printf “20 text/gemini\r\n” printf “my bashblog posts\r\n” user=$(stat -c ‘%U’ $0) for post in $(ls -t /home/$user/public_gemini/blog/*.md); do post=$(basename $post) printf “=> /~$user/blog/$post $post\r\n” done
The workflow from having an idea to creating a finished publication has traditionally been dauntingly technical and complicated. This complexity has largely relegated book publishing to being a commercial-scale activity undertaken by publishers with specialized expertise and equipment. However, by using AI tools now widely available even to hobbyists, the entire publishing process can be simplified and democratized. As an individual maker and small business owner who has trained myself in most stages of book production, I have found the workflow remains complex but doable—and recent AI capabilities are tipping the balance toward empowering solo creators.
Specifically, I believe well-written and edited printed books can now be produced even at home or in a small office. And with the aid of AI as an expert mentor, tutor and troubleshooter, individual makers can readily navigate technical obstacles that previously erected barriers to entry. AI is unlocking creative potential by making the publishing process more accessible.
Take cover design, one of the most challenging aspects of production. Even makers with no visual imagination can now utilize AI image generation to craft book covers. Simply describe the desired scene, aesthetic and purpose to a text-to-image AI tool using natural language. For example, I prompted an AI as follows to create a soft, atmospheric cover that would print well on plain paper:
“Layered digital art brown blue tan green soft edges and subtle gradients, of the Tsing Ma Bridge, cirrus. The style is atmospheric, soft, and dreamlike. Create the image with high resolution and no hard edges, to be inkjet printed twice without any noticeable alignment problems. Detailed yet soft.”
I intentionally avoided bright colors that would disappoint when printed on standard office paper. This also conceals slight misalignment from double-printing conceals the low-resolution output. This prompt allowed an AI to circumvent limitations of my basic home printing setup and yield a presentable cover.
I then imported the AI-generated image into the free vector editing tool Inkscape and added typography to complete the cover. This leverages the respective strengths of textual prompt-based image generation and vector graphics software. The AI handles the creative ideation and atmospheric scene design that I struggle with, while Inkscape gives me control over typography and layout.
The cover is traditionally one of the most labor-intensive and skill-dependent aspects of production. But constructing prompts for AI image generation democratizes access to custom cover art. If you can describe what you want in text, you can get beautifully rendered artwork catered to your publishing needs.
Editing is another barrier for indie publishing. Even competent writers produce typos and other errors. And developmental editing to refine the substance of a manuscript requires experience beyond basic literacy. Again AI can assist: editing tools like Grammarly, ProWritingAid and Hemingway identify issues in grammar, style and readability. They act as an expert proofreader accessible to anyone.
AI writing assistants take this further by providing feedback on overall structure, flow and clarity when supplied with an outline or draft. Their computational linguistic models can suggest improvements tailored to your genre and goals. Of course, AI tools have limitations—human editors still reign supreme for developmental editing. But AI gives unpublished writers feedback difficult to obtain otherwise.
Between AI image generation and text improvements, prompts are key to unlocking AI’s potential for simplifying publishing. Crafting effective prompts leveraging the capabilities of each tool remains challenging. But the same AI that assists with editing and artwork can also help optimize prompts themselves. I have found text-to-text models like Claude useful for composing prompts for image generation—I simply describe what I want the prompt to contain. AI can even suggest prompts personalized for each creator’s style and subject matter, as more training data accumulates.
So while learning to use multiple AI tools effectively involves a learning curve, the same technology provides guidance for smoothing this curve through auto-generated examples and feedback. With each iteration of the publishing process, from drafting to editing to cover design, AI offers users an expert tutor. The knowledge and skills required to self-publish from home are being embedded into widely accessible smart tools.
These recent leaps forward in AI simplify book publishing by programmatically encoding skills once monopolized by industry experts. The sheer computational power of models trained on massive datasets unlocks creative potential for makers lacking technical knowledge or commercial infrastructure. If you can articulate your vision, AI can help realize it—lowering barriers to authoring professional-grade books as an indie creator. While challenges remain compared to commercial publishing, AI tipped the balance to make self-publishing viable for motivated individuals. By continuing to leverage AI as a mentor and multiplier, the realm of possible publishing projects will expand for independent artists, crafters, and creators of all kinds.