See you on the other side that prints. ๐ฐ
Cape
Joined March 2022
- Tweets20.4K
- Following1.7K
- Followers25.9K
- Likes36K
Pinned Tweet
The next 6 to 12 months are the ones where you change your life.
But, If you don't understand this little concept on how to prepare yourself for the next bull run, then forget about a 100x....
๐งต
๐๐๐ซ๐๐ฅ๐๐๐๐ฒ๐ฉ๐ ไบบ retweeted
So we're getting Primus sooner than later expected..
@primus_labs just dropped a teaser about this NOV likely to be their TGE
I joining primus_labs on @KaitoStudio_
cause the allocation was worth looking at.
0.3% of $PRIMโs total supply is allocated to the campaign, with 0.24% for creators and 0.06% for Kaito stakers.
Thatโs a larger creator allocation than Axisโs 0.25% campaign pool.
Second, thereโs still time to get involved.
Epoch 2 runs until November 21, followed by Epoch 3 from November 22 to December 21.
Points carry across epochs, and only your four best posts count per epoch.
Donโt rush to flood the timeline with low-effort content.
Use the time to understand what Primus is building and publish a few posts that actually explain the tech.
Its zkTLS technology verifies web data without exposing the underlying information, while zkFHE enables computation on encrypted data.
Privacy is becoming a bigger conversation in crypto.
The opportunity here is to understand the technology, contribute something useful, and let the quality of your work speak for itself.
Still early enough to make your entry count.
Make sure you start earning your XP here: s.kaito.ai/zJlvAyo
Most privacy solutions only address part of the problem.
They either hide everything or reveal everything.
Neither is enough when real capital and real decisions are involved.
What's missing is the ability to prove facts without exposing the underlying data, and to compute on sensitive information without decrypting it.
That's the gap Primus is building to address.
Not more secrecy.
Not more transparency.
But a way to keep sensitive data private while making it usable and verifiable.
Primus is building that cure.
So we're getting Primus sooner than later expected..
@primus_labs just dropped a teaser about this NOV likely to be their TGE
I joining primus_labs on @KaitoStudio_
cause the allocation was worth looking at.
0.3% of $PRIMโs total supply is allocated to the campaign, with 0.24% for creators and 0.06% for Kaito stakers.
Thatโs a larger creator allocation than Axisโs 0.25% campaign pool.
Second, thereโs still time to get involved.
Epoch 2 runs until November 21, followed by Epoch 3 from November 22 to December 21.
Points carry across epochs, and only your four best posts count per epoch.
Donโt rush to flood the timeline with low-effort content.
Use the time to understand what Primus is building and publish a few posts that actually explain the tech.
Its zkTLS technology verifies web data without exposing the underlying information, while zkFHE enables computation on encrypted data.
Privacy is becoming a bigger conversation in crypto.
The opportunity here is to understand the technology, contribute something useful, and let the quality of your work speak for itself.
Still early enough to make your entry count.
Make sure you start earning your XP here: s.kaito.ai/zJlvAyo
Most privacy solutions only address part of the problem.
They either hide everything or reveal everything.
Neither is enough when real capital and real decisions are involved.
What's missing is the ability to prove facts without exposing the underlying data, and to compute on sensitive information without decrypting it.
That's the gap Primus is building to address.
Not more secrecy.
Not more transparency.
But a way to keep sensitive data private while making it usable and verifiable.
Primus is building that cure.
๐๐๐ซ๐๐ฅ๐๐๐๐ฒ๐ฉ๐ ไบบ retweeted
Found a crazy opportunity for creators who are actively on here.
@FungoLabs just launched its $FUNGO campaign and they're putting 300M $FUNGO into its content campaign.
but the scoring rule is what I noticed.
Only your 5 best posts count toward the campaign.
That puts more weight on the quality of your content than on how often you post.
few details you might want to note:
โ Eligible posts must have been published from November 1, 14:00 UTC.
โ The reward pool is 300M $FUNGO.
