b2b

How $KITE works from the foundation up
I’m going to try and tell this like a story because that’s how I first made sense of it myself, and they’re building something that reads like an answer to a handful of real, everyday frictions rather than a pure technology thought experiment, so imagine a world where autonomous software — not just humans clicking buttons but programs that decide and transact — needs a way to act that’s accountable, auditable, and predictable, and Kite is designed to be that scaffolding, starting with a Layer 1, #EVM -compatible blockchain that’s optimized for real-time agent coordination and then layering identity and governance around it so agents can transact with a verifiable persona and the rules they follow are programmable and observable; from the foundation up that means the team chose an #EVM M -compatible base because interoperability matters — they’re not inventing a new virtual machine which would fracture tooling and developer mindshare, instead they’re enabling familiar smart contract patterns, wallets, and dev tooling to operate while tuning consensus, mempool, and gas logic for lower-latency, high-throughput interactions that you’d need if autonomous agents are to coordinate often and fast, and the three-layer identity model — separating users, agents, and sessions — is the key conceptual move that realigns responsibility and capability in a way that feels more human-centered, because it acknowledges that identity is not one monolith but a set of roles and temporal contexts where someone’s long-term profile (user), their delegated actor (agent), and a particular interaction slice (session) may each need different privileges, revocation rules, and observability.
If you walk through the system step by step you start at the #L1 where consensus and transaction execution are optimized for short finality and predictable latency so that an agent can make a decision, commit a payment, and move to the next task without waiting minutes, and they’ve paired that with #EVM compatibility so smart contracts, wallets, and developers feel at home, then on top of that sits the identity layer which issues attestations and cryptographic bindings that tie an agent to a user in a verifiable way while also allowing sessions — temporary cryptographic channels that can be created, delegated, and revoked quickly — so you don’t have to expose a user’s full authority every time an agent acts; the next layer is governance and token utility where $KITE starts modest, powering participation and incentives to bootstrap network activity, and then phases into staking, governance rights, and fee functions once the network has matured, meaning the economic levers are staged to reduce early centralization pressure and let governance mechanisms be shaped by actual users and agents as they appear in the wild, and around all this are the developer and runtime tools that enable agents to register intents, negotiate state, settle payments, and resolve disputes through on-chain arbitrable contracts and off-chain oracles when needed, which is how the whole experience becomes cohesive rather than a bag of isolated features.
I’ve noticed that the problem Kite is trying to solve is not simply “let agents pay” but rather “let agents act in ways that we can trust, govern, and recover from,” because agents open new threat models: economic actors that can automate gaming behaviors, temporary sessions that if compromised could cause cascade losses, and identity gaps where it’s hard to tell whether an action came from a human or an unattended algorithm; the three-layer identity system solves several of these at once by allowing different verification and penalty policies depending on whether it’s a long-term user identity, an agent delegated to act on their behalf, or a short-lived session for a single task, so you can, for example, require higher collateral or stricter on-chain attestations for long-lived agent contracts but allow lightweight sessions for routine micro-payments, and that design choice ripples through user experience, economics, and risk management in ways that matter more than flashy throughput numbers because it creates practical recovery paths and places where human oversight can re-enter the loop.
From a technical choices standpoint, a few decisions truly matter and explain the network’s behavior in practice: #EVM compatibility lowers the barrier for adoption and lets existing tooling plug in, but if they optimize gas metering, mempool ordering, and block times for agentic flows they change the economics of small, frequent payments which is critical to making agent-to-agent micropayments feasible without grinding the chain to a halt, and the identity-attestation architecture is a second big choice because it trades off centralization for verifiability — you need reliable attestation sources and a way to manage key revocation that doesn’t hinge on a single oracle or authority, so they’re likely to lean on decentralized attestation schemes or multi-party attestors which reduces single points of failure but raises complexity, and finally the staged token utility — starting with participation and incentives before switching on staking and governance — alters early distribution dynamics and is meant to avoid too-early concentration of governance while still rewarding builders and early actors; those three axes — execution performance, identity design, and token economics sequencing — are what determine both the day-to-day user experience and the systemic characteristics like decentralization, resilience, and the cost of mistakes.
