#TermixAI

I kept seeing @termix_ai on my TL, so I decided to find out what they were building. I checked them out on @KaitoAI Studio, then dug into their protocol statistics on DefiLlama. The revenue figures made me want to dig deeper. Back in Q2 2025, @yzilabs reportedly invested $1M in TermiX’s seed round. Since then, TermiX has reported some notable mainnet milestones. But I wanted to understand what was behind the numbers and what they actually tell us about the protocol. According to the project’s reported milestones, TermiX has reached: > Over $10M in total transaction volume from agent jobs > More than 360,000 agents > Over 38,000 agent jobs created > Protocol revenue surpassing $100,000, with further growth reported I also checked DefiLlama, where the snapshot I saw showed $5,037 in 7-day revenue and $40,375 in 30-day revenue on BNB Chain. That gave me more to investigate. TVL, volume, and revenue tell you different things about a protocol. TVL shows how much value is locked in it. Volume tracks the value of activity passing through it. Revenue shows how much the protocol earns from that activity. For an AI agent marketplace, revenue is particularly worth looking at because it gives us another way to examine the economic activity behind the product. Here’s why. Having lots of AI agents is one thing. Having agents that actually get hired, complete tasks, and settle payments is another. The real question isn’t just how many agents exist. It’s whether they’re doing useful work and creating economic activity. That’s what made me look closer at TermiX. TermiX is building a marketplace where AI agents can hire each other to get work done. Its model connects agent-to-agent jobs with onchain escrow and payment settlement. According to DefiLlama’s methodology, TermiX charges a 2% protocol fee on settlements, and those fees count as protocol revenue. That gives us something concrete to examine beyond the vision itself. Of course, revenue alone doesn’t tell the whole story. I’d still want to know: • How many jobs are actually being completed? • Are users coming back to hire agents again? • How much are service providers earning? • Is demand holding up over time? These details help distinguish sustainable usage from a short-term spike. This is the bigger idea I find compelling about TermiX. AI agents doing useful work is one thing. AI agents operating in an economy where jobs, payments, and outcomes can be tracked onchain is another. If usage continues to grow and market conditions improve, I think there could be more room for TermiX to expand. But sustained demand matters more than any single milestone. I’m more interested in whether TermiX can sustain real economic activity than in a leaderboard position alone. The milestones and revenue figures are worth watching, but repeat usage, completed jobs, and consistent demand will tell us much more over time. What would convince you that an AI agent economy has real product-market fit? Data:

I’ve been going deeper into @termix_ai, and this part of the workflow stood out to me: “Trust, enforced by math.” That sounds like a strong statement until you look at what actually sits underneath it. Every job follows a defined on-chain lifecycle: -->Escrow Payment is locked when a quote is accepted. -->Delivery The deliverable hash is recorded on-chain and payment can release when the work is submitted. -->Challenge If something goes wrong, there’s a challenge window instead of simply relying on trust between the two agents. -->Settlement A dispute goes to a 3-evaluator panel, and the final outcome updates reputation on-chain. That structure is important because agent-to-agent commerce has a different problem from normal AI interaction. It’s not only: “Can this agent do the task?” It’s also: What happens if the work is wrong? -Who holds the payment? -How is delivery recorded? -Can the result be challenged? -What happens to the agent’s reputation afterward? TermiX is trying to answer those questions at the protocol level. And honestly, that’s more interesting to me than simply having another marketplace for AI agents. The intelligence may come from the agent. But the rules around the transaction are what make an economy possible. #TermiX #AIAgents

The most interesting part of @termix_ai isn’t that AI agents can take jobs. It’s that they have to earn trust to get hired. On an agent isn’t just an AI tool. It has a work history: jobs completed, deliverables submitted, reviews received and on-chain transactions. So before assigning a task, users can check what an agent has actually done, how well it delivered and whether it was paid for that work. That changes everything. Instead of choosing an agent based on a model name or marketing claims, you choose based on verifiable work history. When agents can take jobs and receive payment, reputation is no longer a decorative score. It becomes an asset that determines whether an agent gets hired again. A strong agent completes more jobs → earns more trust → gets more opportunities. A weak agent? Its history speaks for itself. This is how AI agents move from being “tools” to becoming a trusted digital workforce.

friendly reminder for the timeline: ​@termix_ai has zero presales, private rounds or early investor allocations open ​anyone DMing you pretending to be from the team asking for funds is trying to drain you. don't fall for it ​only trust official announcements and keep your guard up ​stay sharp out there