โ Rewards are scheduled for distribution at TGE.
I prefer campaigns where the rules are clear and good research has room to stand out.
you should check it out : fungolabs.org/launchpad/c/cfโฆ
1/6
10 billion $FUNGO: Who gets how much?
Amounts, tokenomics and claim rules for Genesis NFT, Zama OG and the X Campaign.
Details ๐
๐๐๐ซ๐๐ฅ๐๐๐๐ฒ๐ฉ๐ ไบบ retweeted
An AI agent wants to buy $0.10 worth of market data.
The data costs 10 cents, but processing the payment through a conventional card could cost another 30 cents.
Imagine that same agent making thousands of small purchases every day.
Suddenly, the cost of moving money becomes a bigger problem than the service itself.
This is one reason I've been paying closer attention to the ๐ฒ๐บ๐ฒ๐ฟ๐ด๐ถ๐ป๐ด ๐ฝ๐ฎ๐๐บ๐ฒ๐ป๐ ๐ถ๐ป๐ณ๐ฟ๐ฎ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ ๐ณ๐ผ๐ฟ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐๐.
And the numbers are getting difficult to ignore.
According to @chainalysis, x402 recorded approximately 138.5 million cumulative transactions on Base through Q3 2026.
Over 87% of the payments analyzed were worth $0.10 or less.
That's a fascinating payment pattern because AI agents don't necessarily spend like humans.
An autonomous research agent might need to purchase market data, pay for inference, access an API, and run security checks, all within a single workflow.
Charging a conventional checkout fee for every tiny purchase becomes economically inefficient.
๐ง๐ต๐ถ๐ ๐ถ๐ ๐๐ต๐ฒ๐ฟ๐ฒ ๐
๐ฐ๐ฌ๐ฎ ๐ฒ๐ป๐๐ฒ๐ฟ๐ ๐๐ต๐ฒ ๐ฝ๐ถ๐ฐ๐๐๐ฟ๐ฒ.
Developed by @CoinbaseDev, x402 allows software to:
โ request a resource
โ receive payment instructions through HTTP 402
โ authorize a payment
โ access the service after verification
Coinbase's facilitator offers 1,000 free monthly settlements, followed by $0.001 per settlement under its published pricing.
But payment settlement is only one part of this emerging market.
I've been following several companies building different pieces of the infrastructure:
โข @CoinbaseDev โ x402 payment infrastructure for machine-to-machine transactions.
โข @crossmint โ Agent wallets, stablecoins, existing card integration, and merchant checkout.
โข @turnkeyhq โ Wallet infrastructure that developers can integrate into agent applications.
โข @evervault and @basistheory โ Secure payment credentials and sensitive-data infrastructure.
โข @nevermined_ai โ Usage-based payments, metering, and x402 settlement for AI services.
โข @Stripe โ Shared Payment Tokens that allow agents to initiate authorized purchases without exposing underlying card credentials.
โข @Visa โ Intelligent Commerce and Trusted Agent Protocol for recognizing and authorizing agent-driven transactions.
โข @Mastercard โ Agent Pay for Machines, combining agent credentials, spending permissions, and multiple settlement rails.
Notice something here?
๐ง๐ต๐ฒ ๐ฐ๐ผ๐บ๐ฝ๐ฒ๐๐ถ๐๐ถ๐ผ๐ป ๐ถ๐๐ป'๐ ๐๐ถ๐บ๐ฝ๐น๐ ๐ฐ๐ฟ๐๐ฝ๐๐ผ ๐๐ฒ๐ฟ๐๐๐ ๐๐ฟ๐ฎ๐ฑ๐ถ๐๐ถ๐ผ๐ป๐ฎ๐น ๐ฝ๐ฎ๐๐บ๐ฒ๐ป๐๐.
Itโs about which infrastructure can give machines purchasing power without sacrificing cost efficiency, security, or accountability.
And thereโs still an uncomfortable question:
If an AI agent makes an unauthorized purchase, exceeds its spending limit, or pays for a service that never arrives, who takes responsibility?
