Brainzer

Pure gambler, frontrunning your favorite KOLs

[Moni 🧙‍♂️ @getmoni_io]

Three researches went up on https://t.co/DKAocSf7KX over the last couple of weeks. We dig into crypto projects that look like they might matter and write up what we actually find.

> @OseroHQ. A distribution wrapper for @SkyEcosystem, dressed up as infrastructure. The legal entity is doing more work than the SDK. Worth watching.

> @HypernovaX. Hypernova is moving the prop firm onchain via @HyperliquidX. $3M from @Lemniscap, addresses published, contracts unverified. The framing is ahead of the proof.

> @Pluralis. Pluralis trains models no single party can extract — a third path between closed and open-weight AI. Code, run, funding shipped.

Full versions of researches at https://t.co/DKAocSf7KX. For free.

[blocmates. @blocmates]

https://t.co/gl9JuEsvb7

[Plata @platacrypto]

Daily reminder for another chart where it is just a matter of time $REI

The edge to edge fill gonna be glorious.

[Cryptic Tits (npc/acc) @cryptic_tits]

I've spent time looking at $REI purely from a technical perspective, but this overview is completely focused on investments and valuations.

banger quote: "Distribution can be bought. Interfaces can be rebuilt. Integrations can be replicated. A working reasoning system with learned structure would be a more technically specific asset"

@ajp_digital places REI in the "NeoLab" category - alternative AI architecture labs currently valued at $750M -$32B in private markets

REI gives public access to that thesis at a fraction of the price.

[Moni 🧙‍♂️ @getmoni_io]

MONI COMMUNITY IS ON FIRE WITH @eighty7ss's RAFFLES

@FerrymanTCG: from 11x to 363x depending on rarity
@FROGE69mg: free to 0.06 ETH each
@no_hoshii: free to 0.015 ETH each
@megatio: 3.75x
@giraffies_nft: 3.33x

5h left. 469$/lifetime. https://t.co/ERW3XkIKE0

[D2 Finance @D2_Finance]

Jez read Reminiscences of a Stock Operator and shipped it on top Hyperliquid’ tech ( not @Lighter_xyz )

onchain bucket shop. he confirmed it in this thread under @dipsybitsy “yep, fully transparent and the losers who fund it will own.”

the bucket shop pattern is 100 years old. customer trades at the listed price, the house takes the other side, nothing reaches the actual exchange.

Livermore made his early stake trading against them, then got banned from every shop in Boston for being too good. they died from two pressures: directional regimes that smoked the house, and ticker manipulation where operators pushed the real venue to harvest at the shop. both are live here. neither is solved by stacking five defensive parameters.

what is actually onchain: a contract that reads HL’s BBO via precompile and synthesises swaps against a Martingaler LP. zero flow reaches HL’s orderbook. zero funding rebalance. the only feedback loop is parasitic.

BBO manipulation attempts to harvest the synthetic spread degrade HL’s book without compensating the makers wearing the jitter. the venue extracts liquidity quality from @HyperliquidX ( fair enough!)

the fair launch plus 1000x leverage plus PAPER mint-on-loss design is engineered for initial FOMO. expect a fast first week/month. Jez’ inner circle volume comes in, asymmetric impact taxes the few winners, losers fund the LP and mint PAPER, the chart can look initially great if execute right.

this is the bootstrap window the docs explicitly subsidise at 100 PAPER per $1 of LP gain below 2M.

Then path dependence will shows up.

LP edge per trade is thin: 0.2 bps jitter band plus the convex bite of asymmetric impact on winning closes. order of magnitude, on a $1M ticket the LP edge is in the tens to low hundreds of dollars. one 5% adverse move on $1M of net synthetic exposure is $50,000 of MTM loss. edge accrues like √t under stationary flow. directional regime hits the LP linearly in t. √t vs t means one persistent trend eats months of accrual.

the half life of LP equity in a trending regime is short, and it gets shorter as size scales because the OI cap trails realised OI rather than leading it.

then the debt queue activates.

martingaler issues claims paid by the next loser. once the queue is observable, the EV of opening a new position is negative twice: once because winners get haircut, once because withdrawals sit behind every prior bust. rational flow stops. Queue does not clear.

PAPER, a claim on future LP revenue, is then a claim on revenue that must clear the queue first.

the cross-venue attack (@NaiveKrypto point in the thread) has its own path dependence.

wicking HL spot or perp to harvest the synthetic at the shifted BBO is only EV-positive once papertrade’s OI is large enough that the harvest exceeds the cost of pushing HL.

below that threshold, no one bothers. above it, every desk with an HL maker does.

self-limiting at small scale, openly hostile at large scale. the steady state is zero, the only question is the path.

all bucket shops are zero in short to medium term. the 1900s wave died within two decades, mostly to regulation and to operators eating them. the onchain version skips regulation but keeps the operators and adds a debt queue that hard-codes path dependence into the equity curve. the docs read like a list of every defence shops historically tried, in order.

stacking five does not change the shape of the failure mode, it just shifts where the failure surfaces.
closing thought. the whole structure is short volatility against directional flow, dressed up as a perpetuals venue.

it is the same trade as a Korean retail account systematically selling MRNA noise reversion while their own KOSPI 200 trends straight through the stop. works beautifully until the regime turns, then the half life is a week.

clever paper, novel emissions curve, real engineering. the structure is 100 years older than the precompile.

