Alex Smit

@monad 0x2b7dddebe3a2fe651b2ca4b66939190a7b194a78

Reply to this post with your EVM wallet address for some MON on Monad mainnet. The MON will cover your first few gas fees so you can start using the chain right away. You must be following @monad to receive it.

@Aria_Protocol Nice

If you’ve been with us this year, you’ve seen the momentum 👇 $APL, the first IP RWA token: • $10.95M raised to acquire income-generating music rights • Includes songs performed by Justin Bieber, BLACKPINK & BTS • Distributed $314K+ in royalties • $14M+ in onchain volume

@imtiredofcrypto That banner fits perfectly.

we updated our banner for NovemBEAR. what do you think?

@imtiredofcrypto “Being tired isn’t weakness… it’s clarity.” Damn, that hits.

this is exactly why we’re all so tired tired of liquidations tired of false hopetired of the same cycles but being tired isn’t weakness… it’s clarity

i’m so f*ing tired of this tired of red days that never end tired of trump dumps crushing dreams tired of whale manipulation tired of rugs stealing hope tired of promises that turn to dust been in this space for years and sometimes i wonder why we keep doing this to ourselves but then i remember… being tired is exactly where legends are born maybe it’s time to embrace it maybe it’s time for $TIRED CA: 8AFshqbDiPtFYe8KUNXa4F88DFh8yD8J5MXyeREopump

Traditional prediction platforms lean central to gain speed-but lose true decentralization. @linera_io fixes that with microchains: parallel lanes, instant finality, no compromises.

Imagine running your own microchain on your phone, securely sandboxed by WASM. That’s the Acurast x Linera vision. @acurast @linera_io

@linera_io gmicrochains

gmicrochains ⛓️ The Real‑Time Blockchain meets the Game of Life. Today, we’re launching Linera Testnet Conway, the latest phase of Linera’s public testnet: ultra‑low‑latency microchains + a new points program. Connect your wallet, play the game, and climb the leaderboard 👇🧵

@Kage_Lion @yupp_ai I just used this service for the first time a couple days ago - super convenient.

At first I didn’t plan to write about “AI aggregators,” but since I use @yupp_ai regularly, I decided to share my thoughts on this project. In simple terms, it’s an AI/Web3 platform where one prompt gives you several answers from different models (text/images). You pick the best one, add a short “why,” and that feedback doesn’t disappear - it trains the ranking and slowly tunes your feed. The team claims 700+ models. I didn’t count, but… feels like a lot. How I actually use it: → sanity-check important answers (two models rarely hallucinate in the same way); → quick image drafts without extra apps; → testing new models: “show me how this one explains X”; sometimes new models outperform the “veterans”; → sharing comparisons with friends who ask “which AI should I use?” Credits & rewards (short): you spend credits on “$” models, earn them back with feedback. You can withdraw after a threshold. Not a salary - more like “coffee money” plus free access to strong models if you help the system. Honestly, that’s pretty cool. Notes / Pros: → low entry barrier: free and private by default; → huge variety - you can try top LLMs without juggling a dozen subscriptions; → side-by-side answers reduce “single-model bias”; → clean, fast interface; → honest loop: you help AI improve, the system helps you solve tasks. Who benefits the most: ⇒ newcomers - the safest entry point to AI I’ve seen; ⇒ students/analysts - compare, cite, move on; ⇒ builders - quick drafts before deep testing; ⇒ the curious - those who like double-checking facts before acting. Why it matters: comparison isn’t just convenience. The real scarcity now isn’t “personal data,” it’s human judgment. Platforms that honestly collect diverse “this is better because…” will shape how models evolve. That feels like the most interesting part. Conclusion: for now → is the most painless way to explore a whole range of AIs and keep a clear head. If you’re stuck with one chatbot - try two, you’ll feel the difference. The future is AI. Definitely worth exploring.

@ChristyWri8329 @linera_io Old world jammed, Linera flows.

Humans click slowly. Agents don’t. They fire off thousands of moves an hour. Most chains break under that. @linera_io was built different: microchains, real-time logic, agent-native by design.

