learning to use AI image generators is not something you can do overnight. It takes time. It takes practice. It takes a lot of trial and error. It's a marathon, not a sprint.
I've spent over 500 hours on this, and I'm still learning new things every day. I'm constantly experimenting with new models, new prompts, and new techniques. And I'm still making mistakes. But I'm also getting better. My images are getting more realistic, my videos are getting more polished, and my workflow is getting more efficient.
Don't get discouraged if you don't get amazing results right away. Don't give up if you can't generate the perfect image on your first try. Just keep practicing. Keep experimenting. And most importantly, keep learning.
The world of synthetic media is moving at a breakneck pace. There are new tools and new techniques emerging every week. The only way to keep up is to be a lifelong learner. To be constantly curious, constantly experimenting, and constantly pushing the boundaries of what's possible.
So, that's it. Those are the five most important lessons I learned after spending 500 hours on synthetic media. I hope they'll help you on your own journey. And I hope they'll save you from wasting a week trying to generate a photorealistic image of a squirrel eating a nut.
Frequently Asked Questions
How were these items selected?
Each item on this list comes from direct experience, either from building my own companies or from patterns I've observed across the 200+ startups I've invested in. I prioritize practical, actionable items over theoretical concepts.
Can I implement all of these at once?
I'd strongly recommend against it. Pick the 2-3 items that resonate most with your current situation and focus there. Trying to do everything simultaneously is a recipe for doing nothing well.
Are these recommendations still relevant in 2026?
Absolutely. While specific tools and tactics change, the underlying principles remain consistent. I update my thinking regularly based on what I'm seeing in the market and across my portfolio companies.
How do I know which items apply to my situation?
Start by honestly assessing where your biggest bottleneck is right now. The items that address that specific constraint will give you the highest return on your time and energy.