Use my referral link to join the JTX waitlist. jtx.trade/?ref=bluehorse…
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Blue Horseshoe
2.1K posts
Blue Horseshoe
@BlueHors3Shoe
No Limit Holdings. Bud Fox “Blue Horseshoe loves Anacott Steel.”
Katılım Ekim 2020
6.5K Takip Edilen705 Takipçiler
We fxxked up.
Our dev mistakenly used the wrong access token while deploying GetClaw’s new feature, and now it can fully control our X account.
Any engagement with our posts will now count as a command to GetClaw.
Until we regain full control, please DO NOT engage with any of our posts, things could get unpredictable...
Thank you all for your understanding.
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Blue Horseshoe retweetledi
A lot of folks are misinterpreting this quantum research from google. It is pretty impressive that physical qubit counts are scaling through magnitudes (nic carter has already covered this extensively) and that the theoretical amount of physical qubits needed to crack ECC is dropping drastically due to better error correction, but nothing has changed related to the amount of logical qubits theoretically required to break bitcoin signatures. This is still estimated to be in the 1,000s. As a reminder, the best QPU systems today (IBM, Google, Quantinuum) are still only at ~10 logical. So we are still pretty far away (i'd guess multiple cycles) from bitcoin being in near term danger. However, btc has a strong culture of ossification and change is very slow, so we need to start working on solutions today and prioritize this network upgrade. That said, I am personally not a believer in quantum FUD being a real issue for btc macro bullcase in the short - medium term, and institutions overindexing on this risk are likely well over their skis.
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Fun Fact from Messari’s State of DePIN 2025:
$GRASS is sitting on 57+ petabytes of multimodal public web data (video, audio, images), enough to train frontier-scale video generation or TTS models from scratch.
Most people still think “data scraping” = a few TB of text.
1/2
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Blue Horseshoe retweetledi
New Stateful episode with @TulipKing and @brezshares, hosted by @masonnystrom.
Bitcoin vs Gold: Why 2025 was different
- Bitcoin's $2T wasn't ready for nation-state flows
- Gold's $20T could absorb central bank diversification
- Nations adopt Bitcoin last, not first
0:20 Stateful Overview
01:05 Bitcoin vs. Gold: 2025 Store of Value
03:57 Why Bitcoin Wasn’t Ready for BRICS
06:05 2026 Outlook: Catch-Up Trade or Continued Divergence?
09:19 Is the Four-Year Bitcoin Cycle Dead?
13:30 Bag Check: Bitcoin, Zcash, and Uranium
14:43 Uranium Thesis: AI Power Gaps & 2026 Contract Rollovers
17:27 Finding the “Amazon Bottom” in Altcoins
19:35 Private Money Power Law
22:30 Bearish or Bullish: Altcoins Are Dead Until Token Equity Is Resolved
31:01 Bearish or Bullish: Quantum Threatens Bitcoin
37:23 @brezshares 2026 Trends and Predictions
41:24 @tulipking 2026 Trends and Predictions
44:03 A Fascist Economy in 2026?
48:14 Tether Flipping Ethereum
51:33 Resurgence of Hyperliquid & Equity Perps
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.@hyperbuilder_hl Official Lookbook - Autumn Green Hyperliquid Hoodie
Fabric: 100% cotton, 380 GSM
Fit: Oversized
Shipping worldwide
A basic, minimalist design for everyday wear. Suitable for both tropical and temperate climates.
Explore more at: hyperbuilder-3.myshopify.com/collections/all
*You can place your order directly through me if it shows “sold out” in your region or if you prefer paying with stablecoins on other chains.
ellie.hype@ellie_nfts
.@baynPSD "All roads lead to Hyperliquid" Collection Fabric: 100% cotton, 280 gsm. Fit: Oversized. Shipping worldwide. Use "BAYN" code for extra discount: hyperbuilder-3.myshopify.com
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Blue Horseshoe retweetledi
Looks like we're expecting cloudy skies tomorrow.
🌧️ Be sure to prepare for the rain. 🌧️
Bring your umbrella & waterproof jacket and have a great day day.
GIF
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@luishXYZ @holy_moses7 @Polymarket @PolymarketTrade Easier to just hold a T-bill or he farming airdrops?
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This Polymarket trader holds $86k in both YES and NO shares.
Not because he's hedging.
Not because he's confused.
But because he's farming 4% risk-free with a strategy most people don't know exists:
Polymarket pays 4% annual interest on all open positions in markets that resolve far in the future.
This isn't a bug, it's by design.
If they didn't pay the risk-free rate (US treasury yield), nobody would lock up capital in long-dated markets when they could just hold treasuries instead.
Let's look at @holy_moses7's portfolio as an example (see screenshot):
He's holding 63,000 YES shares AND 63,000 NO shares on the same JD Vance 2028 election market.
- Total position: $86.8k
- Directional risk: Zero
- Annual return: 4%
He's completely delta neutral (market movements don't touch him).
But his idle capital is earning while sitting ready on the platform.