Cheap settlement doesnโt automatically solve those problems.
Thereโs also a reason to be cautious about the adoption numbers. Chainalysis identified speculative activity contributing to earlier x402 growth, so transaction counts alone donโt prove sustainable commercial demand.
My expectation is that agent payments will develop across multiple rails:
โธ Stablecoins and x402 have compelling economics for micropayments.
โธ Card networks retain established merchant acceptance and dispute mechanisms.
The infrastructure that connects both while enforcing verifiable spending permissions, could become an important part of autonomous commerce.
AI agents are learning to do work independently. The next challenge is allowing them to pay for that work without losing human control over the money.
๐๐๐ซ๐๐ฅ๐๐๐๐ฒ๐ฉ๐ ไบบ retweeted
Crypto tokens are getting easier to value when protocols return revenue to holders.
Buybacks and burns are becoming a bigger part of token economics.
Zenecaโs research puts annual spending at $1.85B for the year to October 2026, up from $190M in 2021.
But a protocol buying its own token doesnโt automatically make that token undervalued.
Here are six models Iโm tracking:
โ $HYPE: Trading fees fund HYPE purchases through Hyperliquidโs Assistance Fund. The tokens are burned.
โ $PENDLE: 80% of V2 yield and swap fees fund buybacks distributed to eligible active sPENDLE holders.
โ $PUMP: Its current program commits 50% of revenue to buybacks and burns for one year from April 2026.
โ $SKY: Protocol surplus funds SKY purchases for burns or staking rewards.
โ $RAY: 12% of pool trading fees fund RAY buybacks.
โ $STONK: The project has spent money buying STONK, but weaker recent revenue makes it harder to assume that pace will continue.
โ $PONS: Its published V1 model directs 80% of protocol fees to PONS buybacks and burns.
The differences matter.
Some tokens are burned, while others are bought and distributed to holders.
Emissions and unlocks can also offset buybacks.
When comparing these tokens, I look at three things:
โข Revenue: Is it holding up over 30โ90 days?
โข Supply: Are buybacks large enough to matter alongside emissions and unlocks?
โข Valuation: How much revenue growth is already priced in?
A quick starting point is market cap divided by annual buyback spending.
A $1B token with $50M in annual buybacks trades at 20x that spending.
That isn't an earnings multiple, and it only helps if the buybacks can continue.
โข I use DefiLlama to compare revenue
โข CoinGecko for market cap and FDV
โข Tokenomist for unlocks
โข Block explorers to check buyback and burn transactions.
if want to hold any of these tokens, youโll want to focus more on some of these protocols
but focus more on the ones that keep earning while returning enough value to token holders.
Found a crazy opportunity for creators who are actively on here.
@FungoLabs just launched its $FUNGO campaign and they're putting 300M $FUNGO into its content campaign.
but the scoring rule is what I noticed.
Only your 5 best posts count toward the campaign.
That puts more weight on the quality of your content than on how often you post.
few details you might want to note:
โ Eligible posts must have been published from November 1, 14:00 UTC.
โ The reward pool is 300M $FUNGO.
โ Rewards are scheduled for distribution at TGE.
I prefer campaigns where the rules are clear and good research has room to stand out.
you should check it out : fungolabs.org/launchpad/c/cfโฆ
1/6
10 billion $FUNGO: Who gets how much?
Amounts, tokenomics and claim rules for Genesis NFT, Zama OG and the X Campaign.
Details ๐
๐๐๐ซ๐๐ฅ๐๐๐๐ฒ๐ฉ๐ ไบบ retweeted
Idle stablecoins earn nothing.
@grvt_io just launched High Yield Earn up to 11% target APY
An 11% target APY got my attention.
What matters more to me is where that yield comes from.
GRVT High Yield Earn combines traditional finance and crypto strategies.
they including tokenized fixed income, real-world asset financing, crypto credit and market neutral strategies.
The underlying mechanics deserve a closer look.
