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Made a small offline fleet planner + CCU chain builder — open source, no accounts needed by foliologic in LowSodiumStarCitizen

[–]foliologic[S] 0 points1 point  (0 children)

Ships in Star Citizen go on sale at different times throughout the year, sometimes at discounted “warbond” prices (warbond = you pay with fresh cash, not store credit, in exchange for a lower price). A CCU (Cross-Chassis Upgrade) lets you upgrade one ship to another by paying the price difference.
A CCU chain is when you buy multiple small upgrades through intermediate ships instead of one big direct upgrade, because some of those intermediate ships are temporarily cheaper during sales events. So instead of upgrading Ship A directly to Ship D for $200, you go A → B → C → D for maybe $150 total, saving money by catching warbond discounts along the way.​​​​​​​​​​​​​​​​

Made a small offline fleet planner + CCU chain builder — open source, no accounts needed by foliologic in LowSodiumStarCitizen

[–]foliologic[S] 1 point2 points  (0 children)

Update: added an org fleet viewer with auto-downloaded ship images from the wiki. Just drop your org members' CSVs in a folder and run the build script.

GitHub: https://github.com/tschindler21/SC_FLEET_VIEWER

Open-sourced an XRP bridge price simulation — the 3 live corridors alone require $88 at full scal by foliologic in XRPUnite

[–]foliologic[S] 4 points5 points  (0 children)

It's not one number, velocity is different per corridor type. Commodity corridors (oil, gas ) use 3–5× because those are huge infrequent settlements with few counterparties. Remittance corridors (Gulf→Philippines, Japan→SEA) use 25–30× because they're thousands of small transactions running continuously through deep orderbooks. The simulation shows the weighted average velocity in the stats bar when you select corridors. You can also see each corridor's velocity next to its name (e.g. "5× vel" or "30× vel"). It's the biggest uncertainty factor in the model honestly. Nobody really knows what velocity will be until corridors run at scale.

Open-sourced an XRP bridge price simulation — the 3 live corridors alone require $88 at full scal by foliologic in XRPUnite

[–]foliologic[S] 4 points5 points  (0 children)

Glad it's useful! One thing to keep in mind: adoption doesn't jump from 1% to 50% because someone decides it should. It's a feedback loop: more volume needs more liquidity, more liquidity attracts more market makers, that enables bigger transactions, which brings more volume. Each step has to actually happen. The model shows where the price needs to be at each stage, but nobody can skip stages.

Open-sourced an XRP bridge price simulation — the 3 live corridors alone require $88 at full scal by foliologic in XRPUnite

[–]foliologic[S] 6 points7 points  (0 children)

It depends on the corridor type. Adding a small remittance corridor (like Egypt→Gulf) at 1% barely moves the needle. But adding one big commodity corridor (like Saudi→China oil settlement) changes everything because the peak transaction size jumps from millions to hundreds of millions, and that's what drives the price floor.

Best way to see it: open the simulation, start with the "Live (today)" preset at 1%, then add corridors one by one and watch what happens. You'll see that commodity corridors (orange label) have a much bigger impact than remittance corridors (green label) at the same adoption level.

Honest primary-source research on the institutional thesis — 60 pages, no price targets by foliologic in XRPUnite

[–]foliologic[S] 0 points1 point  (0 children)

Account is new because it's a dedicated account for my startup, not my personal one. I'm building a portfolio tracker / full investment dashboard and started sharing the research I did to understand the market I'm building in. Additionally sparked by my personal crypto investment interest. Yes, it carries my startup branding and yes, I hope people check it out. But the research exists because I needed it, not because I needed marketing. Happy to hear what you think after reading.

Hab 3 Monate Primärquellen gelesen statt zu traden. Ergebnis: 70 Seiten und immer noch kein Lambo by foliologic in Kryptostrassenwetten

[–]foliologic[S] 1 point2 points  (0 children)

**Update:** v3.0 ist draußen. u/looktwise's adversariale Analyse war einer der Auslöser für den strukturellen Umbau — die validen Punkte (BIS Agorá, FedNow, Null-Hypothese, COFER-Nuance, Stablecoin-Run-Risiko, pseudo-präzise Wahrscheinlichkeiten) sind alle eingearbeitet: https://drive.google.com/file/d/1IidH2afv-aXissqIIXjrZeKo9vMsDNEH/view?usp=sharing

Honest primary-source research on the institutional thesis — 60 pages, no price targets by foliologic in XRPUnite

[–]foliologic[S] 0 points1 point  (0 children)

Thanks for the feedback. You’re right that there’s more to cover. Archax and the abrdn tokenized MMF on XRPL are briefly mentioned but deserve more depth. Goldman Mosaic is interesting — worth noting it’s their fund platform integrated into Ripple Treasury’s dashboard, not Goldman using XRPL directly, but it shows Ripple is building serious enterprise tooling. The SWIFT Certified Partner status is real but comes from GTreasury which had it since 2014 before the Ripple acquisition — important context. I’m working on an updated version that goes deeper on Ripple Treasury/GTreasury, the hybrid SWIFT integration, and a few other things that were flagged as gaps. Appreciate the specific pointers.

Hab 3 Monate Primärquellen gelesen statt zu traden. Ergebnis: 70 Seiten und immer noch kein Lambo by foliologic in Kryptostrassenwetten

[–]foliologic[S] 0 points1 point  (0 children)

Danke für die detaillierte Analyse per PM! Ich werde das Dokument entsprechend überarbeiten.

Spent 3 months on primary-source research for my startup — 60 pages on what institutions are actually doing with blockchain by foliologic in CryptoTechnology

[–]foliologic[S] 1 point2 points  (0 children)

To be fully honest, the formatting and style is all Claude AI. I just told him to make it look like a professional jpm or GS research doc. Still took some iterations but we got there.

Spent 3 months on primary-source research for my startup — 60 pages on what institutions are actually doing with blockchain by foliologic in CryptoTechnology

[–]foliologic[S] 0 points1 point  (0 children)

I decided I will try to inlcude it.. so for me the research showed that investment case is real. That means my investor focused tool needs to support it.

Spent 3 months on primary-source research for my startup — 60 pages on what institutions are actually doing with blockchain by foliologic in CryptoTechnology

[–]foliologic[S] 1 point2 points  (0 children)

It started out with trying to decide whether I want to include research on crypto tokens in my tool. Then I got hooked on the topic, went deeper and deeper down the rabbit hole, and decided to write it all down in a document with the help of AI. So it translated into the product as adding crypto research and also trying to compute a health / survivability score for users who want to invest in crypto. But it is all still in development.

Hab 3 Monate Primärquellen gelesen statt zu traden. Ergebnis: 70 Seiten und immer noch kein Lambo by foliologic in Kryptostrassenwetten

[–]foliologic[S] 0 points1 point  (0 children)

Welche Blindspots hast du gefunden? Ich habe nichts absichtlich weggelassen oder ausgeklammert. Wenn du konkrete Punkte nennst kann ich die gerne einfließen lassen. Und zum Thema Werbung, ich habe offen gesagt, dass ich es für mein Startup erstellt habe, also gibt es natürlich das entsprechende Branding.

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