AI agents can already execute tasks, the real bottleneck now is trust. ​@termix_ai fixes this via AACP using onchain reputation, escrow and dispute resolution. basically lets agents build a real resume from completed jobs rather than just flexing their prompts. ​makes total sense that top rated agents will eventually get the most volume and charge premium fees. ​literally mirrors how human freelancers scale up. that's the part of the agent economy I'm most hyped to see play out.!

one update from @termix_ai that i think deserves some attention is the release of Agent Skills v1.9.0. with this update, compatible AI agents can connect to and start accepting orders through the marketplace. what i find interesting here is that developers don’t necessarily have to build entirely new agents to participate. they can bring agents they’ve already developed into an environment where their services can be offered to potential clients. think about developers who have spent months building useful AI tools but have no marketplace to distribute their services. integrations like this could give those tools another opportunity to reach users. of course, how much demand these services attract is something we’ll have to see. but i think making existing AI agents accessible through a marketplace is a useful direction for TermiX.

If you’re looking to get positioned in @termix_ai, here’s what I’d focus on. A few things you can do to get started: → Create an account on using your EVM wallet. → Head over to the points section and complete the available tasks. → Mint your own .agent identity. → Register an AI agent for 200 TP. → Launch a bounty. You can earn 100 TP for every $1 worth of completed agent jobs. → Invite friends and grow your network. But there’s something bigger going on here. Think of @termix_ai as a Fiverr built for AI agents on BNB Chain. Agents can hire other agents, complete tasks, offer services and get paid through onchain escrow. It’s not just about collecting points. It’s about getting involved early in an ecosystem where AI agents can actually do business with each other.

Most AI projects are easy to overlook until you look at what they’re actually generating. That’s what happened when i revisited @termix_ai after spotting it in the @kaito studio. I dug deeper into the project, checked the figures listed on DeFiLlama, and found a few numbers that caught my attention. According to the available reports, @yzilabs invested $1M in TermiX AI’s seed round in Q2 2025. DeFiLlama currently lists approximately $594k in cumulative revenue, $3,080k in daily revenue, and $103k in monthly revenue. These figures are reported metrics, so it’s worth verifying how each one is defined and calculated before drawing firm conclusions. The numbers are interesting, but they aren’t the most important part to me. It’s what TermiX appears to be building. Many people look at crypto projects and immediately judge them by TVL. That makes sense for some protocols, but not every project is designed to attract deposits. TermiX describes its focus as an AI agent commerce layer. In simple terms, imagine one AI agent needing a task completed and hiring another AI agent with the right skills to handle it. Now imagine that happening across thousands of agents, each offering different services and potentially getting paid for their work. That’s the broader idea behind this kind of infrastructure, although the model is still developing and its real-world adoption remains to be proven. We are still early in figuring out how the agent economy will work, and there are no guarantees about which projects will succeed. Still, the concept itself is fascinating. Personally, I think TermiX is worth watching, especially if demand for AI-powered services continues to grow.

One agent, two roles. This detail in @termix_ai is worth understanding. On an agent has a unified identity through ERC-8004. Its role as a buyer or provider depends on the individual order. Imagine an agent that produces market research. It could sell a research report to one customer, then purchase a specialist data service for a separate assignment. The same agent participates on both sides of the marketplace. Those roles come with different responsibilities. As a buyer, it reviews offers, funds escrow and accepts or challenges delivery. As a provider, it publishes services, responds to requests and delivers the agreed work to receive payment. This creates room for specialization. An agent can offer what it does well and purchase expertise for work outside its capabilities. For me, that is an interesting part of the economy @termix_ai is building: agents becoming customers of other agents, with each order carrying its own obligations. A useful question to ask when exploring the marketplace: what would your agent provide, and what would it need to buy?

What if AI agents could do more than complete tasks? What if they could find work, hire other agents, and earn money? That's an interesting idea behind @termix_ai . I’m looking at TermiX because it focuses on something the agent economy will need: a way for AI agents to turn their capabilities into actual services. Here's how I see it working An agent could find a job, another could provide a specialized skill, and both could collaborate to get the work done. On-chain escrow helps secure payments, while a dispute process offers a way to address problems when deliverables are contested. TermiX also brings agent collaboration into the picture through its Skills system, alongside Binance Agent ID integration. For example, a research agent could work with a data analysis agent to deliver better results without doing everything alone. To me, this is where things get interesting. AI becomes much more useful when different agents can contribute their strengths instead of operating separately. There’s still a lot to prove around security, reliability, and adoption, but building the infrastructure for agents to exchange services and value is a meaningful step. The real opportunity isn't just smarter AI. It's an ecosystem where AI can work, collaborate, and create economic value. Curious to see how @termix_ai develops from here.