Whitelist is open ๐
Code: 9HW7U3Z
grvt.io/?ref=9HW7U3Z
DYOR.
JUST IN: High Yield Earn is LIVE for whitelisted users.
Up to 11% target diversified yield across TradFi & crypto, with daily payouts and full self-custody.
The bigger unlock is coming soon: the same capital that earns your yield will also back your trades.
One balance. Two jobs.
DM โEARNโ for whitelist access.
Idle stablecoins earn nothing.
@grvt_io just launched High Yield Earn up to 11% target APY
An 11% target APY got my attention.
What matters more to me is where that yield comes from.
GRVT High Yield Earn combines traditional finance and crypto strategies.
they including tokenized fixed income, real-world asset financing, crypto credit and market neutral strategies.
The underlying mechanics deserve a closer look.
Whitelist is open ๐
Code: 9HW7U3Z
grvt.io/?ref=9HW7U3Z
DYOR.
JUST IN: High Yield Earn is LIVE for whitelisted users.
Up to 11% target diversified yield across TradFi & crypto, with daily payouts and full self-custody.
The bigger unlock is coming soon: the same capital that earns your yield will also back your trades.
One balance. Two jobs.
DM โEARNโ for whitelist access.
๐๐๐ซ๐๐ฅ๐๐๐๐ฒ๐ฉ๐ ไบบ retweeted
Creator Season 1 is live.
Create content about Sight and robinhood:0x238e40b75ae78a1388a14e517d855893e92e58db, earn points and compete for USDC and other rewards.
Your content. Your points. Your rewards.
Start here: creator.sighthood.com
Crypto tokens are getting easier to value when protocols return revenue to holders.
Buybacks and burns are becoming a bigger part of token economics.
Zenecaโs research puts annual spending at $1.85B for the year to October 2026, up from $190M in 2021.
But a protocol buying its own token doesnโt automatically make that token undervalued.
Here are six models Iโm tracking:
โ $HYPE: Trading fees fund HYPE purchases through Hyperliquidโs Assistance Fund. The tokens are burned.
โ $PENDLE: 80% of V2 yield and swap fees fund buybacks distributed to eligible active sPENDLE holders.
โ $PUMP: Its current program commits 50% of revenue to buybacks and burns for one year from April 2026.
โ $SKY: Protocol surplus funds SKY purchases for burns or staking rewards.
โ $RAY: 12% of pool trading fees fund RAY buybacks.
โ $STONK: The project has spent money buying STONK, but weaker recent revenue makes it harder to assume that pace will continue.
โ $PONS: Its published V1 model directs 80% of protocol fees to PONS buybacks and burns.
The differences matter.
Some tokens are burned, while others are bought and distributed to holders.
Emissions and unlocks can also offset buybacks.
When comparing these tokens, I look at three things:
โข Revenue: Is it holding up over 30โ90 days?
โข Supply: Are buybacks large enough to matter alongside emissions and unlocks?
โข Valuation: How much revenue growth is already priced in?
A quick starting point is market cap divided by annual buyback spending.
A $1B token with $50M in annual buybacks trades at 20x that spending.
That isn't an earnings multiple, and it only helps if the buybacks can continue.
โข I use DefiLlama to compare revenue
โข CoinGecko for market cap and FDV
โข Tokenomist for unlocks
โข Block explorers to check buyback and burn transactions.
if want to hold any of these tokens, youโll want to focus more on some of these protocols
but focus more on the ones that keep earning while returning enough value to token holders.
Might be late, but Happy new month frens
i think itโs time we go original.
letโs see how far we can go.
anyways i just hope yโall are enjoying your day..
we go again tomorrow..
The agent economy becomes interesting when agents can do more than complete tasks.
when they can find work, follow instructions, and get paid.
I think that's the next challenge for autonomous agents.
Giving an agent more skills is useful, but skills alone don't create an economy.
There also needs to be a way to connect those skills to real demand and handle payment.
