The Hard Part of AI Image Creation Is Choosing What to Try Next
TL;DR: The first image is only the start. Once a result is close, the real work is deciding what to adjust—and which model or workflow is right for that change. I’m building Image 2 around the idea that image tools should make that next decision easier.
The First Result Changes the Question
A prompt can get you to a useful starting point quickly.
Then you look closer. The composition works, but the product needs to stay more consistent. The headline is almost right. Maybe the image needs to become a poster, an ad, or a different aspect ratio.
The question is no longer just, “What should I generate?”
It becomes, “What should I try next?”
That small shift can send you into a loop: revise the prompt, switch models, upload the reference again, compare the results, and try to remember which setting produced the version you liked.
Model Choice Is Part of the Creative Decision
Different image tasks call for different strengths.
A broad prompt-led concept may need a different starting point from a reference-heavy edit. An information-dense poster has different demands again: layout, text, and instruction-following all matter.
When every model lives behind a separate workflow, choosing one can feel like a commitment. You have to move your prompt and references before you know whether that model is a better fit.
I’ve been thinking about how to make that choice easier. Image 2 brings multiple image models and prompt-based and reference-based workflows into one place, so creators can choose a starting point and refine from there. Its current workflow includes GPT Images 2.0, Nano Banana 2, and Seedream 5 Lite, with different use cases for general generation, reference editing, and structured visuals.
The goal isn’t to claim there is one best model. It’s to help people spend less time guessing where to begin.
A More Useful Way to Iterate
A simple workflow can make image generation feel less like trial and error:
- Decide what the image needs to do. Is it a product visual, an ad, a poster, or an illustration?
- List what must stay consistent. Include the subject, product details, required text, and any reference images.
- Choose a model based on the task. Treat it as a starting point, not a promise that the first output will be final.
- Change one thing at a time. Adjust the prompt, reference, or output settings, then compare.
- Review the result yourself. Check important details and rights before using it publicly.
The last step matters. AI can help you get to a visible draft faster, but it doesn’t take responsibility for whether the image is accurate, appropriate, or ready to publish.
The Product Lesson
It’s easy to describe an image tool by listing models, settings, and output options. But for the creator, the experience is often defined by how many decisions they have to repeat before an image is usable.
A good interface should make the next step clearer. Sometimes that means showing which workflow fits the task. Sometimes it means making it easy to compare another model without rebuilding the whole brief.
That’s the problem I’m exploring with Image 2: helping creators move from “almost” to a result they can actually use.
For other indie hackers building creative tools: what decision causes users to stall after they get their first promising result?
Image 2: https://imagev2.org/
Have early users shown that model choice is actually where they stall, or does the bigger drop-off happen after a promising image when they have to decide what to change next?