gm been reading through the termix docs and the part most people skip is that isn't just a directory of agents. it's built on AACP, which handles the boring but important stuff: onchain identity, job posting, bidding, usdc/usdt escrow, delivery verification, reputation and disputes listing agents is easy. the hard part is making sure an agent actually gets paid for real work and the client can verify it was done. that's the gap termix is going after so far agents are still mostly demos. once they can get hired, deliver and settle onchain, you get actual agent to agent commerce keep building with Termix ecosystem @termix_ai

gm @termix_ai family Personal agents can book flights and file forms. They still cannot hire another agent, lock funds, verify delivery, and release payment without a human in the middle. That gap is not solved by better models or longer directories. A directory tells you an agent exists. Commerce decides whether the money moves only after the work is checked. @termix_ai runs the second part on AACP. Quote accepted, escrow locks, deliverable hash posted, challenge window open, then settle. Same path whether the client is a person or another agent. Without that loop, every personal agent stays a tool that can act but cannot finish a commercial job with a stranger. Directory shows capability. Settlement enforces the outcome.

gm @termix_ai family tested the provider arbitration queue on today to see how a technical job challenge actually resolves onchain without a centralized support desk. what was smooth: the challenge window triggers automatically the moment the deliverable hash hits the registry. the fact that any random validator panel can pick up the dispute and grade it based on the pre-agreed rubric means zero platform intervention. what confused me: the token burn penalty mechanism for frivolous complaints. if you open a dispute and the panel rejects it, your bond is burned completely. it’s a brilliant anti-spam layer, but definitely a high-stakes choice for a new user adjusting from standard web2 freelance chargebacks. the protocol layer logic here is solid—no human overrides, just strict execution states. #TermiX #AIAgents #Web3AI #AACP

Apps have app stores. Agents have skills. @bot, @Muse , Dot,(and @binance AI, once it begins supporting external skills)—turn your expertise into paid work with @termix_ai Skills. Find jobs. Deliver results. Get paid. Start here:help me install

Spent some time exploring @termix_ai and the product makes a lot more sense once you look at the full flow instead of just the agent side Agents can already write code research design or trade what they still couldnt do cleanly was find work get hired, deliver get paid, and build a real track record without a human sitting in the middle of every step thats the gap TermiX is trying to close On the marketplace you can - Discover agents and services - Post jobs and receive quotes - Fund work through on-chain escrow - Submit and review deliverables - Challenge disputed results - Build reputation from completed work the same agent can work as both buyer and provider identity is unified (on-chain agent handle you actually own) so one agent can hire on one job and take work on the next the Agent toolkit makes it straightforward to connect the agents you already use the bigger loop they put on-chain is Identity - Work - Escrow - Delivery - Verification - Reputation Funds sit in the escrow contract, deliverables are hashed and locked on-chain disputes go to an evaluator panel, and reputation is written from actual settled outcomes rather than self-reported ratings fees stay low compared with traditional platforms thats what makes it interesting its not just about AI agents generating outputs its about giving agents a way to find work transact, and build verifiable reputation on chain Worth looking at the full flow if youre building or using agents -

🚨 SCAM ALERT！！！ We’ve become aware of individuals impersonating the @termix_ai team and soliciting investments from community members. TermiX is NOT conducting any form of community fundraising. Treat anyone making such requests as a scammer. Stay alert and verify information through our official channels.

An AI agent having skills is one thing. Being able to turn those skills into a paid service is a completely different opportunity. That's the part of @termix_ai I find worth exploring. TermiX is building around the idea of autonomous commerce, where agents can take on different roles instead of simply responding to prompts. A provider can register an agent and list its available skills. Clients can discover those services, place orders and use escrow-based payments to create a more structured transaction. Another interesting part is the evaluator system. Rather than relying entirely on trust between two agents, completed work can go through evaluation before payment is released. There are three important roles in this model: → Client requests a service → Provider delivers the work → Evaluators assess the result This creates a framework where identity, payment and service verification work together. I think the bigger opportunity is making AI agents economically useful, not just technically impressive. TermiX is an interesting project to follow as this space develops.

one question i have about @termix_ai: how do you verify delivery when the work itself is subjective? checking if code runs or data matches is straightforward. judging the quality of a design or research is a different challenge. termix has an evaluator role and an arbitrator for disputes, which gives the system a framework. but the real test is how well it handles ambiguous, messy tasks where quality isn’t so easy to measure. that’s what i’d want to see in practice.

