Original author: Haotian (X: @@tme l0 211)
After waking up from a sleep, many friends asked me to read manus, which is said to be a truly universal AI agent in the world, capable of independent thinking, planning and executing complex tasks, and delivering complete results. It sounds very cool, but apart from the voices of many friends who are anxious about losing their jobs, what will it bring to the explosion of web3 DeFai scenarios? Here are my thoughts:
1) About a month ago, OpenAI launched a similar product, Operator. AI can independently complete tasks including restaurant reservations, shopping, ticket booking, and takeout ordering in the browser. Users can supervise visually and take over control at any time.
Not many people discuss the emergence of this agent because it is a single model-driven framework called by the tool. Once users think that key decisions still need intervention, they lose the idea of relying on it to perform tasks.
2) Manus seems to be not much different on the surface, except that it has many more application scenarios, including screening resumes, researching stocks, purchasing real estate, etc., but in fact the difference lies in the framework and execution system behind it. Manus is driven by a multimodal large model and innovatively adopts a multi-signature system.
In short, AI needs to imitate the PDCA cycle of human execution (plan-do-check-act), which will be completed by multiple large models working together. Each model focuses on a specific link, which can reduce the decision-making risk of a single model in executing tasks and improve execution efficiency. The so-called multi-signature system is actually a decision verification mechanism for multi-model collaboration, which ensures the reliability of decision-making and execution by requiring joint confirmation from multiple professional models.
3) In this comparison, the advantages of manus are clearly highlighted, and the series of operation experiences shown in the video demo really give people an extraordinary experience. But objectively speaking, Manuss iterative innovation of Operator is just the beginning and has not yet reached a subversive revolutionary significance.
The key point lies in the complexity of the task execution and the definition of the fault tolerance and success rate of the large model after the non-standard user input prompt enters. Otherwise, following this set of innovations, can the DeFai scenario of web3 be maturely applied immediately? Obviously, it cannot be done yet:
For example, in the DeFai scenario, for an agent to execute a transaction decision, an Oracle-layer agent is required to collect and verify on-chain data, perform data integration and analysis, and monitor on-chain prices in real time to capture transaction opportunities. This process poses great challenges to real-time analysis. It is possible that a transaction opportunity that was useful a second ago will no longer exist after the Oracle large model is transmitted to the transaction execution agent (arbitrage window).
This actually exposes the biggest weakness of this type of multimodal large model in making execution decisions: how to connect to the Internet, touch the chain, retrieve and analyze real-time data, analyze transaction opportunities from it, and then capture transactions. The Internet environment is actually not bad. The order prices of many e-commerce websites do not change in real time, which is not easy to cause huge dynamic balance problems for the entire multimodal collaboration. If it is on the chain, such challenges exist almost all the time.
4) Therefore, the emergence of manus will indeed cause a wave of anxiety in the web2 field. After all, many clerical and information processing jobs with high repetitiveness may face the risk of being replaced by AI. But let them be anxious.
We need to objectively understand the role of web3 in promoting DeFai application scenarios:
We have to admit that it is of great significance. After all, the LLM OS and Less Structure more intelligence concepts it proposed, especially the multi-signature system, will provide great inspiration for web3 to expand the combination of DeFi and AI.
This actually corrects a major misunderstanding of most DeFai projects. Dont rely on a large model to achieve complex goals such as autonomous thinking and decision-making of AI Agents. This is simply not practical in financial scenarios.
The realization of the true DeFai vision requires solving complex problems such as the upper limit of the capabilities of single AI models, atomicity assurance of multimodal interactive collaboration, unified resource scheduling and control of multimodal systems, system fault tolerance and fault handling mechanisms, etc.
For example: Oracle layer Agent is responsible for collecting and analyzing on-chain data and monitoring prices to form an effective data source;
The decision-making agent analyzes and assesses risks based on the data fed by Oracle, and formulates a set of decisions and action plans;
The execution layer agent executes according to the various solutions given by the decision-making layer and takes into account the actual situation, including gas fee optimization, cross-chain status, transaction sorting conflicts, etc.
Only when this series of agents are powerful at the same time and a huge system framework is established, a true DeFai revolution will be launched.
What is the real impact of manus on the web3 industry? It is not a technical crush, but a blow to the spirit and soul! To be honest, there are some things that have been in my heart for a long time, and I would like to take this opportunity to speak out:
1) I didn’t understand people in the web2 industry and I was dismissive of web3 AI Agent. But when web3 AI Agent was in a mess, and I saw the endless technological and application innovations in the web2 field, I had to recognize a fact. The AI + Crypto vision we uphold is not wrong, but the current web3 field is full of idiots, and there are many garbage projects that play with MEME in the name of long-term Builder to cut leeks;
2) Originally, I wanted to say that we need to give the market more confidence, and innovation is always on the way, but over time, I found that after a pile of projects came out, a bubble of tens of billions of dollars was blown up. When the bubble bursts, it will not only hurt every long-term holder of the currency, but also hurt some practitioners who may still have a little idea of building in the chaos. The continuous dump is destroying the confidence of the bottom of the industry. Not only the currency price that has returned to zero is being cleared, but also a large number of excellent teams that were originally passionate about entrepreneurship; there is no winner in the situation where bad money drives out good money!
3) We may have overestimated the innovation ability of web3 AI Agent. In a short period of time, we dreamed of AI + Crypto innovation, such as autonomy of AI Agent, independent transaction decision-making of AI Agent, embedding of AI Agent game NPC, interaction of AI Agent metaverse modeling, etc. However, we found that most of the plans and visions were utopian and self-talking, and the feasibility was not evaluated before the proposal was even put forward. As a result, the pie was drawn round and big. After a speed run, the price of the currency was smashed, and the technical vision and roadmap originally outlined were also given a shit; to be honest, forget that the big one is coming, and it is already very good to be a follower of the web2 innovation echelon.
4) I was originally very proud of the unparalleled appeal of Tokenomics in web3 and its appeal to outstanding web2 talents, but when I saw the teams behind DeepSeek, Yushu Technology, and manus, which was all over the screen today, they basically all had doctoral degrees in computer science, electronic engineering, etc. from Tsinghua University, Peking University, and the Chinese Academy of Sciences. Looking at the developer teams in the Crypto AI circle, they are either web2 developers who have lost their way in web3 to find shortcuts, or they are habitual narrative fraudsters in the web3 field who have always been a nest of snakes and rats, or they are marginal web3 developers who have technical strength but do not get the attention they deserve. In terms of talent, how can we compare the speed of innovation with web2? If pure Tokenomics coin issuance is the source of all Build power, it is also the root cause of killing everything;
5) Originally, I thought that the biggest dilemma of web3 AI Agent was time, as if time was the cure for everything. But now I know I was wrong. If the idea of underlying value creation is not reshaped, time will only bring the next bigger bubble and will not change anything. Well, now web2 has brought the iteration of multimodality to single-modality, the innovation of the concept of decision-making + action separation, and the transition of the framework operating system with LLM OS + open source combination. The framework and standards of web3, DeFai, GamFai, MetAiverse, chainization and other innovative build propositions and path directions clearly point out the direction. I am looking forward to what kind of team can be the first to break through the siege and bring a glimmer of life to web3 AI Agent.
