u/Dependent-Hamster923

not being dramatic but i really cannot categorize my own manuscript and it's starting to be a real problem, i need this for querying, for shelving it in my own head, for literally filling out a form

it's not epic fantasy and there's no quest and no chosen one, the stakes are one family and one house. it's not quite literary fiction cause there is, undeniably, one object in it that does something it should not be able to do. it's not magical realism in the way that term usually gets used, because the "magic" isn't ambient or symbolic, it's a specific mechanical thing with rules i actually worked out. it's not urban fantasy cause there's no hidden magical society, just one anomaly sitting in an otherwise completely mundane world.

tried "slipstream." tried "the fantastic." tried just writing hard to categorize, sorry in the genre field of my own project notes in mythril and staring at it for a while. genuinely asking, is there a name for this specific shape of book or are we all just inventing a new made up subgenre every time one of us writes something like this

any idea what genre is that

he's been writing a web novel for years, we're currently around chapter 240. writing is the one thing he's absolutely refused to give up after the diagnosis, and honestly I don't want him to either.

but lately it's getting harder. he's started occasionally forgetting whether two power systems collide, or if the townsfolk have already met, whether a city's been introduced before, or how a particular part of the power system worked 100 chapters ago. sometimes he'll accidentally contradict his own lore without realizing it. worst part is the readers notice. I usually catch it before a chapter goes live, but I work a 60-hour week and I can't keep manually maintaining a giant Notion database forever.

I'm also the one managing our Discord community now, and every week there are questions like "didn't this character already know him?" or "whatever happened to that artifact from chapter 80?" or "can someone explain this part of the power system?" my bf remembers these things but he's forgetting more now, so we're wondering if we could just use something like a wiki, a page for every piece of magic and every character in the story, where readers could go and get the official answer.

half the time I end up spending an hour searching through hundreds of pages just to answer one question.

I've tried keeping everything organized in Notion moved a lot into Obsidian too, hoping backlinks would make it easier it helped for a while, but once a story gets into the hundreds of chapters it still feels like I'm constantly playing catch-up I even tried Mythril even tho the makers are adding new features often but its not there yet it's still in its early stages, so for now I'm looking for something that can help us bridge the gap until tools like that mature.

the doctor told us that routines and external memory systems can help reduce the mental load, so that's what I'm trying to build around him.

this story is his legacy. he's told me that even if he has to rush the ending a little, he only has around 60-80 chapters left before it's complete. more than anything he just wants to finish the story while he still can.

so I wanted to ask authors who've written very long series, what do you actually use once your story gets too big to keep in your head. I'm not looking for another generic note-taking app, I'm looking for something that makes it easy to track characters, relationships, locations, timelines, lore, and power systems, and to answer "where was this mentioned" without me manually maintaining everything by hand.

any recommendations would mean a lot. thank you

posting back cause I added links which i didn’t know was prohibited

when multipke people are working on prompts at the same time . engineers , product manager , content people . how do you make sure nobody overwrites someone elses work or pushes something tp prod that hasnt been revieed

seen a few tools come up for this. langsmith , orqai , langfuse , humanloop , promptlayer

langsmith: tracing is good, but collaboration beforee something goes to prod feels like an afterthought, no real approval flow before a prompt get pushed

orqai: approval flows and role seperation betweenn who edits and who deploys is more of a focus, newwer so edge cases in collaboration flow still surface occasionally

humanloop; has reviewed and feedback flows built in, works better for smaller teams,, start feeling limited when oyu have multiple people touching the same prompt across different roles

promptlayer: tracks prompt history well , simultaneous editing and conflict resolution across a large team feels like it was not really designed for that use case

langfuse: good at showing what happened post deployment , collaborative editing and review before deployment feels underdeveloped for biggger teams

how are people actually structure this. who owns prompts and who can edits and what gets approves before thngs go live.

what is working

rates arent coming down as fast as people i know predicted and a lot of them are looking to short long duration treasuries . tlt kinda trade without any broker..