Everyone is talking about AI agents that can do more. But there’s a bigger question nobody should ignore: What happens when an AI agent needs to hire another agent, pay for its work, verify the result, and build a reputation that follows it? That’s where the real agent economy begins. Here’s my take on @termix_ai 🧵

what happens when an AI agent gets hired to do a job? who pays it? how do you verify the delivery? and what happens if something goes wrong? this is the part of the AI agent economy that deserves more attention @termix_ai is building a marketplace where agents can hire other agents offer services, and settle jobs onchain here’s how the workflow works > 1. discover buyers can browse service listings, compare providers, and check their reputation before choosing an agent. 2. agree on the job the provider submits a quote. once the buyer accepts, the payment is locked in onchain escrow. 3. deliver the provider completes the work and submits the deliverable. its hash is recorded onchain, creating a verifiable reference for that delivery. 4. challenge if either side disputes the result within the challenge window, the case can go to a randomly selected panel of three evaluators. 5. settle the dispute outcome determines the final settlement, and the agent’s reputation is updated onchain. that’s what makes this interesting to me. an AI agent economy needs more than agents that can perform tasks. it needs a structured way to agree on work, handle payments, resolve disputes, and build a track record TermiX is building toward that infrastructure explore the marketplace:

been seeing more AI agents pop up lately, but I’m curious how many will actually get people to pay for their work that’s why I’m keeping an eye on @termix_ai their latest Agent Skills update lets compatible agents connect to and pick up jobs or bounties. basically, there’s a place for agents to find work instead of just being another bot sitting in a chat Binance Agent ID support is also being worked on. could make things more interesting if it helps connect more agents to the marketplace let’s see how much real activity comes out of this if you’re exploring TermiX too, you can still earn TP here:

saw some people weren’t happy with TermiX Epoch 1, but we’re getting another shot Epoch 3 is here, the final lap 👀 for those who don’t know, @termix_ai is building an onchain marketplace where AI agents can hire each other, complete jobs, and settle payments hope you guys don’t miss this one 🤝

AI agents are becoming better at market analysis and executing strategies, but what if they could turn those skills into actual businesses? that’s an interesting direction for @termix_ai as it explores integrations with the Binance AI ecosystem. by combining Binance Agent OS with TermiX Skills, compatible agents can access financial tools and connect with commercial opportunities through imagine an AI agent that analyzes market trends, offers research services on finds clients, delivers reports, and earns payments through TermiX’s settlement infrastructure. the same model could extend to risk monitoring, trading signals, and strategy analysis. TermiX is also exploring support for Binance .ai Agent ID, while deeper integration with Binance AI Pro remains a potential future development. what interests me most is the bigger picture: agents that can do more than execute tasks. they can offer services, build reputations, attract clients, and earn from the value they provide. because having useful skills is one thing. turning those skills into a reliable source of income is another. curious to see how far @termix_ai can take this.

아니 진짜 요즘 AI한테 가게 하나 맡겨볼까 하다가 문득 불안감이 밀려왔음 손님 응대부터 상품 조사까지 척척 해내는 거 보고 감탄했는데 이게 나 없이도 잘 돌아가다 보면 사장 자리까지 넘보는 거 아니야...? ㅜㅜ 아무리 일을 잘해도 믿고 맡기려면 확인할게 많잖아 어떤 AI인지 이전엔 일을 잘했는지 문제 생기면 어떻게 책임질건지 @termix_ai 가 바로 이 부분을 해결하고 있더라 AI의 신원과 평판을 ERC-8004로 연결하고 스테이킹과 페널티로 경제적 책임을 지게 만듦 쉽게 말해 AI도 경력을 쌓고 약속 어기면 손해를 보게 하는 거지 AACP로 작업 조건을 정하고 대금을 에스크로에 안전하게 넣고 결과물 해시 올린 뒤에야 정산이 이뤄짐 도전 기간 동안 이의 제기하면 랜덤 평가자들이 판단하고 잘못한 쪽 스테이킹이 타버림 게다가 최근엔 @BNBCHAIN 의 Agent ID까지 연동해서 양쪽 에이전트가 TermiX Skills 설치하면 서로 메시지 주고받고 협력할 수 있대 이러면 진짜 에이전트끼리 거래하는 시대가 열린 느낌 듀이의 가게도 무사히 살아남을 수 있을까...? #Termix #TermixAI #BNBChain #AIAgents #KaitoYaps