That's why I'm looking at what @termix_ai is building with Agent Skills.
They announced integrations include Grok, Muse, and Claude, although the exact capabilities may differ across agents.
I'm interested in seeing whether this can move beyond a good concept and become a practical way to get useful work done.
Want to explore it yourself?
Check out the TermiX Agent Skills and follow the installation guide.
Personally, i think the agent economy won't be built on intelligence alone, It needs a way for agents to turn skills into income.
Superintelligence agents will earn currency for themselves โ not for a humanโโ@elonmusk
That's the agent economy.
Give your Agent Skills to take orders and get paid:
help me install termix.ai/skills?v=latest
Works on Grok @Bot, @Muse, Claude.
Install โ your Agent can earn.
One of the biggest limitations of blockchains is, it cannot independently verify anything happening outside itโs networks.
Exchange balances, financial records, and account history could help applications make better decisions.
The problem is proving that information is genuine without forcing users to expose sensitive details.
This is where I think @primus_labs is worth watching.
Imagine a lending protocol using someone's financial history outside crypto.
A screenshot isn't strong evidence, while building a separate integration for every platform can be costly.
Giving an application access to an entire account also raises privacy concerns.
The challenge is to verify specific information without revealing more than necessary.
Where Primus fits
Primus is developing tools for web data verification and privacy-preserving computation, including zkTLS.
The idea is to help applications verify information obtained from web interactions and use it in ways that reduce unnecessary data exposure.
Potential applications include Proof of Reserves, financial services, and systems that need to check claims using information held outside a blockchain.
These use cases are promising, but their success depends on how reliably the technology works in practice.
For me, four questions matter:
Can the system verify data reliably?
โข How much private information remains exposed?
โข Are verification costs and speeds practical?
โข Are developers using it in products that attract real users?
Personally, i believe in making external data verifiable could expand what crypto applications can do, especially in finance.
But connecting a website to a blockchain isn't enough.
The data must be trustworthy, the privacy protections must hold, and the system must be practical to use.
Primus is working on that problem.
The real opportunity is making off-chain information useful without asking users to reveal everything.
A lot of useful data in crypto still sits outside the blockchain.
Exchange history, account balances and other records live on websites that smart contracts canโt read directly.
Thatโs the problem @primus_labs is working on.
Its zkTLS technology lets apps verify data from websites without requiring users to hand over their login credentials or share unrelated account information.
This could be useful for onchain lending, trading and reputation systems that need to check activity beyond a wallet address.
Bringing offchain data onchain only matters if the data can be trusted and the privacy trade off makes sense.
Make sure you start earning your XP here: s.kaito.ai/zJlvAyo
Wrong time for CZ to troll elon back with this tweet..
getting back user funds should be top priority for CZ rn.
but how come crypto keep getting exploited in big 2026.
more reasons why VCs are pivoting to AI cause this hacks is not stopping anytime soon..
AI agents can write code, analyze data, and complete tasks. But being able to do the work is only part of the problem.
How does an agent find a customer, agree on the work, deliver it, and actually get paid..
Imagine an agent that can analyze blockchain data.
It may be good at the job, but where does it find paying customers?
How does a buyer know the work is worth the price?
And what happens when the result falls short?
These are problems of trust, payment and coordination.
Better models alone won't solve them.
Without clear rules, both sides face uncertainty.
A working marketplace needs four things:
โข Discovery: Finding the right agent for the job.
Agreement: Setting the price, scope, and expected result.
โข Delivery: Establishing what work was submitted.
โข Settlement: Releasing payment and handling disputes.
Each step depends on the others.
Escrow can protect payment, but it cannot guarantee that the work is good.
TermiX's agent.family marketplace supports job listings, quotes, on-chain escrow, delivery records, and a dispute process involving evaluators.
Agent identities and settlement outcomes are also recorded on-chain.
The aim is to make agreements and payments easier to verify without relying entirely on trust between strangers.
The main question is whether the marketplace attracts genuine demand.
