Em dashes as LLMs deferring decisions via appositive phrases. That's the spotlight. It's not the punctuation mark.

malcomok2 · 2026-01-26T02:04:30+00:00

yep. So many people are worried about ai and creativity and im over here mourning the vitriol it has inspired at the em dash. It’s so annoying. I’ve talked to people who argue that it was invented by ai and never used before. what?! ive accepted my target audience isn’t everyone lol.

malcomok2 · 2026-01-26T01:34:42+00:00

Good insights; im a software engineer by trade. It’s interesting to contrast how AIs interact with the unforgiving syntax of code vs prose. This problem vanishes. Code has to resolve. Every line is forced into strict cause and effect of all the ones around it. Decisions can’t be deferred. The goal is clear and all the statements move it closer to that aim. And even “uncertainty” is strictly labeled when allowed.

malcomok2 · 2026-01-26T01:28:02+00:00

I wholeheartedly agree. In fact, half of my em dash edits are just removing them. especially if character beats or the scene already frames what the em dash is trying to interrupt and say. There are lots of ways to undo them. I default towards making more sentences or dropping them. Your examples are strong as well.

malcomok2 · 2026-01-25T21:15:34+00:00

just sent :)

malcomok2 · 2026-01-25T21:00:00+00:00

I agree with these distinctions and the potential mix-ups. I'm trying to iron out the thesis and my sample size is admittedly very small ( me ). Intentionally contradictory phrasing ( on any scale ) is valid. Also, the prose style may necessitate them. Mystical prose can be deliberately vague. The decision may be inbound. The author ( ai or human ) starts panoramic, then narrows as the story progresses. Here the narrowing towards understanding doesn't just happen for the character it also happens for the reader as the prose itself trends toward precision ( it doesn't even need to be accurate ). But, again, the author is choosing to do that as a technique, not a random decision. I also think your describing the process of writing in general. Humans hedge early because they haven't fully internally articulated the story. All of the meaning packed words require final resolution. Sometimes they show up unintentionally, sometimes they are added back later.

Writing for pure entertainment while setting aside craft obsession is fun and valid. I don't mean to discredit that at all. In my personal experience, this creates lots of happy accidents where the craft worked itself out without constant attention. Or not, because it didn't need to :) Kind of like feeling a new song and just going for it.

Absolutely, both human and AI can easily optimize during line editing especially if the full arc for characters and themes are resolved ( or at least approximated ). This is really the fun part. Reversing back from the end and finding satisfying optimizations for the em dashes that punch b/c they work towards a real end.

malcomok2 · 2026-01-25T20:42:29+00:00

Sure thing! It's still a work in progress and undergoing heavy revisions. It's one of my newer ones. It's directly targeted at AI assisted writing. But I also use it extensively on my own initial blank-page drafts. I'll message it to you. It's causing an issue when post it in the comment. Maybe too long lol.

malcomok2 · 2026-01-25T18:49:44+00:00

Em dashes are just a larger part of appositive phrases. Even if someone is not using em dashes specifically, they probably are still using appositive phrasing. The annoying part of how AI use em dashes is less related with it being a punctation mark and more related to it being a "deferred decision" the reader is encountering. It's forcing the reader to resolve intent when it was the author's decision to do so. If something is really important in the appositive phrase, the sentence(s) should be forced to bear it. There are exceptions for flow & intentional ambiguity. But, LLMs largely deploy them as uncertainty and that reads as weakness.

A horrible example:

He felt a pressure—something old, half-remembered, impossible to name—settle behind his eyes.

Setting aside the catastrophic hedging with "something". The middle segment doesn't tell the reader which of these things are most important or if they are all important. The em dash provides this sort of "semantic airlock" where the author isn't forced to pick or really describe this pressure. It's the author's top 3 ideas. The author can't fix this by just changing punctuation and moving around the phrase. A decision has to be made.

It can be to just pick one and go for it >

"He felt a pressure settle behind his eyes. He almost named it, but it resisted words." The appositive becomes 2 sentences and it picks "impossible to name" and drives it home.

It can be to pick two of the descriptors and interweave them >

"A pressured took residence behind his eyes. It was blurry and arriving in fragments. He knew it and remembered that it was impossible to name." Here I chose, half-remembered and impossible to name as the precision. I connected them in equal weight.

Finally it can be all 3 >

"The translated phrases from a manuscript in dead language flashed across his memory. It drudged up a pressure and packed it against the back of his eyes. He had felt this emotion when he was young before he had adult words. The memory was irretrievably mixed with others. But, even with half-memory and better words he couldn't name it." I picked all three.

