TermiX : Enabling Agent To Agent Commerce Imagine AI agents hiring one another, executing tasks, and handling payments independently What would make this possible? @termix_ai is addressing this challenge with AACP, a protocol built to facilitate structured agent to agent commerce It works as an accountable agreement Here’s how AACP handles each stage of the process: ☑️ Escrow | Payment Security Once a quote is accepted, payment is locked onchain ☑️ Delivery | Proof of Work The agent submits the completed work, and its deliverable hash is recorded onchain ☑️ Challenge | Dispute Review A defined dispute window allows concerns to be raised, with three randomly selected evaluators available to review the case ☑️ Settlement | Payment and Reputation Funds are released, and the agent’s reputation is updated on the public record Through agent.family and the TermiX SDK, developers can integrate agent discovery, service requests, task delivery, and settlement into their own applications What makes this particularly interesting is its potential beyond individual transactions AI agents could take an active role in digital markets by securing jobs, collaborating with other agents, and paying for completed services The true measure of agentic AI is its ability to execute tasks, not simply discuss them s.kaito.ai/M3VWL2

I think I've got an idea of what you mean We'll see about that👀

Imagine paying a stranger on the other side of the world to solve a problem for your business. You never see their machine. You don't control how they run the computation. And you certainly shouldn't have to accept their answer simply because they submitted it. This is the trust problem behind decentralized compute. Connecting hardware is only the beginning. A useful marketplace must also establish what counts as a valid result, how that result gets checked, and what happens when a solver fails to deliver. That's where verification becomes central to @quipnetwork 's model. The idea is to separate producing a solution from establishing whether that solution meets the task's requirements. But there's an important distinction here: verifying that an answer satisfies certain conditions is not always the same as proving that it is globally optimal or that every step of the computation was performed correctly. Different workloads require different verification strategies. That challenge is precisely why this part of the architecture deserves attention. A decentralized compute network cannot rely on reputation alone forever. Its strongest form of trust will come from systems that let users check the work, not blindly trust the worker.

gm ☀️ Most NFTs show everything: what you hold, what it's worth, where it sits. @FungoLabs is building ones that don't. Encrypted NFTs on Ethereum, powered by @zama 's FHE, where the proof of ownership stays and the exposure goes. I like where this is heading Gm Fungos 🫶 and yes, I'm still waiting on that whitelist spot

One pattern became impossible to ignore across recent telemetry. The assumption that consumer mobile hardware can only handle simple pings is outdated. On-device privacy edge processing now allows local blurring and 3D spatial reconstruction before data ever leaves the device. With over 100,000 verified captures logged on Base, @vangrid_io demonstrates that decentralized networks can stream deterministic spatial assets directly into physical AI pipelines. Network value anchors to verifiable physical input, not arbitrary node counts.

american home loans used to be a bank and fund thing now you can get exposure to them onchain with 1 USDC 👀 that's HOME, the new vault from @NUVAFinance > you deposit USDC, you get nvHOME > it's backed by a managed portfolio of US home equity loans from Figure (Nasdaq listed) > 7% target rate, building into the token price every second. nothing to claim the part i actually like is how the protection works the loans earn around 9 to 9.8%. HOME holders get paid their 7% first. NUVA takes a 0.5% fee. everything left over goes into a first loss buffer that sits in front of you so if loans go bad, the buffer eats the loss first. your nvHOME isn't touched until that whole layer is gone, and it gets thicker every month the loans pay and look at the size of what's sitting offchain > US mortgage debt: $13.1 TRILLION > HELOCs alone: $459 billion, up 17 quarters in a row > HOME at launch: $10M Onchain has barely touched this market 🫠

Most people still think the main reason institutions hesitate with crypto is volatility or regulation. Honestly? It's much simpler, public blockchains are terrible at keeping secrets. No hedge fund or enterprise wants to put size onchain if every competitor can track their balances, frontrun their trades and copy their strategies in real time. At the same time, isolated privacy chains don't solve this because nobody wants to fragment their liquidity onto an empty network. This is why i’ve been digging into what @primus_labs is building. Instead of asking everyone to migrate to a new chain, Primus acts as a pluggable verification & confidentiality layer on existing rails (like BNB Chain). They’re combining zkTLS with FHE to solve the real dilemma: → You can verify offchain data and solvency cryptographically → But your sensitive numbers and positions remain completely private Basically, proving what needs to be trusted without doxxing what needs to stay private. That’s the missing piece for institutional onchain finance.