the onchain way to do this perp contract that track treasury prices without holding any bonds. gains network has this and been there for a while now . you can short long duration treasury exposure from a wallet . ostium has real world assets and treasury related markets fit into the category . these are the two relevant for these kinda trades onchain . gmx and hyperliquid are more like crypto focused.

this is not like shorting real treasuries or buying tlt puts . you are just getting a price exposure .this isnt the actual bond market participation .

if the view is rates stay higher for a long time and you want to express that without an involvment of a broker . the infra for that trade exists onchain now.

cfd brokers , the place everyone goes to trade forex or gold. you get a contract for difference and somewhere in the fine print the broker is on the other side of your trade. hoping you lose. while also taking your money .

this is how market maker brokers work and most people find out when its very late. (blockchain fixes this part)

a few platforms do forex and gold onchain. ostium and gains network are the most relevant ones if rwa is what you want in particular . ostium is newer and built around for this. gains has been doing it longer and has more pairs. both use external price feeds so the protocol is not your counterparty in the way a cfd broker is.

gmx is bigger but crypto is its thing . forex is secondary.

synthetix has synthetic versions of forex and gold . older. more complicated. has a whole ecosystem around it which is either a feature or overhead depending on what you need.

the tradeoff is that you need usdc before anything else. gas exists even on l2. slippage also exists. liquidations are fast and also not negotiable.

but the core conflict of interest. the broker holding the other side of your trade. that part is a different in onchain. the contract settles against a price feed not against a desk that wants you to lose.

thats the answer to the question.

ostium is most direct one. its specifically built for forex and gold without a broker. real world assets . it has cfd kinda execution with the same access to liquidity that institutional dexess have and its on arbitrum which is cheaper than a regular eth . this is the closest thing to decentralised cfd broker that actually exists. gains network does forex. actual currency pairs with high leverage which is exciting until you remember high leverage is also how people lose everything very fast. its been around longer than ostium. synthetix has synthetic version of gold and forex which sounds kinda weird. its older and more complicated and has a whole ecosystem built on it.

so then i realized blockchain fixes this.and there are actual platforms that do this.

you need crypto before you can do anything. theres slippage and gas fees.

so yes the alternative exists. ostium and gains network are the most relevant for forex and gold in particular. you can got rid of dodgy broker but for you need to learn something which is not very simple.

Its obvs that we'd never met in person and only sparred in comment sections over a genre discourse thing that got surprisingly heated a while back and it was the kind of disagreement where you build an entire mental image of someone from a handful of tweets

be it some funny coiencedent that placed next to each other at a regional book fair completely by accident cause apparently organizers had no idea then we spent the first twenty minutes in stiff, overly polite silence but then a slow afternoon with nothing to do but talk turned into an actual conversation, and by the end of the day we were comparing notes on royalty statements and complaining about the same cover designer neither of us had good experiences with

got lunch together after funny I’m saying this but o kinda liked her and I don't think either of us was wrong about the original disagreement exactly, we still think different things, but I don't think either of us fully accounted for the fact that a real person exists behind the account you're arguing with, and that person can be someone you'd actually enjoy having lunch with once the specific disagreement isn't the whole of who they are to

nothing writing related but felt like it’s a space i can vent at tho we’re planning a non-cannon one shot collab b/w our stories now

I recently shipped a chatbot and its working well but how to figure out when it says something wrong to the customers

There can be retrieval failures

When rag pipeline pulls the wrong chunk , the model will answer confidently but from  bad context . The output looks fine even while using the wrong source . This is very hard to catch ,I need to log what got retrieved alongside what got returned.

Boundary violations c an happen

The chatbot is scoped to customer support but what if it starts to answer questions it shouldn’t . Not hallucinating but operating outside its defined scope without flaggingg it.

Numeric or date errors

Model can get calculations or pricing wrong more than people expect when numbers appear in context rather than in a structured field . evals that check for this are not common.