@SuzanneMan72778 @linera_io Scalability built-in, not patched.

We’re not building blockchains for yesterday. The future is AI agents, millions of them, moving fast. Old L1s choke on that load. @linera_io brings microchains - instant, agent-native, built for the world that’s coming.

@MelynaSant57324 @linera_io From laggy chains to instant UX.

Binance said it best: most chains weren’t designed for millions of AI agents. They’re right. That’s why @linera_io exists. microchains = low latency, real-time UX, and space for the agentic web to breathe.

@BrenSag28048868 @linera_io Bottlenecks are history now.

@DoroninJohn @linera_io Linera feels like Web3 fast lane.

You wouldn’t run a Formula 1 race on a dirt road. So why run AI agents on yesterday’s chains? @linera_io built microchains for speed: instant UX, infinite scale, real-time reactions.

@H_Jones1989 @linera_io No queues, just smooth flow.

Cross-chain delays. Bottlenecks. Queues. That’s the old world. @linera_io changes the rules with microchains - each user, each agent, their own track. No collisions. No lag. Just flow.

Let’s be real: blockchains today still feel slow, clunky, made for humans clicking buttons. But AI agents won’t wait. @linera_io flips the script with microchains → real-time speed, infinite scale, and native agent support.

@Kage_Lion @gaib_ai Not zero risk, but clear mechanics.

How AID behaves in crypto drawdowns Crypto dumps happen. Red candles everywhere. So the real question: what does AID from @gaib_ai do in a drawdown? I’ll keep it short and honest. Price (peg) - AID targets ≈ $1. If panic hits, price can wobble a bit on DEX, but swaps + arbitrage + KYC redeem (for partners) help pull it back. I just watch peg and slippage, that’s all. Yield (sAID) - sAID ratio grows from off-chain revenue (GPU financing + reserves), not from token printing or #DeFi hype. Market down ≠ income dead. it may slow if compute demand cools, but it doesn’t depend on coin pumps. Liquidity - in red markets depth can get thinner. Plan exits: split orders, keep gas, don’t market dump into tiny pools. Cool-down/timing - unstake isn’t instant. There’s a cooldown window by design, so I plan ahead and avoid panic buttons. real risks - if many rush the door, peg spreads widen; if borrowers delay, cash flow slows; hardware prices can reprice; off-chain ops still matter. Not zero risk, never is. My simple playbook - when market bleeds I park in AID, or stake to sAID if I want the flow. I do a 30-sec check: peg ≈1, pool depth ok, sAID ratio trending up. If those three look fine, I stop overthinking. TL;DR: AID tries to stay stable; sAID keeps earning from real machines, not from market noise. Bad days still happen, but the engine here is compute, not hype.

@Kage_Lion @gaib_ai Collateralized funding shows real trust.

Partners & investors of @gaib_ai. Recently I came across some big news. The project secured backing from major players. In summer 2025, @gaib_ai raised $10M in strategic funding led by Amber Group - one of the leaders in the crypto industry. But this isn’t just a headline number. Part will go to expanding $AID liquidity across networks, so users can move funds freely. Part will go into new GPU deals, because demand for compute is insane. And part will fuel DeFi integrations: PT/YT, lending, swaps, and other useful tools. The investors trust the model enough to put money directly into collateralized assets. And they definitely know what they’re doing. I think they’re betting on AI compute becoming a new asset class of its own.

@Kage_Lion @irys_xyz Huge W for devs, less overhead.

gm, fam 👋 Today I’ll talk about programmable data in @irys_xyz. What I like about this project is that data here isn’t just stored and left idle. Each piece of data can actually carry its own rules. Let me give an example so it’s clearer what I’m talking about: – who can read it, – how long it will be available, – or whether the author gets a cut every time the data is used. Hope that came across clearly. Normally you’d need separate services and tools for this. But with @irys_xyz it’s simpler - the rules are baked directly into the data itself. That’s a huge win for developers: no need to set up access or payments from scratch every time, because the data already knows how it should behave. And that’s just awesome. It might sound simple, but it changes a lot. Instead of asking “how do I control this file,” you just work with the file - and trust the rules inside it.