Today I begin consulting for the pre-launch layer-1 blockchain @linera_io created by @ma2bd. Scalability and usability are the key limiting factors to the growth and mass adoption of blockchain. Linera has a truly innovative approach to solving this problem: ⛓️MICROCHAINS ⛓️

Read the whole article by Nick Ruzicka, head of BD at @linera_io medium.com/@nick.c.ruzicka/p…

🧠 TLDR: Prediction markets are having a moment. Platforms like @Polymarket & @Kalshi are thriving, but liquidity, UX, and resolution issues persist. Builders who fix these bottlenecks could redefine the space. 👇

This is my favorite piece of content to come out of the @linera_io community this week. Might inform something that I've been working on behind the scenes... 👀 Props @best_freetoken

🚨 CRITICAL UPDATE for Buildathon Wave 2+ 🏗️ To keep the judging process fair and focused on real, functional builds, all submissions must now meet the following requirements: ✅ Compile and run successfully ✅ Include a functional Linera contract We’ve also released an official Buildathon Template to make things easier for everyone building locally. 👉 All submissions must either: 1️⃣ Use the Buildathon Template, or 2️⃣ Provide a link to a live demo running against Testnet Conway 🔗 github.com/linera-io/buildat… This update ensures all projects are testable, verifiable, and built on real Linera logic. Keep buildin'. 🧱💪

Predict This! | Community Hour 06.11.25 x.com/i/broadcasts/1ypKdqLgZ…

Buildathon Wave 1 Recap 🏗️ Wave 1 of the Linera Buildathon on @akindo_io is officially complete — and it’s been an incredible start. We received 93 submissions from builders all over the world and selected 22 projects as winners. 🎉 That includes one project originally marked Yellow and one marked Red that our judges felt had been miscategorized after deeper review. A great reminder that real innovation doesn’t always fit neatly into boxes. Overall, the quality and creativity of submissions blew us away — from real-time marketplaces and AI-powered tools to experimental on-chain games. It’s clear builders are already pushing what’s possible with microchains. Looking ahead, future waves will raise the bar. Winning projects will need to: ✅ Compile and run successfully ✅ Include a functional Linera contract We’ll be sharing a submission template soon to make that process easier. Behind the scenes, our team is also refining and improving the evaluation process — filtering out the noise and better identifying the most promising projects. As for rewards: 🏅 1,000 XP has been distributed to all Yellow and Green projects 🧱 Builders of Green projects have earned the Builder role on Discord 🎨 POAPs are coming soon! Wave 1 showed us how much talent, curiosity, and experimentation lives in this community. Thank you to everyone who participated — and stay tuned for Wave 2. We’re just getting started. 💛

Congrats to all the winners!

Buildathon Q&A | Developer Workshop x.com/i/broadcasts/1lDxLBVVa…

Prediction markets have become Web3's mainstream breakthrough. The next frontier is Prediction Market Terminals. Professional traders need data density and execution speed more than discovery. This creates a big opportunity for professional trading terminals, mirroring the memecoin rush. These terminals integrate multiple platforms like Polymarket and Kalshi and justify charging fees by offering a suite of key features: Market Aggregation & Order Routing: A single interface to view odds across all major platforms and route trades to the venue with the best price and lowest fees (@tradefoxai, @fliprbot, @StandDOTtrade). Real-Time News & Data Integration: A live feed of news, social media sentiment, and economic data integrated directly alongside the relevant markets and their impact on a trader's open positions (@VersoTrading, @betmoardotfun, @fireplacegg). Onchain Intelligence: Tools for tracking the flow of smart money, identifying large wallet movements, and analyzing the positions of top traders (@hash_dive, @poly_data, @polyburg). AI Assisted Market and Opportunity Discovery: Utilizing AI to augment and improve a trader's decision making process (@polyfactual, @polymtrade, @Polysights) or utilizing agents to help users passively participate in prediction markets (@polytraderAI, @rainmakerdotfun). Advanced Risk Management and Order Types: Tools that allow users to model complex scenarios and utilize order types such as TWAPs and trailing stop losses for professional traders. Third Party Leverage: Offering leverage on selective high volume markets with their custom liquidation engines. These terminals serve the power users driving the most volume in prediction markets.

AI has totally changed what it means to “build” — and what it means to judge those builds. We got 93 submissions for Wave 1 of the "Don't Be Late. Be Real-Time" Buildathon with @akindo_io. Some are genuinely creative, functional apps built to run on microchains. Others… let’s just say, were clearly AI-generated filler. Our small review team — 2 of us from marketing and 5 engineers — spent the last few days sorting everything into three rough buckets: 🔴 Not Ready 🟡 Meets Minimum 🟢 Promising That first pass wasn’t about perfection. It was just about finding signal in the noise — figuring out which projects actually deserved a closer look. Now our engineers are digging through the 🟢 projects to pick the winners for Wave 1, which we’ll announce Monday. It’s been slower (and harder) than we expected. As our Head of Protocol put it: "It's now extremely fast, cheap and easy to produce tons of test, code, and even good-looking app prototypes. But it's extremely time-consuming, expensive and hard to distinguish pure generated content from honest work." He’s right. Some people clearly spent days or weeks coding, debugging, and testing. Others are just really good at prompting AI to make it look like they did. And that’s okay — we’re not against using AI. It’s an incredible tool. What matters is whether a human actually looked through the output, fixed things, made decisions, and understood what they were building. That’s the line between AI-assisted and AI-produced. We also know this process isn’t perfect. With 93 projects, we’re bound to misjudge a few. Some great builds might get missed; others might get more credit than they should. We’re sorry for that. That’s why everyone gets something — and the biggest rewards go to the people who clearly put in real, sustained effort. (See chart below 👇) If anything, this Buildathon has made one thing clear: building — and judging — in the age of AI isn’t about how much you made. It’s about how real it is. We’re learning right alongside you. 💛

