I Built a Platform Instead of Finishing My Book

I wanted to write a novel. I ended up building a platform instead. And I couldn't be happier.

It Started With a Python Script

If you read The Drakenhart Experiment, you know the backstory. I wanted to tell a story through a series of short form videos shared on social media. AI generated video, while absolutely amazing right now, still has a real consistency problem when trying to create the same characters over hundreds of short videos. I didn't want to reduce the quality of output just to fit the current industry's video capability, so I pivoted to telling my story through the written word instead, and started telling my story through a series of 5 fully written novels.

Over a month of struggling with AI to have it generate adequate prose, I ended up building a multi-tier system in Python to keep AI-assisted chapters coherent across a full novel. At its center was what I started calling the ChapterSpec - an AI targeted specification that allows it to know how to write my story without telling it what to write.

It worked. Really well. The prose being generated around my story was really engaging and fun to read. It was at this point I began to realize that the spec-driven prose concept that was working for me, is actually fairly new. I couldn't find anyone else out there doing it in a similar way.

That's when I decided to share my tools with more people.

But... python doesn't share. It doesn't scale. You can't hand someone a terminal or a bunch of files and say "here, write your first book."

I had something I genuinely believed exceeded what the current tools in this space were offering. And zero other people could actually use it.

That bothered me more than I expected.

The process itself — going from blank concept to actual prose worth reading — that's the part that's fun. That's the part that shouldn't require a software engineering degree to access.

So I decided to build a platform.

I Didn't Write a Line of Code

I'm a Principal Software Engineer with over thirty years experience. When I have something to build, my instinct is to open an editor and start writing code. However, what I had in mind would have taken me, by myself, over a year to build. So before I started, I made a deliberate decision: don't touch a single line of code unless there is literally no other way.

I vibe coded the entire Novelmint platform from day one.

This was my first real attempt to build a finished, production-ready app strictly through vibe coding. No scaffolding sessions. No "just this one thing." If I couldn't get there by describing it to an AI, I had to find a different angle.

I am a solid AI convert now. The experience was phenomenal.

What surprised me wasn't that it could generate code. I expected that. What surprised me was the discipline it forced. Not writing code yourself means being precise about what you actually want. That precision made the product better. I could focus entirely on the idea itself, refine it, challenge it, test it, and build it through words alone.

What Was Actually Hard

The vibe coding wasn't the hard part.

Learning roughly a dozen third-party systems was.

ElevenLabs, Stripe Connect, various automation tools, hosting, security audits, LLM APIs, storage, caching, etc. All of these I knew quite a bit about through my day job, but each tool had its own way of doing things that I had to learn and adapt to. Each integration required understanding not just the API, but the assumptions baked into it.

And in a vibe-coded solution, a lot of manual steps still remain — I found that out the hard way.

That's the part AI doesn't abstract away. I still had to understand the systems I was connecting.

Thirty years of engineering instinct helped here, even when I wasn't writing the code.

Why I Thought the Community Side Was Solvable

From 2018 to 2022 I ran a social platform for independent artists called Blackett Music. At its peak the site had ~4,000 members, ~2,000 artists, ~1,000 songs. I took two accounts on social media platforms from 0 to 50k followers over about a year and a half. I understood what was needed on the social front to build a community.

Sadly the business didn't survive the Twitter to X conversion, but it taught me one valuable thing I've held onto: build a good enough system, and you can build a community around it.

Most people see the marketplace problem — readers and authors, chicken and egg — and stop there. That history didn't stop me. It actually got me started. I'd done the community side before. I knew it was solvable if the product underneath it was worth building around.

This product is worth building a community around.

Where It Landed

Novelmint is live at novelmint.ai.

Studio is the author pipeline: sequence draft → review → prose → editorial → publish → promote. The spec system that started as Python scripts on my laptop is now a feature called ChapterSpec — a structured blueprint built before a word of prose is written. Authors steer at every stage. IP stays with the author. Always.

Commons is the reader marketplace. $0.05 per chapter. 70$1.05. Typical production cost for an author: ~$63. Break-even: 90 readers.

High fidelity audio narration. 15-language support. Author reliability scores. Reader feedback that feeds directly back into the next chapter.

One thing that makes Novelmint stand out is how it improves the quality of the reading or listening experience by using the ChapterSpec as a baseline for everything it produces. It produces more authentic output because it knows the intent behind what it is supposed to produce.

The catalog is small right now. That changes as authors publish. It's a growth curve.

I built this because I had something worth sharing and no good way to share it.

That is still the whole reason.

Novelmint is a TeamLesh LLC product — novelmint.ai