TRAPPERVERSITY

STRATEGIST • 3BLOCK • CVO • TRAPPERVERSITY 🥫🔌

[TRAPPERVERSITY @trapperversity]

@ShaniceBest https://t.co/fFIyMjxrRg

[TRAPPERVERSITY @trapperversity]

Trust bro we good 🚨🤦🏽‍♂️

[Arkham @arkham]

Someone just withdrew ~1% of all the ZEC in Zcash’s shielded Orchard pool.

Theoretically, Orchard now holds 3.88M ZEC, worth $1.65 Billion.

ZEC is up 70% since the bottom caused by the discovery of the Orchard Pool Exploit.

[TRAPPERVERSITY @trapperversity]

This time is different “trust me bro” 🤣

[𝗰𝘆𝗰𝗹𝗼𝗽 @nobrainflip]

🚨US STOCK MARKET IS ABOUT TO DUMP HEAVILY:

Apple went public at under $2B and 15x revenue

SpaceX goes public at $2T and 100x revenue

I’ve been in the markets for 13 years, and IPO boom we’re seeing now is the biggest red flag I’ve ever seen.

Here’s what will happen & why:

First, let's talk about Apple example, where you got a $2B valuation with $2T here

So basically retails are not just not getting early but buying at the richest valuations, while early investors just exit

Here is more evidence:

- Fidelity cut min investment from $500K to $2K
- SpaceX allocated 30% shares to retail
- Millions of new buyers invited just before listing

All of that while insiders are owning 95% of shares, which means that $1.66T worth of stock is held privately

And even that's only the beginning

Instead of a standard long lockup, we have 60 days, 20% unlock, +30% stock move and another 10%

Days 70, 90, 105, 120, 135 recurring 7% release and after Q3 earnings another 28%

Means that by November, ~93% of insider shares will become sellable

Institutions are already front-running this forced index buying by:

- shortened inclusion timings
- selling current holdings
- raising cash

Based on all of that, you can already say what crash is waiting for us and we are not even talking about current market weakness

Retails are mass-selling assets to fund IPO participation

And as I said before, institutions are selling too to prepare for forced buying later

Another great reminder would be that the company itself, I mean SpaceX is losing money heavily

Q1 2026: $4.3B losses

Total losses are at $41.3B

There are the details that retail don't think about cause IPO docs have 300 pages, most just skip all of this info

Anthropic and OpenAI are the same story - valuations inflated by circular investment flows involving NVIDIA, and priced at levels that make little sense.

But the fact that these IPOs don’t deserve their current valuations because the companies aren’t profitable - and likely won’t deliver the profits investors are pricing in - is only half the problem. That’s just why I expect most of them to trade significantly lower within a year.

The other half is where the money comes from.

Capital flowing into these IPOs doesn’t appear out of thin air. Investors sell existing stocks to free up cash and participate in new offerings. That creates selling pressure across the broader market.

We saw the same dynamic during the dot-com era in the late 1990s and early 2000s, and we’re seeing it again today.

That's why if you read this, you probably get the biggest informational edge in your lifetime.

And now choose whether you want to join IPO and become that exit liquidity or actually make money from it

In the coming days I will tell you more details and my strategy on how I am planning to play this out and make money

So make sure to follow me and turn notifs on

[TRAPPERVERSITY @trapperversity]

@ShaniceBest

[ProfitsOverWages 🧼🇩🇴 @ShaniceBest]

The World Cup in Miami is going to be insanity ⚽️

We locked in a huge watch party series at a 15,000 SF venue with 500+ people expected DAILY across the tournament from June 22nd through July 19th.

Brands: this is the kind of IRL attention you can’t fake online.

High energy crowds. International audience. Viral content opportunities. VIP experiences. Real community. Real culture.

Looking for sponsors + strategic partners across:
hospitality, liquor, sports betting, fashion, tech, web3, food brands, recovery/wellness & lifestyle.

If you want your brand attached to one of the biggest moments in the world this summer send me a DM.

[TRAPPERVERSITY @trapperversity]

Ai will replace you only if you dont add it to your life .

[Andrej Karpathy @karpathy]

LLM Knowledge Bases

Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So:

Data ingest:
I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them.

IDE:
I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides).

Q&A:
Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale.

Output:
Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base.

Linting:
I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into.

Extra tools:
I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries.

Further explorations:
As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows.

TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

[Clemente @Chilearmy123]

POV: The Crypto BD guy that was “networking” at E11even until 6 AM last night

[TRAPPERVERSITY @trapperversity]

😵‍💫

[OpenSea @opensea]

may the 4th be with you 🫡

koda yoda ftw

[TRAPPERVERSITY @trapperversity]

@Ape1926 @Drinkboredvodka Always a vibe hanging with the NFTs brosss 😂✌🏽

[Sailor Gary @Ape1926]

Consensus was absolute banger!

#ModelsOnBottles

[TRAPPERVERSITY @trapperversity]

The 🐐 @SuiNetwork

[TRAPPERVERSITY @trapperversity]

@pudgypenguins 🫵🏽🔌

[TRAPPERVERSITY @trapperversity]

@SuiNetwork ❤️ 🤝

[TRAPPERVERSITY @trapperversity]

@SoeHaghighi @consensus2026 ❤️✌🏽🔌

[4eva 🤙🏻 @4evaFamouss]

Miami 📍

Active❗️

@okx

[TRAPPERVERSITY @trapperversity]

@SuiNetwork Miami ❤️✌🏽

[TRAPPERVERSITY @trapperversity]

@4evaFamouss @adultarts @okx real...

[TRAPPERVERSITY @trapperversity]

@CihunSol @4evaFamouss @okx GM gang

[TRAPPERVERSITY @trapperversity]

Must pull up today fam … 🔌✌🏽

[ProfitsOverWages 🧼🇩🇴 @ShaniceBest]

Hosting this in the city I call home feels special 🫀

Miami has always been more than a backdrop to me. It’s energy, culture, people, and presence.

We’re bringing all of that into one room in Wynwood in less than 48 hours during Consensus Week.

Come be part of it 🙌🏽

RSVP below.

[TRAPPERVERSITY @trapperversity]

@alcidezx3 @4evaFamouss @okx Pretty decent nice turn out and good connection i would say gang

[TRAPPERVERSITY @trapperversity]

Gang in Miami