When you ask what metrics to watch and what those numbers actually mean in practice I’m more interested in a few human-centric signals rather than raw benchmarks, even though both matter: watch throughput (transactions per second) and finality time together — #TPS tells you capacity and finality time tells you decision latency, and for agents you want modestly high TPS with sub-second to few-seconds finality depending on the use case because if your agent waits tens of seconds to proceed it breaks flow, so those numbers directly map to user experience; watch median and tail latency because agents are sensitive to the worst-case delays more than the average, and if you’re seeing long tails you’re going to have brittle agent logic that either stalls or makes unsafe fallbacks. On the economic side watch active agent count, session creation rates, and on-chain attestations — these are usage proxies that show whether real delegations are happening versus synthetic test traffic — and also keep an eye on token distribution metrics (what percentage of $KITE is in early team/treasury hands vs circulating supply), staking participation rates once staking is enabled, and governance turnout percentages because they tell you whether decisions will be broadly representative or controlled by a few large holders; lastly, watch security metrics like number of slashing events, incidents of identity compromise, and oracle divergence incidents — those aren’t vanity numbers, they’re the places where real users lose faith, and they’re the things that force emergent, sometimes ad-hoc responses that become precedent.
There are real structural risks and weaknesses here without exaggeration: identity systems create privacy trade-offs, because verifiable identity means data that could be correlated across sessions unless privacy-preserving attestations are used, and if privacy is mishandled agents meant to operate on behalf of users might leak behavioral or financial information that could be weaponized, so they need selective disclosure and zero-knowledge style primitives or strong legal/operational safeguards to avoid that. There’s also the risk of Sybil or collusion attacks in agent economies where automated agents spin up to vote in governance or to manipulate incentives; even with staking or slashing, automation allows an attacker to iterate strategies quickly, so governance design needs to account for automated coordination and include rate limits, identity-linked quotas, or reputational weightings that are robust to cheap automation. Smart contract bugs and economic design flaws are another class of risk: agents will compose contracts rapidly and at scale, and a single economic exploit that drains collateral or manipulates a session protocol can cascade through agent networks, so formal verification, bounty programs, and layered fallbacks are more than checkbox security—they’re insurance for a new class of emergent behaviors. There are also regulatory and compliance risks: if agents act with delegated authority to move value, regulators may ask who is responsible when things go wrong, and the three-layer identity system helps clarify that responsibility but may also make the network a target for regulatory scrutiny if it’s seen as enabling automated, opaque transfers, so they’ll need clear on-chain audit trails and a governance posture that can engage with legal frameworks. Finally, centralization of token holdings or attestation services is a practical weakness because if a handful of entities control attestations or a large fraction of tokens, they can distort governance or censor agents, and this is one of those slow-burning risks that looks fine early on but becomes a structural problem when usage scales.
If it becomes successful, we’re seeing two plausible macro trajectories and both feel realistic: in a slow-growth scenario Kite grows methodically as developers experiment with agentic money for narrow verticals — think subscription management, automated supply chain micro-payments, or in-app agent assistants that manage small budgets — adoption remains developer-led and mostly #B2B , staking and governance activate gradually, and the network’s economic design is refined through low-impact incidents and community processes; this path means the network has time to mature, governance norms to develop, and privacy-preserving features to be iterated with careful community input, but it also means slower value capture for early token holders and a longer runway to product-market fit because agents require real-world integrations to matter. In a fast-adoption scenario the network finds a killer integration — perhaps autonomous marketplaces where agents negotiate service-level microcontracts or large platforms adopt the session model to delegate routine tasks to on-chain agents — and usage explodes, leading to high TPS demand and an early move to full economic utility of KITE where staking, fee capture, and governance matter rapidly; this accelerates liquidity and network effects but also stresses identity and oracle systems, exposing scaling and security risks sooner, and the team’s ability to respond decisively and transparently to incidents becomes the hinge on whether growth is sustainable or ends up concentrated and brittle. Both scenarios share a common theme: governance and the ability to evolve protocol rules rapidly but responsibly are central to healthy outcomes because agentic payments introduce novel dynamics that no static token model can fully anticipate.

