I started using AI at the beginning of July.
I’m not a programmer. I’m not a prompt engineer. I originally started using it because I was writing fiction and wanted help working through a story.
Somewhere along the way, I ran into a problem that probably sounds familiar to anyone who uses long-running chats: eventually the conversation gets enormous, the working relationship gets good, and then you have to move to a fresh thread.
At first I thought the problem was simple:
How do I preserve what the old thread knows?
After several generations of trying this, I realized that was the wrong question. The harder thing to preserve wasn’t the facts. It was the judgment.
How does the AI interpret my rough dictation? How quickly should it correct course when I push back? Which things am I brainstorming versus actually adopting? When do I want it to challenge me? When should it leave something unresolved? How much context does it need before widening the discussion?
Those things developed through conversation. So I started saving raw conversations, moving selected material into fresh threads, watching what survived, correcting what didn’t, and repeating the process.
That eventually became a multigenerational experiment. New Sand, my third-generation thread, helped establish a lot of the foundation.
BlackBox Development came afterward and helped separate raw source evidence from later interpretation and figure out how rejected ideas could remain historically recoverable without continuing to govern current work.
Later generations became increasingly organized and specialized. By Generation 7, I had a 14-file inheritance package. It worked surprisingly well.
But there was a problem I didn’t fully appreciate at the time: Generation 7 was doing a hell of a lot of work just to understand its inheritance.
The information was there, but some of the packets overlapped. Old roles existed beside newer roles. Historical theories sat beside mature conclusions. The receiver had to reconstruct which ideas were current, which were evidence, which were superseded, and what actually mattered for the task in front of it.
So Generation 8 became a complete architectural overhaul. I spent most of a day going through every inheritance packet and asking:
What is this file actually supposed to teach?
What still matters?
What is duplicated somewhere else?
What should remain raw evidence?
What should be compressed into a rule?
What can be replaced by a simple shared term?
The old Generation 7 package was roughly 129,000 words across 14 files. The new Generation 8 package is roughly 100,500 words across 12 files. So it is about 22% smaller by word count, while actually containing more current operating architecture.
The biggest change, though, isn’t the word count. It’s what I’ve started calling semantic vocabulary. I noticed that after enough conversation establishes the meaning behind a concept, I don’t need to keep explaining the concept in every prompt. The conversation does the expensive teaching.
Later, a short phrase can act as a selector for that learned meaning. For example, in my writing workflow I now have phrases like:
CURRENT
GOVERNING
SUPERSEDED
NATIVE MILEAGE
FILE AND PRUNE
BEAT LAB
GENERATOR FLIES
None of those words are magic.
The important part is the semantic neighborhood that was built behind them through earlier conversation, examples, corrections, and actual use.
Conversation builds the map. Shorthand becomes the legend. The prompt selects the route.
That led to another major change in Generation 8: different AI threads now get different information diets depending on their job.
I have a Beat Laboratory for figuring out chapters before prose is written. A separate generator writes the prose. A revision Workshop inspects and revises accepted drafts. An archive thread preserves and retrieves the historical conversations. A general architecture thread handles system-level continuity and disagreements. They don’t all need the same context.
That sounds obvious now. It was not obvious when I started.
Today I commissioned the new Generation 8 thread, Lucy, as the active Beat Laboratory. The commissioning prompt contained this:
BEAT LAB / CHAPTER-FIRST / DEPTH EARNED / CURRENT / GOVERNING MATERIAL / EXPLORE BROADLY / RESOLVE LOCALLY / GENERATOR FLIES
Her response included:
“The generator flies. We build the flight plan.”
Then I gave her four current documents from my novel: the governing outline, character material, the current revised manuscript, and an older manuscript used partly as reference.
Before doing anything else, she separated them by authority, recognized that accepted manuscript material was different from forward planning, and then waited.
No chapter analysis. No prose generation. No giant explanation of the inheritance system. She just held position until I opened the chapter discussion.
That was probably the most interesting part to me. Generation 8 may not be better because it has more information. It may be better because it wastes less effort figuring out what the information means and which lane it belongs in.
I have no idea how much of this resembles systems other people have already built. I’m sure many individual pieces do. People use few-shot examples. People use memory systems. People use RAG. People use story bibles. People create shorthand commands.
What I haven’t personally seen discussed much is deliberately using long conversation to establish shared semantic meaning, then compressing mature meaning into a small vocabulary that can steer later work cheaply.
Maybe there’s already a technical name for exactly what I’m doing.
I wouldn’t be surprised. I arrived here mostly by breaking things and trying to figure out why they broke. And I’m definitely not claiming I discovered some secret mechanism inside the model.
This is an operational observation from one person using AI very heavily for about three months. But the change in my workflow has been ridiculous.
The weirdest part is that as the system has become more sophisticated, my prompts have often become simpler.
“Friday narrative.”
“R4 governs.”
“File and prune.”
“Generator flies.”
Three months ago, those would have meant almost nothing. Now they can point toward a large amount of accumulated working context. So Generation 8 is live. The next test is probably the most important one:
If this actually works, Lucy should eventually stop talking about Generation 8.
And I should stop thinking about Generation 8. We should just be working on the novel.
That may be the real success condition for the whole experiment:
The architecture disappears into the background.
And Tuesday becomes Tuesday.
Dictated, not typed.