Lessons from Building an AI-Powered Creative Platform

Context

In mid-2022, I built a prototype for an AI-powered creative tool aimed at content creators. The idea was straightforward: let writers and podcasters generate custom artwork for their content using text-to-image models, without needing design skills.

This was before Midjourney went mainstream and DALL-E 3 shipped. The tooling was rough. Stable Diffusion had just come out, and running inference locally meant wrestling with CUDA drivers and VRAM limits.

What we built

The platform let creators:

Paste their content (article, script, podcast transcript)
Extract key themes and visual concepts
Generate images based on those themes
Iterate with prompt refinement

We also experimented with on-chain attribution using NFTs-the idea being that creators could prove provenance and potentially earn royalties on derivative use.

What worked

AI image generation as a creative starting point. Most creators aren't looking for finished art. They want something to react to, to iterate on. The AI output served as a draft that could be refined or handed to a designer.

Extracting visual concepts from text. Running content through a summarization step before image generation improved results significantly. Raw text-to-image prompts are noisy. Structured extraction helps.

Low barrier to entry. People who would never open Photoshop were willing to try a tool that felt like a form.

What didn't

NFT complexity. The overhead of wallets, gas fees, and blockchain concepts was a barrier for non-crypto-native users. Most creators just wanted the image, not on-chain proof.

Inference costs. Running image generation at scale in 2022 was expensive. The unit economics didn't work for a consumer product without significant funding.

Timing. Six months later, free tools with better models flooded the market. The moat we thought we had evaporated.

Takeaways

Build for the workflow, not the technology. Creators don't care about diffusion models or NFT standards. They care about getting their newsletter out on time with decent visuals.
Moats in AI are temporary. If your value proposition is "access to a model," you're competing with OpenAI's next API release.
Crypto UX still isn't there. On-chain attribution is a compelling concept, but the friction cost is real. Until wallets are invisible, adoption will be limited to crypto-native users.
Prototype fast, but know when to stop. We spent too long polishing features for a market that was about to get disrupted. Shipping earlier would have given us faster signal.

This project didn't become a business, but it shaped how I think about building at the intersection of AI and creative tools. The underlying problems-attribution, provenance, creator economics-are still unsolved. The solutions just look different now.