I built this because I was frustrated with the current state of AI image generation. I found myself spending hours re-rolling prompts just to get the text spelled correctly or to fix a layout that looked "slightly off." The issue is that diffusion models generate pixels, which makes them inherently probabilistic—if you ask to change a text the whole image is regenerated.
LayoutCraft takes a different approach. Instead of guessing pixels, I built a rendering pipeline that uses LLMs to write HTML and CSS, which is then rendered via Playwright. This makes the output deterministic. It means the text is actual DOM text (always crisp), the layouts respect specific hex codes for brand consistency, and you can resize the same design state to different aspect ratios instantly without artifacts.
It’s definitely not for generating "art" or photorealistic scenes, but for structured marketing assets where layout consistency matters, I found this workflow much more reliable. I’d love to hear your feedback on the approach!
You've perfectly articulated the gap in the market. The solution isn't just a better image generator. I built a tool called LayoutCraft to solve this exact problem. It focuses entirely on creating a great layout with good font choices automatically. It uses AI to understand the request, but then applies a structured, programmatic 'blueprint' to build the layout. This is how it handles fonts and spacing properly, resulting in a clean design, not a chaotic image.
Interesting framing around error cost. The piece that seems missing is accountability. A core function of a CEO is to be the single person ultimately responsible for a decision. If an engineer ships a bug, their manager is accountable. If an LLM hallucinates a disastrous market strategy, who gets fired? You'd still need a human to formally accept the risk, making the LLM more of an advisor.
In theory - CEO's have ultimate responsibility. In practice it's more complex - boards, delegation, company structures, hr etc etc remove a lot of ultimate responsibility from CEO's. The buck stop's here, unless, the CEO's decides otherwise. Carlos Tavares is a good example of this. Got away with more screwups than many senior employee's could dream of. Ditto lots of legacy autos. The board / shareholders typically have a lot of sway and delegated accountability / responsibility.
Agree with your point of distribution of responsibility and accountability. My argument was more about bosses vs engineers not particularly about CEO's. You can't let llms take decisions and blame them later if it backfires.It has to be humans to take those high impact decisions and be accountable for the results.
I built this because I was frustrated with the current state of AI image generation. I found myself spending hours re-rolling prompts just to get the text spelled correctly or to fix a layout that looked "slightly off." The issue is that diffusion models generate pixels, which makes them inherently probabilistic—if you ask to change a text the whole image is regenerated.
LayoutCraft takes a different approach. Instead of guessing pixels, I built a rendering pipeline that uses LLMs to write HTML and CSS, which is then rendered via Playwright. This makes the output deterministic. It means the text is actual DOM text (always crisp), the layouts respect specific hex codes for brand consistency, and you can resize the same design state to different aspect ratios instantly without artifacts.
It’s definitely not for generating "art" or photorealistic scenes, but for structured marketing assets where layout consistency matters, I found this workflow much more reliable. I’d love to hear your feedback on the approach!