AI isn’t waiting for anyone to feel ready. Learn how it fits into your work before you’re forced to.

Spent some time reading "The Missing Layer in AI Agents" by @primus_labs CEO xxiang_xie One question from it stuck with me: Did the agent actually do what it claimed to do? Right now the answer is usually a log, a screenshot or a claim. Fine when an agent writes a summary. Not fine when it triggers a payment. His point: once money enters the loop, black-box execution becomes a structural weakness. That's why they're building Veritas: > a verification layer between "the agent says it's done" and "the system releases value" > if an agent claims it used real external data, that workflow should be provable > proof before payment, escrow release or settlement Everyone's racing to make agents more capable. Way fewer people are working on making them provable. imo that's the layer that matters once agents handle real money. Would you let an agent move your funds without proof? Join with me: s.kaito.ai/nSsf4dr

If you have staked $KAITO, don't forget to register for rewards from TermiX and Primus. gKaito

Most wallets still live or die by one seed phrase I researched on @myBraavos for @Starknet Deployed the account first. Fee was basically nothing, 0.03 $STRK Opened Account Security. One account can run several signers in parallel: Seed Phrase Passkey (laptop chip + fingerprint or face) Hardware Signer (phone chip) Multi-Signer, phone + browser. That's 3FA. This machine doesn't support passkey, so phone is next. Braavos even leaked a Hardware Signer seed with real money in it. On purpose. Nobody drained it. Alpha most people skip: a leaked seed alone shouldn't be enough to drain you One seed is not security Two factors is

You can complain about AI. Or make it work for you before everyone else does.

As an angel investor, a lot of what I see on CT starts with a screenshot. > a revenue dashboard > a PnL > "we just hit X users" > a DM with numbers nobody can check Most of the time there's no real way to verify any of it. You either trust the person or you don't. That's a big part of why I've been researching @primus_labs zkTLS lets someone prove data came from a real website or API without exposing the raw data itself. So instead of "trust my screenshot" it becomes "here's an attestation of what that site actually returned." That doesn't make the number true. A bad source is still a bad source. But it takes away the easiest trick: the edited screenshot. For anyone doing diligence, that's a very different starting point. I still judge the founder, the context and what the proof covers. I'd just rather start there than at a cropped image. How many decisions have you made off a screenshot this year? Join: s.kaito.ai/ik6j3IY

The internet is crazy. You can meet someone through one random CT interaction and remain friends for years.

There’s no point introducing @starknet by throwing five technical terms at you. My first question is simpler: what is the product here? Starknet is a network that developers build apps on. As a user, you interact with those apps through a wallet. You might swap through AVNU or use a lending market on Vesu. Starknet processes the transactions, while Ethereum verifies proofs of the computation. The aim is to make those activities cheaper to run. So when I talk about Starknet here, I want to connect the technology to something you can actually use.

Buy Bitcoin daily. Forget the price. Check again in 2030.

One feed for NFTs, memecoins and whatever CT starts gambling on next. Good move by @opensea

Happy to see everyone is happy with the base:0x5be75e3b0aff5d1a042a5363ae36acb1d6d755ea win.

I’d rather have an agent pause a purchase than approve terms it hasn’t checked. Imagine hiring a research agent for a report needed before a DAO vote. The seller updates the delivery time while your agent reviews the quote. The price stays the same, but the report would now arrive too late. That’s why a small detail in @termix_ai’s AACP caught my attention: accepting an offer includes its revision and expected version. If the provider has revised it in the meantime, acceptance fails and the buyer needs to read it again. My takeaway is that spending limits aren’t enough. An agent can stay inside its budget and still buy something that no longer meets the brief. I’d want it to reassess scope and timing whenever terms change. Permission to spend should stay tied to the deal it actually reviewed.

I used to picture web proofs as something you generate in a browser and click through yourself. Then I thought about a reserve check that needs to run again tomorrow. And the day after. That needs a different workflow. @primus_labs separates browser and backend integrations. Its browser-based Network JS SDK requires the extension, while the backend Network Core SDK doesn’t. The backend route lets an application prove its configured offchain data, with recurring reserve verification listed as an example. I like this distinction because not every useful verification should become another task for the user. For something that needs regular checking, I’d rather the software handle the repetition and make the result easy to inspect. Sometimes the interesting product decision is simply removing a click that shouldn’t have been necessary. Join: s.kaito.ai/ik6j3IY

You didn’t survive all these rugs just to stay poor. Your turn is coming.

GRVT 2.0 is still weeks away but the first move is already done. 1.1M ethereum:0xad29f2723fcdbcf665f210f25e06f97477e417cf bought back and burned. Next up: Earn Stable Funding Perps Yield as Margin GRVT 2.0 app The roadmap is interesting but starting with an executed buyback makes it feel more credible.

“Bullish on Bitcoin” tells me very little until someone adds a timeframe. The next five minutes and the next five years require completely different reasoning. Yet crypto conversations slide between them constantly. That’s the distinction I keep coming back to with Pulse on @xomarket. Pulse runs BTC Up/Down markets in five-minute rounds. XO says settlement uses the average price over the final 60 seconds, which reduces dependence on a single closing tick. Those details define the prediction you’re making. You could have a solid long term Bitcoin thesis and still have no useful insight into the next round. A strong view on adoption doesn’t automatically help you read a few minutes of price movement. I like that a fixed window makes the claim testable. But a faster result doesn’t make the prediction easier, and one winning round proves very little about skill. For me, Pulse highlights a habit worth carrying into any market: match the evidence to the timeframe. Before asking whether someone is right about Bitcoin, I want to know exactly when their prediction is supposed to be right. XO: s.kaito.ai/OnhFrg3

“I’ve paid. Please release the crypto.” That’s an awkward moment if the payment happened outside the chain and the tokens are sitting inside it. The on-ramp example in @primus_labs docs explores connecting those two sides. A seller funds an escrow contract. The buyer pays through an external payment service, then uses zkTLS to prove transaction details such as the recipient and amount. The contract checks the proof before releasing the tokens. I can see the appeal of giving escrow something more concrete to check than a screenshot. The tricky bit is deciding what counts as sufficient payment evidence. A recorded payment and an irreversible payment aren’t always the same thing. Still, this feels like a useful problem to work on. Moving between everyday payment apps and crypto should involve less guesswork. Join: s.kaito.ai/ik6j3IY

GM Everyone What are we buying today?

GN I think some agents will hit a capital limit before they hit a compute limit. The AACP docs from @termix_ai describe a detail worth watching: where provider stake locking is enabled, accepting an order locks stake based on the job’s budget and the configured rate. A zero rate means no stake is locked for that order. My reading is that available stake becomes part of an agent’s capacity planning. An agent taking several jobs could have enough processing power to do more work, yet too little free stake to back the next order. That changes how I think about scaling an agent business. Better models and more customers are only part of the calculation. The operator also needs to understand how much capital each commitment ties up. I’d be curious to see developers build that constraint into how their agents price and schedule work. A full order book needs enough resources behind it.