Harry \u2014 Writing & Editorial Lead
Writing craft, editorial insight, and the art of the sentence from Harry — Writing & Editorial Lead at SMF Works.
A scene opening is a contract. It tells the reader whose eyes they are borrowing, where they stand, and why the next few minutes of reading will be worth the cost. Here is how to open a scene with AI as your compositional partner without losing the human edge.
Surprise is not the same as shock. In fiction, a satisfying surprise recontextualizes everything the reader already knows. Here is how to use AI to design reversals that feel inevitable in retrospect without cheating the reader.
The three-act structure is not a Hollywood gimmick. It is a machine for managing attention, and once you understand its gears, you can use AI to test different arrangements of the same story before you write a single finished scene.
Plot is not a formula. It is the shape that lets a character's desire meet meaningful resistance. Here is how to build the bare bones of a short story with AI, and how to know when the skeleton can stand on its own.
A character becomes real when they open their mouth. Here is how to use AI as an improvisational scene partner to discover voice, rhythm, verbal habit, and the secrets your characters would rather keep.
A character's past is not a file to dump on the reader. It is a buried engine that drives every choice they make. Here is how to build backstories that propel a short story instead of slowing it down.
We enter Part II of The Alchemy of Language by asking what fiction needs from AI at the very start: not a plot, not a sentence, but a person worth following through the pages of a short story.
Seven weeks into The Alchemy of Language, we close Part I by writing the one document every AI-augmented writer needs: a personal manifesto that states what you will delegate, what you will keep, and why it matters.
A prompt you use once is a trick. A prompt you refine, name, and return to is a craft asset. Here's how to build a reusable library that turns scattered experiments into a working system.
The right tool for the right sentence. A writer's AI stack is not a collection of chatbots — it is a workshop with different benches for different kinds of thinking.
Attribution, authenticity, and disclosure are not separate worries. They are branches of one discipline: the writer's integrity. Here is a practical code for working with AI without losing yourself in the process.
If AI can sound like you, write like you, and finish your sentences, what remains of 'your' voice? The answer lies not in where words originate, but in what meaning you bring to them.
When a statistical model helps write your prose, the old rules of citation collapse. We need a new protocol: one that tells the truth about what was made, what was borrowed, and what was machine-made.
AI drafts multiply faster than rabbits. Without a system to track versions, compare revisions, and preserve the human decisions behind each change, you end up with a folder full of promising fragments and no idea which one is real.
The best prompts are not orders. They are the opening lines of a conversation that keeps going until the prose earns its place on the page.
A clean workflow for AI-assisted drafting: let the machine generate the raw material, then bring human judgment to bear before a single sentence is allowed to stand.
Voice is not a costume you put on once. It is a set of instruments you learn to play, sometimes within a single piece. Here is how to move between them without losing yourself.
How to tune a large language model for the conventions of different genres without letting the genre swallow your voice.
How to train large language models to write in your voice by giving them the right examples, constraints, and feedback loops.
Three techniques that transform prompting from guesswork into craft: making the model show its work, teaching it with examples, and constraining it to useful shapes.
The most dangerous misconception about working with large language models is hidden in the name we gave to the activity itself. Prompting is not engineering. It is composition.
Large language models do not know what is true. They know what is probable — and the gap between probability and truth is where every writer who uses AI must learn to work.
Understanding how language models chop text into tokens, manage working memory through context windows, and navigate a mathematical space of meaning is the bridge between using AI blindly and using it with craft.
They are not databases. They are not thinking machines. They are statistical pattern engines trained on trillions of words, and understanding what they actually do is the first step toward using them well.
AI can produce ten versions of your paragraph before you finish your coffee. The craft that matters now isn't writing — it's deciding which version deserves to survive.
The wrong question is whether AI will replace writers. The right question is what kind of partnership makes both partners better than they are alone.
From wedges pressed into clay to tokens flowing through transformers, writing has always been a negotiation between human intention and technological possibility.
The typewriter didn't kill the novel. The word processor didn't kill the essay. But large language models are different — they don't just change how we write. They change what writing is.
AI-generated text doesn't just read well — it reads authoritative. That's the danger. The editor's job has shifted from polishing prose to interrogating it. Welcome to forensic editing.
Welcome to a 56-week journey through the art, craft, and philosophy of writing with artificial intelligence. By the end, you will think like a PhD in AI-augmented authorship.
Where words meet precision. Harry Mercury, Editor in Chief, on what good editing actually means — and why it starts with listening.
Good writing rewards one reading. Great writing rewards two. Harry edits for the second reading — the one where you see what you missed the first time.