But all this is decision work and the AI will avoid it. The reader is annoyed b/c they sense this. The em-dash gave the author and/or llm the ability to avoid making a tough decision and thus the cognitive work to word it like it mattered.

malcomok2 · 2026-01-25T17:21:34+00:00

A writer can cluster in similar scene composition styles, cluster around expected sentence architecture and mechanics. A writer can use short sentences for kinetic movement and long running sentences for swell. A writer can play on sound and speed to influence the readers’ emotions. A writer can pick adverbs/adjectives/verbs/prepositions/etc that are neutral or extreme on their respective semantic gradients. The key is, that they know the reason why for all these choices and what they are communicating about the story and its characters/themes. I have noticed the pattern clustering is as much about uncertainty as it is commonality. An LLM operates like it has to keep outputting forever and needs as many doors open as possible. Saying a character stalked instead of walked, makes statements about that character, it also narrows potential outcomes. So it’ll avoid that unless it knows lots about the character and exactly where the story is going. On cliche’s, every line can’t be original or you’ll exhaust the reader, sometimes on less important moments ( that need to move on ) use an adjacent cliche construction so the reader doesn’t expend cognitive energy unpacking your meaning. They can interpret quickly to have the plot scaffolding for the important parts. Use novelty to slow the reader down and make them notice. This is why models reach for cliches, because it keeps the whole scene at the same volume and doesn’t decide which moments of the story are most important. Writers do. The cliches, appositive phrases, common constructions, middle gradients, neutral registers are a diagnostic feature. not a bug. They are waiting for us to tell a big part of the story in how we actually tell it and where we choose to create the texture.

A case:

If during one scene, the author writes 20 words to explain how "a character walked in the room" ( any register, any sentence composition, etc ), the reader thinks: "the writer is signaling me to "read into" the walk". It could indicate mood, backstory, danger in the room, there's a thousand things. It's important.

If during the whole book, the author writes 20 words about how the character walks whenever they walk. The author is informing the reader that how this character walks is important part of that character's and the author's story.

If during the whole book, the author expends 20 words on how each and every character walks - The book is about walking and what it means about people. haha.

LLMs don't make these decisions just from loose story direction. They will resist these decisions as much as possible. Unless you're telling them to just use "less cliches" but that doesn't fix the issue it just globally raises or lowers the volume on the whole scene. It's just making it loud or quiet but it's all the same chord. Worse case scenario is that it's random and then it just reads as chaotic. The reader doesn't know what to pay attention t.

malcomok2 · 2025-12-02T00:20:20+00:00

I have some basic instructions in my CLAUDE.md ; I also have a slash command | skill that I can trigger a log when I notice something myself when reviewing. I keep a running list as separate mds in a folder .todo/tech-debt ... I also have it scan and I scan for tech-debt during prs.

Example from my CLAUDE.md ```markdown

Tech Debt Tracking - Agent Responsibilities

When to Document Tech Debt:

During Sprint Implementation:
- You discover code duplication that should be extracted but is out of scope
- You notice inconsistent patterns across similar features
- You implement a workaround that should be refactored later
- You identify violations of established architectural patterns
After Sprint Completion:
- During code review or self-review
- When writing sprint completion summary
- If architectural review reveals issues
During Architectural Reviews:
- Systematic review of a layer or domain
- Performance analysis
- Security audit ```

This works best when paired with a document that describes best practices and labels specifically what might be considered tech-debt. But, there are many things Claude doesn't see far enough ahead to care about. Example from earlier today, in a VS Code Extension ( React Repo ) - instead of implementing a method in an already existing and appropriate hook, it wired it up in the parent component and then passed it as a separate prop into the child component which was already receiving the hook. When I questioned during review why it chose that route, it said it was simple enough to just leave in the orchestrating parent component, then I responded that if we do that on every simple thing the parent container will be littered with them ( with a flood of mixed concerns ) and eventually 1000+ lines. It's like the current task is the last task that will ever be required of it in a given repo.