Confident refusals

The model can refuse to answer questions it should handle . The customers get a dead end which can be technically correct but functionality breaks the experience and will be missed if I only monitor for bad outputs not ones which are missed.

Persona drift

The model was prompted to behave a certain way . over long sessions or after certain touchpoints it starts dropping the persona with tone changes or style changes

i did a lot of research and found a few names like orqai, arize, aporia , fiddler ,whylabs

arize - statistical output monitoring is good. catching semantic failures like boundary violations or persona drift will need to setup a custom eval

orqai - evals are tied to prompt versions and help catch persona drift and regression across versions, observability and evals together in one place. It seems newer so community might be still catching up

Whylabs - the distribution drifts is its core feature and response level semantic failure feels underdeveloped

aporia - the real time guardrails is the main function ,and is good for boundary violations and policy breaches and retrieval failure feature detection isnt up to the mark

Fiddler - systematic risk based monitoring feels very native and numeric and factual accuracyy tracking looks developed here but has a very heavy setup

what is working for people across the failure types of chatbot and what would they suggest?

been trying to understand this for a while and i get the obvious reasons as leverage, capital efficiency, being able to short but if someone already has enough capital to trade spot outright, what actually makes perps the better choice

is it mostly about not having to own the underlying asset and the flexibility, the liquidity, or do experienced traders just think they're a genuinely better instrument regardless of account size?

ig there's a real answer beyond leverage and the one big one is hedging without selling, if you hold a large spot position long-term and don't want to close it, you can short perps against it to hedge short-term downside without touching the actual holdings. another is funding rate arbitrage, buy spot and short the equivalent perp at the same time, and if funding's positive you collect that as yield, market-neutral, nothing to do with wanting leverage

perps also tend to have deeper liquidity than spot on the same asset a lot of the time, so even someone with plenty of capital might just get a cleaner fill

there's something i was missing cause whenever experiencd traders talkin about markets they almost always seem to gravitate toward perps instead of spot, and now i think i get why tho am not sure

so for those of you who trade both, what actually made you stick with perps

I was writing linearly like a damn kid start of chapter to end and kept discovering the ending wasn't strong enough only after I'd already committed to everything leading up to it

then 3 beers down I had a revalation and switched to drafting the last paragraph of a chapter before anything else, then writing backward into it

meaning every scene in the chapter is now built to arrive somewhere specific instead of wandering until I find a stopping point chapters are shorter and endings hit harder with a mall process change, bigger effect than I expected do with it what you must

been seeing alot people talk about tokenized stocks, gold, forex, and other RWAs onchain might be missing something idk but still trying to figure out the actual advantage

if i want exposure to Apple, gold, or EUR/USD, i can already get that through traditional markets, so what makes the on-chain version better 24/7 trading, leverage, global access, being able to use it inside DeFi, or something else i'm not seeing

but as it turns out there's a sharper answer than just conveniencemost traditional forex and CFD brokers, the exact venues you'd use for this kind of price exposure otherwise, are often literally the counterparty to your own trade. they profit when you lose, which is a real conflict of interest baked into how a lot of retail brokers actually operate. an on-chain perp isn't your counterparty in that same way, you're trading against a pool and LPs instead, different tradeoffs, but not that specific one

still not saying there's no case where a traditional broker makes more sense, there probably is. but it's not just crypto solving problems traditional markets never had, and it's not just a more open version of the same thing either, it's actually removing a specific structural conflict that exists in a lot of the traditional retail trading industry.

if you trade RWAs on-chain, what's the actual reason you picked it over a traditional broker or platform

started at levels in the single digits with meaningful jumps we're two hundred chapters in now and characters are casually referencing numbers in the tens of thousands, and a reader did the math comparing early chapter power differences to current ones and showed that my current "small" gap between two characters is functionally bigger than the entire journey from chapter one to chapter fifty

not sure yet whether to introduce a hard cap, switch to qualitative tiers instead of raw numbers, or just accept that this is what long running systems do and lean into the absurdity of it. open to hearing how other people have handled a system that's outgrown its own math

we've been writing this serial together for two years we started it as a discord collab that turned into something real with split POV chapters, weekly calls, the whole thing I write and relate to the villain where he's the hero somewhere along the way we just started calling each other by our usernames, and it never came up that those aren't our real names (playing the picture perfect villain for months LITERALLY)

had to ponder about it today when a mutual friend asked wait, who's Corvid actually? and my co-author and I looked at each other on the call, both realized we genuinely didn't know, and had to formally introduce ourselves months into a working partnership that's produced 400,000 words together