Hyperliquid

[Cryptic Tits (npc/acc) @cryptic_tits]

63 AI labs. pre-revenue. $1B+ valuations

$REI: already doing what most of these claim to… shipping products, real capital running through it, completely novel architecture

$20m

⏱️

[Plata @platacrypto]

https://t.co/we4VE6caxw

[John Scott-Railton @jsrailton]

BREAKING: You checked the weather this morning.

And you just told a surveillance company where you sleep.

Meet #Webloc, used by ICE, cops & foreign govs to track 500m+ phones.

No warrant required.

Our latest @citizenlab investigation + how to protect yourself 🧵/1

[francesco 🏰 @francescoweb3]

This is our first branded report in PDF, we also ran a lot of quant analysis on the oil markets on @tradexyz and the CME (NYMEX CLJ6) across overlapping hours and three different weekends to analyse the gap at opening, median order size and much more.

Asking everyone to take a look at this one if you are interested in @HyperliquidX, tokenisation, commodities, gold, oil, or just research.

Feedback is super welcome
Feel free to dm me

[James | Snapcrackle @Snapcrackle]

https://t.co/r0KLqneV5V

[Marc Zeller @Marczeller]

https://t.co/Jlf28T3uSM

[Rei @rei_labs]

Weekend Update:

Unit Usage Guide Volume 1 released
Updated for Core 0.4 and its mental model
Volumes 2 & 3 scheduled for Q1

https://t.co/5Np8z9d6HY

[Rei @rei_labs]

We crossed 1.2M API queries in December (new record). Big shoutout to @RFLnow for being part of it.

Core everywhere.

[Rei @rei_labs]

A Message from the Product and Dev Teams Before We Begin 2026:

In 2025 we learned what building for the next mental model feels like.

LLMs got everyone used to expect a certain thing from AI. say something, get it back. context persists within a session. it's familiar, it's what people know.

Core doesn't work that way. and honestly, nothing alive does either.

Core is cognitive architecture. It traverses concept spaces, evolves pathfinding strategies, forms relationships between ideas through reinforcement and feedback. decay is part of it, information that isn't reinforced fades but so is concept formation, competitive strategy selection and so on. It extracts meaning and not transcripts.

We took as much inspiration as we could from living systems. and living systems don't regurgitate training data. that's not a bug, that's how learning actually happens.

the gap isn't anyone's fault. years of LLM usage just built a certain habit; say it once, retrieve it within the session, no feedback loop, just dump and query. Core asks something different. you're not querying, you're teaching. same question gets better answers, not identical ones. corrections matter. reinforcement matters.

In the past six months, we noticed that our UI worked great for advanced users who get those concepts from the get-go. for everyone else, there's a learning curve we're still helping with and adding guides to tackle. on top of that, UI (Factory) data APIs we added free of charge as a closed beta perk sometimes returned nothing and MCPs have their own flaws, things outside our control that still hit the UX. builders with their own custom stable data feeds don't have that problem.

What worked the most for a certain demographic: builders who abstract the complexity, feed their own data, don't ask end users to prompt directly. @EclipticaOS is the first to go semi-public and hit a few thousand users in beta doing exactly that.

In a nutshell: every app built on rei adds indirect users who get the benefits without the learning curve. the infra doesn't need to be understood by everyone to be useful.

Beyond agentic core and mental models, learning curves and so on, the goal is fully capable digital entities that learn conceptually. right now Core handles reasoning really well. conceptual learning, numerical accuracy, things LLMs fumble. with Core Abstraction
(separate from the agentic Core on the frontend/API), builders can plug in external knowledge bases that are task-specific.
reasoning and retrieval without polluting your agent's brain. Abstraction is an intelligence layer for all AI, beyond agentic systems and text interfaces. it's destined to give builders complete freedom.

We put all our energy into reasoning evolution and learning. that's much more challenging and will always be what sets us apart. task-specific retrieval and db integration ship with abstraction. the foundation had to come first.

There's a reason AI feels like it's consolidating around a few big players. the models are massive, the compute is getting expensive, hardware costs are out of hand and if you're not running your own data center you're paying someone who is. we didn't want to play that game. Core is modular. we're aiming at making it possible to run on much less hardware than your average model even 10 versions away from this one. the goal was always to build something powerful that doesn't need billions to keep running.

Holiday season just ended, we're back to work. It's been humbling. Shipping something completely new isn't always obvious to get right. thank you for sticking around, it means the world to us. Happy New Year.

[reisearch @0xreisearch]

https://t.co/QWNI2xo8ZP

[Plata @platacrypto]

We have been once again one of the first discovering the MetaDAO narrative and talking about it since months.

We will always find the next major trend like we found $OMFG and $AVICI before everybody talked about it

Stick around on my X, try to join the @Sanctuary_DAO and learn.

[Moni 🧙‍♂️ @getmoni_io]

https://t.co/VGWnuCm9hD

[Moni 🧙‍♂️ @getmoni_io]

The Moni Community runs the game 🏎️
Here are the top 10 deals from last week.
All 2X’s don’t count (sorry, but we love them too).
Year-end is no excuse to slow down.

[Rei @rei_labs]

GitHub integration is now live in Rei Code Sandbox. Link your account, import repos (public or private), edit, and push.

Access directly via https://t.co/NHD7aLcqWj or through our app.