We built MemeFX AI to close that gap. This post isn't a launch announcement. It's a write-up of what we learned turning "I want to be in that meme" into a product, including the parts that didn't go the way we expected.

The idea: remove the prompt

The first version of the idea was the obvious one: a text box. Describe the video you want, and the model makes it.

We dropped it quickly. When people want to join a trend, they already know exactly what they want. They want that trend, with that song, with themselves in it. Asking them to write a prompt that rebuilds a meme they've already seen a hundred times is friction with no payoff. Prompting is a skill, and most people scrolling a feed don't want to practice it.

So the core product decision was: no prompt at all. The trend is the prompt.

The user flow

The whole flow fits in three steps:

1. Pick a trend template. Each template captures a specific meme format: its moves and its song.
2. Upload 1–3 of your own photos. That's the only input.
3. Get an MP4 that follows the trend with its song, sized for TikTok, Reels and Shorts.

It sounds almost too simple, and most of the work went into keeping it that way. Every option we considered adding (style sliders, length controls, advanced settings) was weighed against one question: does this help someone post their meme faster? Usually the answer was no.

Product notes (kept generic, on purpose)

A few things that turned out to matter more than we expected:

Templates are the product, not a feature. In a prompt-based tool the model is the product. In a template-based tool, the catalog is. A template has to be recognizable instantly, and the song is a big part of that recognition. Most of our product thinking ended up being about curation, not generation.

Trends have a shelf life. A meme format can peak and fade in a couple of weeks. That changes how you plan work: being quick to add a template matters more than polishing it forever. A template that ships late is a template nobody uses.

Generation can fail, so treat failure as part of the UX. AI video generation isn't deterministic, and some inputs just don't work well, like a blurry photo or an odd crop. Telling users clearly what makes a good photo and handling a failed render gracefully earns more trust than a slightly better best case.

Own photos only. The input is meant to be your photos, so you're the one in your meme. Being clear about that up front in the product and its copy matters for a tool that puts real people into videos.

Output should be ready to post. The last mile matters. If someone has to re-encode, crop or re-add audio before posting, the "no prompt, no effort" promise breaks. A plain MP4 in a short-form-friendly format turned out to be the right answer.

Lessons

• Start from the user's intent, not the model's capability. The model can do lots of things. The user wants one specific thing. Building around that one thing made the product much easier to explain.
• Constraints are a feature. "Pick a template, add photos" is easier to understand than any number of settings. Fewer choices made it faster to go from opening the site to having a video.
• Pricing is UX too. For a tool people use in bursts when a trend hits, not every day, how they pay shapes whether they try it at all. We kept that in mind when designing how people pay.
• Ship, watch, adjust. Trends move faster than roadmaps. Short feedback loops beat long plans.

Try it

If you want to see how the flow works in practice, MemeFX AI is live here: memefxai.com

We'd love feedback from other builders, especially if you've worked on template-driven or no-prompt AI tools. What did you cut to keep things simple? Let us know in the comments.