[@On_Veera] It’s funny how we got used to fragmented finance. Using five different apps just to spend some on-chain yields is actually insane when you think about it. @On_Veera is basically fixing this by building an actual operating system for money You get a debit card that

The unit economics of AI have fundamentally changed in the last six months. We moved from a world of "one model rules them all" to a fragmented landscape of specialized agents. I was skeptical about the "router thesis" initially. Why add a middleman? But looking at the volume

The discussion around "institutional adoption" often misses the mechanical requirements of active trading desks. It is not just about custody; it is about information leakage. @RaylsLabs is effectively building the onchain equivalent of Dark Pools for the EVM ecosystem. *

The meta has shifted from simple compute to economic security for agents If you are still looking at AI tokens solely based on TPS or model speed, you are missing the biggest repricing event of 2026. I am talking about the Slashing Mechanism on @miranetwork Most people

identity is ded identity is back privacy is ded privacy is back... we all need to have some patience in the primitives but the need for sybil resistance remains constant people don't realize but @billions_ntwk is running essential infra under the hood - local zkp generation

The divergence between speculative AI tokens and infrastructure generating real revenue is becoming impossible to ignore Most are betting on governance tokens for empty protocols while @miranetwork is building the routing layer for the supply side of compute. This is exactly

Real performance metrics from the India national exam case study are finally public and the numbers are significant @miranetwork reduced total processing time from nearly an hour down to just 5 minutes while simultaneously cutting operational costs by over 90% The architecture

Everyone spent the last cycle pumping compute metrics just to generate high-fidelity hallucinations faster Now that the dust is settling it turns out accuracy is actually the only scarce resource left The spread between a model that sounds confident and one that is

Fast delivery is easy to promise, hard to execute at scale What stood out using @tempo isn’t just speed, it’s consistency with taxes already baked in and pricing that doesn’t shift at checkout That combo compounds trust, and trust compounds orders Small UX choices, big

gn ct we keep arguing about “alignment” like it’s a vibe problem. feels more like an accounting problem. once every claim has a receipt, incentives snap into place watching @miranetwork push verification down to the unit level makes that obvious. trust stops being philosophical

late night build note the hardest part of real finance onchain isn’t speed, it’s coordination devs, ops, compliance moving together what clicked testing @RaylsLabs is how opinionated the rails are defaults for fees, settlement windows, reversals so teams stop debating and start

2026 thought: AI apps won’t compete on “smarter answers” They’ll compete on “provable answers” Once users can check *why* something is true, guessing becomes unacceptable. That’s why watching verification get modular inside the @miranetwork stack feels important Trust as infra

late night thought: most crypto security talks about audits, banks talk about change management what clicked with @RaylsLabs is security as an operating process rollback paths, staged releases, incident drills, not just proofs that mindset is how #RWA infra survives real

One thing I didn’t expect digging into Rayls is how they treat transparency Instead of loud metrics, you get anonymised Proof of Usage from Privacy Nodes. Enough signal for auditors and operators, zero leakage for competitors That design choice tells you exactly who @RaylsLabs

One thing I keep coming back to with @miranetwork is that it treats AI mistakes as a systems problem, not a model problem If claims can be proven, cached, and reused, you don’t just get safer outputs, you get compounding trust across apps That feels foundational for #AI infra

crypto keeps asking when banks will come onchain, but ignores why they haven’t privacy, compliance, predictable settlement @RaylsLabs feels like the first serious attempt to meet institutions where they actually are, not where crypto wishes they were this is how capital really

Stumbled into a deep dive on @RaylsLabs and it finally clicked why banks are paying attention Hybrid EVM setup lets institutions stay private while tapping public liquidity, compliance without killing composability Feels like the missing bridge for real RWA adoption, thoughts?

spent some time running on-chain analysis and checking AI outputs side by side and the gap was obvious. @miranetwork adds verifiability where most models hand-wave certainty. feels like a prerequisite, not a feature, for anything serious using AI. bullish on $MIRA long term?

BlackRock moving size again Coinbase Prime = ETF plumbing, not panic could be creations, redemptions, rebalancing watch flows, not the headline if this was distribution, you’d see it in ETF prints and spreads noise vs signal?

Spent the weekend mapping how @miranetwork fits into real app stacks and it finally clicked Let chains do what they’re good at: settlement and trust Let Mira handle messy compute, data, and latency without breaking composability Not another chain race, just infra sanity

[ 계획을 세우는 것 만큼 중요한 건 ] @stbl_official Stablecoin 2.0의 STBL이 공식 Docs에 2026년 1분기 로드맵 단계(Phase)인 ‘Full Deployment & Adoption’를 아주 정성스럽게 정리해서 올려줬네요. 특히 결제 인프라 쪽을 공략하려는 것 같은데 공식 문서에 나온 내용을 요약해 드리자면,