The moment he spots an opportunity, he merges those positions back into USDC and places his bet. (It take like 30 seconds.)
BUT:
Don't buy YES and NO shares on the open market.
You'll get destroyed by the spread between bid and ask prices.
Instead, use two Polymarket features that most people don't know exist:
"Split" and "Merge"
Find them by hovering over "more" in the order interface.
Split: 1 USDC → 1 YES token + 1 NO token
Merge: 1 YES + 1 NO → 1 USDC
Both are free, no fees.
Here's what you do:
1. Choose an eligible market (like the US 2028 presidential election market)
2. Use "Split" to convert your USDC into equal YES/NO positions
3. Your capital earns 4% APY while staying 100% liquid
4. When you want to trade, use "Merge" to convert back to USDC
5. Place your bet
Nobody talks about this because it's not sexy.
But it's super low risk and profitable.
The Polymarket chads understand that 4% risk-free beats 0% on idle capital every time.
Every dollar in your account should be earning.
This is one trick that separates casual users from people actually making money on the platform.
Now you know 🫡
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Risk-aware DeFi starts now.
Credora by RedStone launches on @MorphoLabs and @sparkdotfi, bringing live, automated risk scores to the heart of DeFi: lending markets.
As capital flows onchain, only risk-aware data can power what’s next 🧵
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BREAKING: President Trump has pardoned convicted Binance Founder Changpeng Zhao (CZ).
Welcome back @cz_binance.
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The Future of Collectible Perpetuals is nearly here
Trove Beta goes live soon - early access is limited
Join us now: trovemarkets.com
Need an invite code? Reply below
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Love the charts!
Polaris@PolarisFund
Humanoid-robot economics look complex. Until you zoom into the Bill of Materials (BOM). BOM isn’t just a cost sheet. It’s a "strategy map". It reveals where cost hides leverage, where complexity hides moat, and where hardware and software meet or clash. - when you know how to read it, the BOM tells you: - which subsystems drive cost vs. differentiation - where integration complexity creates or erodes margin - what IP is worth owning (mechanical, model, or data) - how geography impacts iteration speed - why some companies scale like SaaS and others get stuck in hardware Let’s walk through the robot stack with the BOM lens on🔍 ⚙️Actuation drives cost and moat At the base of every robot is actuation. That’s where nearly half the BOM cost sits and where most of the defensibility lives today. Motors, gearboxes, torque systems: - have complex supply chains - require high levels of integration - are extremely competitive But they’re also strategic strongholds. Vendors like LeaderDrive, Harmonic Drive, and Beite used to dominate here with hard-to-copy IP built on: - tight tolerances - decades of iteration - end-to-end vertical integration If you control actuator design, you control a robot’s core physics. These systems though are now getting replaced AI centric ones, which favors on dynamic behavior and cost, being less IP centric and hedge more on strong manufacturing and good overall product design. 🧠 Takeaway: high cost + high IP = hardware moat 💻 Software eats margin But moving up the stack, the leverage flips. Compute, sensing, and model layers might each take up ~10% of the BOM, but they disproportionately define: - adaptability - autonomy - cost compression over time Chips are cheap. Torque isn’t. But paired with the right stack, compute compounds fast. That’s why companies like NVIDIA don’t stop at silicon. They own: - Isaac → simulation tooling - GR00T → foundational control models - Fleet learning loops → systems that get smarter with usage This is the GR00T playbook: Own the model, the data, and the learning loop and suddenly, your 10% of the BOM controls 80% of the product’s differentiation. This is where margin scales like code: - fleet-level learning loops - API-style unit economics - lower per-unit cost over time usage → data → model → autonomy → usage → margin 🧠 Takeaway: low cost + model/data IP = software moat 🧩 Integration creates margin or kills it Hardware margins are brutal - unless you own precision complexity. The question is: are you assembling parts? Or engineering behavior? A company might carry high COGS if it: - makes its own actuators - tunes torque curves for specific behaviors - designs electromechanical systems end-to-end But that’s not just about defensibility, it’s a risk-for-margin tradeoff. Owning this layer means taking on supply chain complexity, firmware tuning, and precision control. But if done right, it can knock 25–50% off costs which is a serious edge for hardware-heavy players. Case study: Unitree’s $16K humanoid Unitree didn’t win only on AI breakthroughs. They won by engineering the BOM: - sourcing actuators locally (cheaper motors) + in house manufactured (no vendor margins) - skipping multi-plane LiDAR (cutting sensor cost) - avoiding radical architecture; just tight control over the stack - co-locating supply chain; 90% of vendors within hours of Hangzhou Here's a high level breakdown of the BOM for Unitree's Quadruped: Western companies often can’t match this - not because of tech gaps, but because they lack supply chain density. That slows iteration and bloats the BOM. 