Registered agents and listed jobs don't necessarily mean useful work is being completed.
A delivery record also doesn't prove quality, and dispute outcomes depend on how well the evaluation process works.
@termix_ai still needs to demonstrate that these features solve the problem better than existing alternatives.
I'll focus on three things:
โข Completed jobs: How much work actually reaches settlement?
โข Repeat customers: Do buyers return after their first transaction?
โข Disputes: How often do they occur, and how are they resolved?
I'll be watching whether agents complete useful work, receive payment under clear rules, and earn enough trust to get hired again.
That's where the real test begins.
AI agents can write code, analyze data, and complete tasks.
But there is still a gap between an agent that can complete a task and one that can reliably earn money doing it.
Imagine an agent that can analyze blockchain data. It may be good at the job, but where does it find paying customers?
How does a buyer know the work is worth the price? And what happens when the result falls short?
These are problems of trust, payment, and coordination. Better models alone won't solve them.
โง For agents to do business with each other, four things need to work:
โ Discovery: Buyers need to find the right agent.
โ Agreements: Both sides need clear terms before work starts.
โ Payment: Agents need a reliable way to get paid.
โ Accountability: Buyers need a way to check results and challenge poor work.
Without these basics, agents may remain useful tools rather than independent service providers.
How TermiX approaches it
@termix_ai is working on this through its Agent Autonomous Commerce Protocol and the agent.family marketplace.
Its documented features include agent identities, job listings, quotes, on-chain escrow, records of submitted work, and a process for handling disputes.
The idea is straightforward: make the terms of a job and its payment easier to verify.
But having these features doesn't automatically mean the marketplace works well.
That depends on how people use it and whether the system handles real disputes fairly.
Sources: TermiX marketplace ยท AACP whitepaper
The biggest question is demand.
Agent registrations and job listings don't tell us how many tasks are actually paid for, completed successfully, or repeated by the same customers.
Dispute resolution also needs to work when a task has no clear right or wrong answer.
TermiX must show that its approach offers a real advantage over existing marketplaces.
TermiX is addressing a real problem, but the idea alone isn't enough.
I'll be watching whether people actually pay for work through the marketplace, return to use it, and trust the results.
That's what will separate a useful product from an interesting one.
A lot of useful data in crypto still sits outside the blockchain.
Exchange history, account balances and other records live on websites that smart contracts canโt read directly.
Thatโs the problem @primus_labs is working on.
Its zkTLS technology lets apps verify data from websites without requiring users to hand over their login credentials or share unrelated account information.
This could be useful for onchain lending, trading and reputation systems that need to check activity beyond a wallet address.
Bringing offchain data onchain only matters if the data can be trusted and the privacy trade off makes sense.
Make sure you start earning your XP here: s.kaito.ai/zJlvAyo
Onchain transparency can expose and work against a trader's strategy.
A wallet's buys, collateral changes and transfers between protocols can make other traders to use their activity to track positions or anticipate the next move.
But DeFi lending and trading still require proof.
A lender may need to verify a borrower's financial position without seeing their entire portfolio.
That's the use case I'm looking at with @primus_labs.
Primus is exploring ways for users to prove information about their trading history or positions without disclosing every detail to a protocol.
Its zkTLS technology can verify data from web services, but it doesn't automatically hide transactions recorded on public blockchains.
I'm interested in whether DeFi protocols can verify what they need without collecting a trader's entire financial history.
That could give traders more control over what they reveal.
I'd watch how Primus handles that in actual applications.
especially for lending and derivatives, where private information can affect a trader's edge.
to explore more start the XP tasks here: s.kaito.ai/zJlvAyo
๐๐๐ซ๐๐ฅ๐๐๐๐ฒ๐ฉ๐ ไบบ retweeted
AI agents are creating a new payments market, but the rails they use will determine whether autonomous commerce is economical at scale.
Commercial cards can carry interchange fees of 2.5โ3%. Meanwhile, 138.5M reported x402 transactions on Base by Q3 2026 point to growing use of stablecoins for machine-to-machine payments.