Linera's Getting Spicy | Community Hour 30.10.25 x.com/i/broadcasts/1OdJrONAn…

gmicrochains and gspice! We’re thrilled to share our latest partnership with @spicenet Together we enable real-time composable execution: Linera microchains + Spicenet’s brokerage network for fast cross-chain performance Full announcement: linera.io/xspicenet More 🧵👇

We got 93 submissions for the Linera Buildathon in Wave 1. Can't wait to dig in...

The real time predictions market holy grail is not necessarily on the betting side (which of course is required) but in how the data is used. In the future, every competitive endeavor is going to have a percent likelihood of success on screen in real time at all times.

Top 5 Prediction Market Ideas from @a16z 10² Hackathon Just a couple of weeks ago, @calblockchain hosted the 10² Hackathon - with Prediction Markets as one of the main tracks, sponsored by @Polymarket and @eigenlayer among others. I took some time to dive deeper into the projects and select the five that stood out to me the most. I’m not sure if these teams plan to turn them into real startups, but the creativity and depth here are worth sharing. 1. Borrowing Against Your Basket of Predictions The beauty of this idea is that you can collateralize all of your positions together as a basket decreasing the risk of liquidation on any single position. It introduces a global lending pool where users can deposit liquidity for yield, while Polymarket traders can borrow USDC against their Polymarket YES/NO tokens, with health factors and collateral values computed off-chain through EigenCompute and verified on-chain via Trusted Execution Environments (TEEs). Source: devpost.com/software/polylen… 2. Enterprise Hedging with Prediction Markets What if companies could use prediction markets to hedge political or economic risks - like tariffs, regulations, or geopolitical shocks? This project turns uncertain, event-driven risks into fixed, budgetable costs using correlated Polymarket events. A CFO can define a risk (e.g., “$10M loss if a chip tariff passes”), and the platform constructs a synthetic hedge using correlated markets connected through a Bayesian dependency graph, dynamically adjusting exposure as probabilities shift. All execution and pricing logic run inside EigenLayer Trusted Execution Environments (TEEs) for verifiable computation and data integrity. The result is a decentralized, automated certainty-as-a-service layer turning chaotic futures into predictable expenses. Source: devpost.com/software/polyhed… 3. Bayesian Arbitrage Vault for Cross-Event Mispricings Think of this as an on-chain hedge fund for event arbitrage. A Bayesian engine maps connections between mostly uncorrelated Polymarket events, assigns confidence weights to each relationship, and continuously scans for brief moments when model-implied odds diverge from live market prices. When a mismatch meets latency, slippage, and liquidity guardrails, it executes a trade - all verifiably logged and attested so depositors can audit the math. The result is a trust-minimized arbitrage pool that identifies deeper, slower-to-correct inefficiencies - uncovering structural alpha in prediction markets. Source: devpost.com/software/ruckus-… 4. Finding Hidden Links Across Prediction Market Events Prediction markets are often siloed - one market for elections, another for macro events, another for crypto. This system connects them. Traders can map price correlations, estimate conditional or joint probabilities, and spot sentiment spillovers (e.g., how a tariff market ripples into semiconductor or election odds). Under the hood: Pearson correlation, time-series normalization, linear regression for first-order links, and embedding-based clustering to de-duplicate near-identical markets. Basically, it helps traders see the bigger picture - where probabilities interact across seemingly unrelated events for hedging, portfolio construction, and structured bets. Source: devpost.com/software/posteri… 5. Stock Insights Powered by Prediction Market Data This idea connects traditional finance with prediction markets - letting AI analyze how Polymarket probabilities could move real-world stocks. The system reads financial news, market spreads, and sentiment data to produce short, evidence-based outlooks on stock performance. It acts like a prediction-market-aware Bloomberg feed - making professional-grade financial reasoning accessible to traders, analysts, and retail investors alike. Source: devpost.com/software/stockbo… The beauty of prediction markets is that they aren’t fully dependent on crypto cycles. We might finally be seeing a sector that grows independently of market moods. With rising open interest and volume, expect more builders to choose this space as their playground. If anyone’s working on these ideas - tag them below. Early as always 🤝

Is this the greatest World Series game ever?

MEEB FORCE ONE over the Vegas Strip.

Picked this guy up a few months ago. Been investing in the space since 2013, and now excited to join one of crypto's most impactful communities. gm!

Life is #COMPLEX

Buildathon is live | Community Hour 23.10.25 x.com/i/broadcasts/1OdKrOYQm…