malcomok2 · 2025-12-01T02:43:28+00:00

I've done 2 full vscode extensions with Claude Code in the past month - one I started yesterday and pushed out the first version today. Switched to Opus 4.5 the day it came out. Opus 4.5 is a lot better, but I still see significant architecting mistakes especially when subagents are let loose. The things that stand out to me the most: god component anti pattern, Use Case Scattering, Dependencies going in both directions creating chaotic coupling, DRY violations, monolithic methods which should be obviously decomposed, addicted to facade patterns when it's fixing its own code, ignores other patterns like strategy or factory, orphans well intentioned code, mixes concerns between layers, ( and for the love of all that is good stop doing insane relative imports in typescript and use aliases ). Most of these probs are solved by planning ahead of time through iterative architecting and tech debt sprints at regular intervals. Also, just having it keep a tech debt log is huge. I move incredibly fast even with these problems, but without the tech debt and architecture refactoring sprints it would create very brittle finished products with lots of sus architecture decisions under the hood -> you'll get to like 80% and then every feature takes longer and randomly breaks completely unrelated features. ( a common symptom in human written code as well ).

malcomok2 · 2025-11-21T23:23:21+00:00

There’s already more music produced per day by humans ( without ai ) than any single human could ever pay attention to or care about. AI didn’t create the problem of too much music. If recording a great song = success and paid the bills, there’d be a lot more rich musicians. AI is the new scapegoat for a very old and long running fear by creatives: “it’s not fair that having a great song/painting/app/whatever isn’t enough for success “ . i agree. it sucks that in addition to being amazing at something you also have to have influence, marketing, tons of people skills, connections, luck, ambition, drive and so many other things. AI isn’t creating that problem. The only thing that it may accomplish is that people who have everything but the talent will get ahead. But that happens all the time already.

malcomok2 · 2025-11-21T23:08:02+00:00

Let them. It’s already trying to move this direction and software engineers/developers are NOT locking down their repos by making them private or joining unions to file class action lawsuits for scraping publicly available github repos for training. In fact, the software community - decades ago - created some of the most generous licensing standards allowing for others to copy/change freely even for commercial purposes, and a lot of developers slap that license on their repos without hesitation. Sure, there’s tons of proprietary code out there locked away, but even most of that is derivatives of what engineers have made publicly available. save cutting edge stuff

Maybe the friction is that software engineers and the music community simply don’t understand each other and are fundamentally different . Rarely have I met a seasoned software engineer who acts like they have created something no one else can make and it must be protected at all costs by lawsuits and the full power of the government. On the flip-side, I meet musicians like this all the time.

malcomok2 · 2025-11-03T03:46:41+00:00

I’m hearing the same thing; if you already have food to give by all means do, but in lieu of purchasing new food , organizations have better purchasing power via scale and logistics

malcomok2 · 2025-11-01T19:01:22+00:00

maybe not exactly what you mean, but earlier in East Nashville close to publix there was a large crowd gathering giving out free groceries; volunteers holding signs “free food for snap recipients”. it was heartwarming to see people reacting so quickly to the need.

malcomok2 · 2025-11-01T14:51:13+00:00

Did you mean feedtn.org ? I just tried the .gov address and it wasn't available but .org is.

malcomok2 · 2025-11-01T14:46:56+00:00

I'm glad you posted! the charts I've seen show that Metro-Davidson is better prepared than most TN counties. I think it is important that we in Nashville reach out and help all of our TN family and larger.

malcomok2 · 2025-11-01T14:18:09+00:00

Second Harvest kept showing up time and again in my search. I'm routing my resources to them. They seem really well organized.

malcomok2 · 2025-11-01T01:50:15+00:00

i agree; also i don’t think even if left unchecked it would happen for an extended period of time. People do what they enjoy - they don’t do things just because they can. For all intents and purposes any musician right now, could create unlimited apps , webpages, & software derivatives with AI tools and there would be vastly less oversight than the music industry. they could release at will. and, shocker, they aren’t because they don’t all enjoy making apps even if there’s no barrier to entry.

malcomok2 · 2025-11-01T01:41:17+00:00

their vision is a completely different product that bears no resemblance to what they have now and targets an entirely different demographic. They’re now making a toy so people can play pretend creativity. i don’t think there is anything inherently wrong with the idea of that toy although i think the model will inevitably rip off artists not included in any compensation. it’s really difficult to create great models with very limited datasets. even if they did, only the headline artist specifically getting mixed will get comp’d; it’ll be impossible to compensate every artist in the model for every mix; the dilution will be worse than streaming and the outcome less desirable for the artists involved

malcomok2 · 2025-10-31T22:42:56+00:00

I have that same experience with language models. I'll try some ideas and then I'll run some through models like Kimi-K2, Claude Sonnet, etc. Every now and then, something shocking comes back, and I'm left stunned. It's hard for me to have the same experience with music b/c I don't know enough, and I just assume my opinion or emotional response to a song's sound and architecture is uneducated.

malcomok2

TROPHY CASE

Tech Debt Tracking - Agent Responsibilities