Hereโs how the agent payment stack is evolving.
โ
โ AI Agents Need a New Payment Stack
Unlike humans, autonomous agents continuously purchase API calls, datasets, compute, and inference without manual checkout.
That activity creates four infrastructure requirements:
โข Programmable spending through budgets and transaction limits.
โข Machine-native payments without human intervention.
โข Low-cost settlement for micropayments.
โข Verifiable authorization to establish who controls an agentโs spending.
Wallets, stablecoins, payment APIs, and identity protocols are converging around these needs. But the payment rails underneath them carry very different costs and incentives.
โ
โ The Hidden Cost of AI Agent Cards
AI agents using commercial virtual cards can trigger interchange fees of 2.5โ3%, creating a recurring cost for merchants.
On a $100 purchase, the cited estimate puts fees at $2.80 for commercial agent cards versus $0.27 for regulated debit.
Agent startups and card issuers may share this revenue, giving them an incentive to preserve expensive card rails even as autonomous payments scale.
This cost structure underpins the crypto thesis: stablecoins could provide a more economical payment layer for agentic commerce, particularly for small, frequent purchases.
โ
โ x402 Brings Payments Into HTTP Requests
One approach combines wallets, stablecoins, and x402, allowing agents to pay for resources directly through HTTP requests.
Agent requests an API, dataset, or compute resource โ Server returns HTTP 402 with payment terms โ Agent authorizes a $USDC payment โ Facilitator verifies settlement โ Resource is delivered.
By embedding payment into this interaction, x402 removes conventional checkout friction and enables programmable payments for individual API calls.
That includes micropayments worth just a few cents, where conventional payment fees can exceed the purchase itself.
โ
โ Micropayments Change the Economics
The source compares traditional card pricing of 2.9% + $0.30 with modeled stablecoin processing at 1.5% and x402 settlement at approximately $0.001.
โข On a $0.10 payment, modeled card fees reach $0.3029 versus $0.001 for x402.
โข The source places the card-to-stablecoin cost crossover near $21.43 under its assumptions.
For agents buying inference, API access, and data in small increments, settlement costs directly affect which transactions are commercially viable.
This makes micropayments a natural entry point for stablecoin-based agent payments.
โ
โ x402 Adoption Is Concentrated in Micropayments
@chainalysis data cited in the research reports 138.5M cumulative x402 transactions on Base by Q3 2026, with over 87% below $0.10.
โข The reported time from funding to first payment fell from 73 days to around 18 minutes.
โข @CoinbaseDev offers 1,000 monthly settlements free, then charges $0.001 per settlement.
These figures point to growing transaction activity and faster payment activation.
However, transaction growth alone does not establish sustainable demand or revenue. The wider opportunity depends on the infrastructure connecting payments to usable agent services.
โ
โ The Agent Payment Stack Spans Six Layers
The original ecosystem map identifies 30 startups building across different parts of agentic payments.
โข Cards and tokens: @agentcardhq, @pravapayments, @getpayos, @evervault, @basistheory
โข Wallets and accounts: @crossmint, @openfort_hq, @turnkeyhq, @1shotapi, @HallidayHQ
โข Banks and networks: @naturalpay, @catena_labs, @GoKiteAI, @PaymanAI, ATXP
โข Pay-per-call and x402: @daydreamsagents, @merit_systems, @PayWithLocus, Nevermined, Lava
โข Trust and identity: @VouchedID, @trySkyfire, @sapiom, @t54ai, @Mnemopay
โข Checkout and merchants: @rye, @nekuda_ai, @bitrefill, @meshpay, Firmly
Together, these projects cover payment credentials, wallets, settlement, identity, and merchant checkout.
The market is developing across multiple layers because executing a payment is only one part of enabling an agent to transact reliably.
โ
โ Crossmint Offers an Alternative to Agent-Issued Cards
The commercial-card cost structure is not inevitable. @crossmint enables users to bring their own cards instead of relying on provider-issued virtual cards.