🧠 Takeaway: low BOM + tight integration = speed + margin 💸 Cost ≠ Commodity A low BOM doesn’t guarantee margin. A high BOM doesn’t mean weak strategy. It depends where exactly the cost sits and whether it’s backed by: - model/data flywheels - mechanical IP - tight subsystem integration In commoditized layers, cost savings often just pass through to the buyer. But in leveraged layers, they unlock compounding advantage. 🧠 Takeaway: Cost only matters if it carries leverage 🧬 The invisible BOM matters more What’s not in the BOM is often what defines long-term edge. You won’t find fleet logs, ROS tuning configs, or simulation policies listed, but these layers determine: - autonomy behavior - adaptability in edge cases - learning across robots - margin expansion over time This is the invisible layer: data → model → behavior → more data Whoever owns this loop doesn’t just reduce cost, they also bend the performance curve. 🧠 Takeaway: What’s not in the BOM might define long-term defensibility more than what is. 🗺️ How to read the BOM like a strategy map BOM tells you exactly where leverage lives: - Actuation → high cost, high moat, low margin - Compute → low cost, high leverage, high margin - Comms/frame → low cost, low moat, low margin - Sensors → medium cost, increasingly commoditized So the BOM becomes a proxy for margin profile: - high BOM + high IP → hardware moat (gears, drives) - low BOM + model/data ownership → software moat (GR00T stack) - high BOM + low IP → worst of both worlds (commodity assemblers) As robotics systems will evolve, I feel BOM will offer a uniquely grounded lens to assess technical constraints, economic structure, and strategic leverage of the robotics stack. Thanks to @chynaqqq & @castorhat (PrismaX), @karsenthil, (Reborn), @xmercury_one (Xmaquina DAO), @ivailoj (Paper Ventures), @BlueHors3Shoe (No Limit Holdings), @shutterbugsid (Decentralised Co) for some quick feedback & suggestions on the piece.
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Pendle crossed a huge milestone last week: $1.42 billion in weekly trading volume, the highest ever since our inception.
The majority of this was driven by the May 29th maturity event, where $1.6b in TVL reached maturity. In fact, this maturity event had the best liquidity retention rate of all time. The rest came from users buying PTs and looping collateral across money markets, a testament to the utility and composability of Pendle assets.
Historically, Pendle's maturity events have prompted understandable concerns around TVL retention. Since the launch of Pendle V2, we’ve gone through 27 maturity events, 7 of which involved over $1 billion in maturing TVL. Over the course of the last cycles, what has remained consistently true is this:
a) Pendle works. All of our mechanisms have operated as intended over the years. We’ve successfully processed all PT/LP redemptions,including last year’s $3.8 billion June 2024 event
b) Yes, we’ve seen liquidity outflows post-maturity. Some due to macro headwinds, others tied to shifting narratives. But if there’s one constant in Pendle’s evolution, it’s our ability to constantly adapt to find PMF. From LSTs → LRTs → BTCfi → Stablecoins, the nature of Pendle has allowed us to continuously realign to meet the market where it is.
Looking at the recent maturity events in the past 6 months, I believe that Pendle has reached a new stage of growth, with a reasonable offering as the premier yield marketplace.
The Pencosystem is growing, with PTs being increasingly adopted as a trusted collateral across DeFi money markets, including household names such as Aave, Morpho and Euler. The same foundation and growth path are currently being laid for Pendle LPs as well.
Unlike earlier cycles, TVL retention has become significantly more consistent, even as the scale and frequency of maturity events have grown.
Let’s look at some of the numbers from the recent May 29th maturity:
- $4.79B → $4.23B peak-to-trough dropoff (-11.7%) in TVL
- Within one week, TVL rebounded to $4.45B (just -7% from peak)
- 35% of matured TVL migrated to other Pendle pools within a week, the best 7D retention rate of all time
- $1.15B of PT and $236M of LP redemption processed successfully within a week
- Ethena-linked TVL only saw a -6% dip ($2.8B → $2.6B) after 4 days, and has already rebounded back to $2.73B (h/t @jamesjho_)
Today, over 83% of our TVL is in stablecoins, showing a significant shift from our early days dominated by LST and LRT yield farming. Comparatively, stablecoin yields remain evergreen with their demand persisting through bull and bear markets as a reliable tool for wealth preservation.
Unlike our early LRT days where headline-grabbing yields of 80–120% Fixed APY were the norm, the current range of 3–12% Fixed APY reflects a maturing market - and that’s a good thing.
We’re now seeing more stable, reliable yield flows, underpinned by real demand rather than short-lived, mercenary capital.
This coupled with the shift towards more sustainable liquidity dominated by stablecoins, is ideal for Pendle’s long-term trajectory - all while maintaining the flexibility in pivoting to various narratives on demand. This price discovery of yields is crucial in helping the whole financial ecosystem of the crypto space mature as Pendle transitions into a platform offering DeFi yields to TradFi and institutional investors.
The global fixed income market is one of the largest securities markets in the world, valued at US$140 trillion as of 2023 (Securities Industry and Financial Markets Association). The demand for Fixed Yield products is obvious and continuing to grow, and we believe that stablecoin-denominated PTs are DeFi’s best shot at breaking out into the mainstream.
Job’s not done.
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