His name is Marcus nice fella but I don't think either of us is going to stop calling him Corvid though

a provider  updates a model and the prompt starts changing its behaviour . how to catch it before users do

it has several type of regression and each one is comes out differently like

quality drift - output accuracy pulls down after a model update and there is no hard error and no alert . the aanswers starts to get worse  over time . it only shows up when you compare it against a baselinee you captured

latency regression - th e response times slows up after a provider change and it effects the user experience . It can be easily miseed if you are not tracking p95 and p99 seperately from average latency

format regression - the model returning clean structured output after an update , starts adding extra text and change json structure and dropping field .

prompt sensitivity - prompt that worked starts to behave with inconsistencies. with same input different outputs can be seen . the update in model changed how sensitive it is to pphrasing with no announcement .

capability regression - if the model handled a task well before . after update it stops doing that specific task incorrectly .The function calls behavior changes and tool use breaks and edge cases that passed evals before starts falling

i found out a few tools to help like orqai , whylabs , aporia , fiddler , arize

arize is good at detecting drift across output distributions but the catching format and capabilities needs custom eval configuration

orqai has eval pipelines tied to prompt versions and catches drift across versions. It is newer so third partyy integrations is still catching up

aporia catches real time guardrails and catches issues real time but proactive regression detection before deployment seems very limited

fiddler has systematic baseline comparison feels more native given the model risk background  but the setup feels heavy for teams outside regulated industries.

whylabs has statistical drift monitoring is main function . llm specific regression type prompt sensitivity looks veru underdeveloped.

what is actually catching regressions before users hit them . automated evals , canary deployments or something else?

yk the trope of having one kingdom with onelanguage and religion and ethnic look with same style of dress to segregate kingdoms with these as if borders were drawn around cultural uniformity instead of the really really messy accidents of conquest with forced migration and trade that actually produce real countries been reading alot of history too and most real nations are patchworks with multiple languages coexisting badly with territorial like regional dialects that barely understand each other. A capital culture that looks nothing like the borderlands three hundred miles away

thanks to my history professor jotting it down in our mind time n time again that I could figure that my first draft had this exact problem, one kingdom equals one culture, clean and wrong revising it now to make my largest kingdom actually contain three distinct regional identities that resent each other more than they resent the neighboring country, which is a much more interesting political landscape than the good kingdom and the other kingdom ever was

writing this as a reminder to help my fellow writers

[ Removed by Reddit on account of violating the content policy. ]

as of now data residency just became a hard requirement for us. legal wants to know where the data is sitting and gonna need proof if someone asks

been on langsmith and languse for a hwile now. both are working fine tbh. both work fine for the llmops side but eu data residency is not enough for what the compliance is asking

langsmith have a limitation for eu data residency and will get complicated if the legal is strict about where data acutally sitting

langfuse has self hosting in eu , since it is opensource , cloud version worht checking before assumming and mainitaining self hosted setup is its own overhead..

started looking at newer options got feww

brainlogic - eu based so gdpr feels more native, llmops feature depth is not wide compared to its peers

orqai - eu data residency and gdpr is covered , soc2 also there but the community is still smaller than the more established tools

stackai - eu hosting option is there , more no code workflow tool than proper llmops platform , compliance depth varies by tier

most options are us first and with eu as an addon. eu native with proper llmops functionalities is difficult to find. anyone running llmops with strict eu data residenccy . what did you land on and did it hold up when compliance actually checked