I’ve noticed in conversations with others building similar tech that the social layer — how humans interpret and police agent behavior — is equally important as the code, because agents will do what they’re allowed to and sometimes what they’re incentivized to do even when those actions don’t align with human expectations, so systems that make agent decisions observable, explainable, and reversible in practice are the ones that get trust first, and Kite’s session revocation and layered identity approach are the right kinds of primitives to support those human remedies if they’re implemented with real-world usability in mind, for instance clear user dashboards showing active agent sessions, easy keys for revocation, and dispute-resolution flows that non-expert users can follow.

On the economical front, keep an eye on how incentives are distributed during the early participation phase because incentives that are too generous to early liquidity providers can lock the protocol into unsustainable subsidy cycles, whereas incentives that’re too stingy slow adoption and leave useful network effects unrealized; the staged roll-out of token utility is a thoughtful attempt to balance these trade-offs, but it’s not automatic — the community and core contributors will need to calibrate rewards, staking yields, and governance rewards to avoid perverse outcomes while still motivating builders. There’s also a UX element that often gets underestimated: identity management must be frictionless enough that ordinary users can delegate tasks to agents without security fatigue, and that requires careful wallet integration, clear visuals for session scopes, and sensible defaults that protect novices while letting power users compose complex delegations.
We’re also going to need robust monitoring and incident-response primitives baked into the protocol: think on-chain signals that automatically flag anomalous session behavior, automated rate limiting for suspicious agent actions, and community escrow mechanisms that can temporarily pause funds while disputes are adjudicated; these are not glamorous, but they’re the sort of practical engineering that prevents a single exploit from becoming an existential crisis and that ultimately determines whether real people will trust agents with money. In terms of developer ergonomics, SDKs that make it simple to create, register, and revoke agent sessions, along with testing sandboxes that simulate real-world adversarial conditions, are what will take Kite from an interesting technical architecture to a platform that teams bet production workloads on, and I’m always surprised how often projects underestimate integration friction even with good architecture, which is why the human-centered tooling is as important as consensus speed.
There are also subtle emergent considerations about market design: if agents become capable of micro-arbitrage at machine speed, then fee and ordering mechanisms matter a lot because they determine whether the network rewards productive coordination or pays out to opportunistic, low-value automation that extracts rent, and that’s why gas rules, incentives for off-chain batching, and fee-discount structures for verified sessions all deserve careful thought, because small changes in micro-incentives compound into very different macro behaviors. We should not pretend these are easy problems, but I’m encouraged by architectures that treat governance, identity, and economics as first-class citizens rather than afterthoughts because they naturally give the community levers to iterate when real-world behavior exposes design blind spots.
If you’re trying to decide whether to watch this space closely, watch those human-facing metrics I mentioned earlier, and watch whether the project publishes clear operational playbooks for incident response, identity attestation rotation, and governance emergency measures; those process artifacts are often better predictors of long-term success than early marketing or followership because they show whether a team anticipates the messy realities of real money and real agents operating in the world. And finally, if you’re imagining what a mature Kite ecosystem looks like, picture a fabric where people delegate routine financial chores to assistant agents that can be audited and constrained, where marketplaces of agent skills negotiate on behalf of users with transparent reputations, where disputes can be opened and resolved with minimal human toil, and where tokenized governance gradually hands control to a broad community that cares about safety and utility in equal measure — that’s the slow-and-sure ideal, and the fast-adoption world looks similar but compressed in time, with larger, earlier stress tests that force primitives to harden quickly.
I’ve noticed that when technologies touch money, they stop being games and start being citizens’ infrastructure, and that’s why Kite’s grounding in identity, staged token utility, and EVM compatibility matters in practical, human ways: it’s neither purely an engineering feat nor purely a financial experiment, it’s an attempt to let machines be intentional actors that we can still hold to account, and if they get the balance right between usability, privacy, and accountable governance then we’ll have a new kind of plumbing that makes many everyday digital interactions smoother without turning control over to opaque systems; if they get it wrong, we’ll learn important lessons about how delegation and automation interact with incentives and law. So whether you’re a developer, an operator, or someone who simply wonders what happens when software can pay for things on your behalf, I’m struck by how much the eventual outcome will depend less on flashy throughput numbers and more on trust-building primitives, clear recovery mechanics, and an active, engaged community that prioritizes safety alongside growth, and I’m quietly hopeful that with careful design, thoughtful governance, and a steady focus on real-world problems rather than hype, the Kite model can make agentic payments an ordinary convenience rather than a hazardous novelty, leaving us a little more time to think and a little less time babysitting routine tasks.

1. China is testing stablecoins with concerns about capital outflows.
China is seeking to introduce stablecoins as part of its efforts to internationalize its national currency (the renminbi) and challenge the dominance of the US dollar (Financial Times).
Legislation has been enacted in Hong Kong allowing licensed companies to issue digital tokens backed by traditional currency, but authorities are taking a cautious approach by limiting and gradually granting licenses, tightening controls to reduce risks of money laundering and capital flight (Financial Times).

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𝗢𝗿𝗶𝗴𝗶𝗻𝘀 𝗼𝗳 𝗕𝘂𝗯𝗯𝗹𝗲𝗺𝗮𝗽𝘀
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𝗛𝗼𝘄 𝗕𝘂𝗯𝗯𝗹𝗲𝗺𝗮𝗽𝘀 𝗪𝗼𝗿𝗸𝘀
The system scans blockchain data to identify token-holding wallets and their transactional relationships. Each bubble on the map represents a wallet address, with its size reflecting the number of tokens it holds. The lines connecting the bubbles showcase transactions between wallets, while clusters and color coding reveal potential links between groups of wallets. For example, a massive central bubble connected to many smaller ones may represent a treasury or exchange wallet, while a group of equally sized wallets consistently trading could point to a dev team or possible Sybil attack.
𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀
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𝗧𝗵𝗲 $𝗕𝗠𝗧 𝗧𝗼𝗸𝗲𝗻 𝗨𝘁𝗶𝗹𝗶𝘁𝘆
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𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗮𝗻𝗱 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀
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𝗧𝗵𝗲 𝗩𝗶𝘀𝗶𝗼𝗻
In a crypto world plagued by rug pulls and hidden manipulation, Bubblemaps stands as a beacon of clarity. Its greatest strength lies in its simplicity: even new users can understand the risks and opportunities within token supply. If adopted widely, Bubblemaps could become the Web3 equivalent of a credit rating system—an essential pre-investment check that builds trust, empowers communities, and makes transparency the norm.
♡𝐥𝐢𝐤𝐞💬 ➤ @Bubblemaps.io #Bubblemaps $BMT

#TradingTypes101 One of the main problems faced by

YouTubers, freelancers, and traders in

Yemen and other countries have a problem with withdrawing profits from the internet.

and this is of course due to some restrictions and bans ❌ on
financial transfers. Many young people

worked on sites for several weeks and gathered

respectable amounts, but unfortunately in the end, they are surprised.