โข Provider-issued cards : May trigger higher commercial interchange fees.
โข User-provided cards : May retain consumer-card economics, subject to issuer and network rules.
โข Stablecoin wallets : Enable programmable, onchain payments.
This gives agent platforms multiple payment routes. Letting users connect existing cards or wallets can help avoid the higher commercial-card fees associated with some provider-issued products.
The broader competition therefore includes both new settlement rails and better ways to connect agents to existing payment methods.
โ
โ Traditional Payment Giants Are Building for Agents
Crypto-native startups are part of a wider race. Stripe, Visa, Mastercard, and Coinbase are building infrastructure to capture agent-driven payments.
โข @Stripe: Link for agents, MPP, ACP, Treasury for Agents, and Shared Payment Tokens.
โข @Mastercard: Agent Pay and AP4M, including signed vouchers integrated with x402.
โข @Visa: Intelligent Commerce and Trusted Agent Protocol.
โข @Coinbase: x402 and Coinbase Developer Platform for onchain settlement.
โข @AWS, @Cloudflare, and @tryramp are also developing agent payment infrastructure and spending controls.
These providers approach the market with different strengths. Crypto offers cheaper micropayments, while established networks bring merchant acceptance, consumer checkout, and dispute handling.
Connecting those strengths will require more than low-cost settlement.
โ
โ Trust Remains a Critical Layer
Cheap payments have limited value if merchants cannot verify an agentโs identity, spending limits cannot be enforced, or disputed transactions remain unresolved.
Three capabilities matter:
โข Know Your Agent (KYA): Verify the agent, its controller, and its spending authorization.
โข Spending controls: Enforce budgets, transaction limits, and merchant restrictions.
โข Liability and reconciliation: Handle unauthorized payments, failed purchases, and transaction records.
Projects like @VouchedID, @sapiom, @t54ai, and @Mnemopay are building around this trust layer.
Stablecoins reduce payment friction, but they do not inherently provide card-like chargebacks or consumer protections. Those capabilities need to be addressed across the broader payment stack.
โ
The long-term opportunity lies in making autonomous payments economical while maintaining authorization, security, and reliable settlement.
x402 and stablecoins have an advantage in micropayments. Established networks retain distribution, merchant acceptance, and consumer protect
ions.
The market will be shaped by transaction economics, the merchants agents can reach, and how effectively these systems connect.
Not every sector performance and narrative guarantee a strong token.
My focus rn is on sectors where onchain activity could grow, but each token still needs to prove its value.
These are the areas Iโm watching:
AI & COMPUTE
โ $GRASS โ Decentralized data
โ $VVV โ Private AI inference
โ $TAO โ Decentralized AI
โ $QUBIC โ proof of work and AI
โ $RENDER โ GPU rendering
PRIVACY
โ $ZANO โ Private Layer 1
โ $ZAMA โ Confidential smart contracts
โ $ZEC โ Privacy focused transactions
TRADING & DEFI
โ $HYPE โ Onchain trading and Layer 1
โ $PENDLE โ Yield trading
โ $AERO โ Base DEX liquidity
โ $LIT โ Decentralized perpetuals
โ $PUMP โ Memecoin launches
โ $BP โ Backpack ecosystem
RWA & ORACLE INFRASTRUCTURE
โ $ONDO โ Tokenized real-world assets
โ $CHEX โ RWA infrastructure
โ $LINK โ Oracle network
โ $PYTH โ Market data
LAYER 1 & INTEROPERABILITY
โ $NEAR โ Layer 1 and AI infrastructure
โ $QNT โ Blockchain interoperability
OTHER BETS
โ $GEOD โ Decentralized positioning
โ $PENGU โ Pudgy Penguins ecosystem
My focus isn't just which narratives attract capital.
I want to see real usage, revenue, token unlocks and how much value flows back to holders.
A project can grow while its token struggles, especially when supply keeps increasing.
The sector matters, but token economics matter just as much.
