"Garbage In, Treasure Out": Anthropic's Chief Designer on the Product Philosophy of Cowork and the Truth Behind Its 10-Day Launch

marsbit發佈於 2026-03-31更新於 2026-03-31

文章摘要

Jenny Wen, Design Lead at Anthropic, discusses the product philosophy and development story behind Claude Cowork. She explains that Cowork was designed as a "thinking partner" for general knowledge workers, emphasizing its ability to organize information and turn raw inputs into valuable outputs—summarized as "garbage in, treasure out." Contrary to the popular narrative that Cowork was built in just 10 days, Wen reveals that the concept had been in development for nearly a year, with multiple prototypes and technical experiments. The accelerated launch was triggered by observing strong product-market fit during the Claude Code holiday period. Wen shares how her team relies heavily on iterative, informal collaboration with engineers and product managers, often bypassing detailed spec documents in favor of rapid prototyping. Cowork is now central to her workflow, used for tasks ranging from synthesizing user research to generating wireframes and kickoff presentations. She also touches on Anthropic’s flexible planning process, which focuses on short-term, adaptive vision cycles rather than long-term roadmaps, and encourages designers to embrace change—much as engineers have—by focusing on higher-level creativity and judgment.

Organized & Compiled: Deep Chao TechFlow

Guest: Jenny Wen, Cowork Design Lead

Host: Peter Yang

Podcast Source: Peter Yang

Original Title: Claude Cowork Tutorial from Cowork s Design Lead (40 Min) | Jenny Wen

Release Date: March 29, 2026

Key Points Summary

Jenny is the design lead for Cowork. She gave me an in-depth look into Anthropic's internal operations, including how she uses Cowork to design and develop products, and the real story behind the birth of Cowork. Anthropic is releasing new features almost every day, and seeing how they work is truly astonishing to me.

Highlights Summary

About Daily Work Style

  • Most of what I spend my time doing is getting the product out there. But I think it might look different than it did a year or two ago; a big part of it is just jamming (improvising collaboratively) in a very informal way with engineers, product people, and the like. Usually, it's everyone looking at a prototype together, then pointing things out and thinking about how it can evolve.

About the "Garbage In, Treasure Out" Usage Philosophy

  • I think the thing that amazes me most about Cowork is its ability to organize information. I like to call it "Garbage In, Treasure Out." It can gather information from various sources, quickly find the key points, extract valuable content, and turn it into something tangibly productive.

About the Difference Between Cowork and Claude Code

  • Apart from very detailed production code work, I now use Cowork for almost everything. For scenarios that require focusing on specific code details, I still use Claude Code. But for daily communication and collaboration, I now rely entirely on Cowork.

About the Birth Story of Cowork

  • That saying "they built it in 10 days" was actually taken out of context from some interview or media report. But the real situation is, we had been brainstorming this direction for Cowork since I joined Anthropic a year ago; we were always thinking about how to build a "thinking partner" that could help all general knowledge workers.
  • Although Claude Code was very good at handling code-related tasks, our goal was to cover all knowledge work scenarios. I think the real challenge was: How should we execute this idea? What architecture is most suitable? What is the right user experience (UX)?

About the Evolution of the Design Process

  • I still use Figma. But we don't do spec documents as often now, and they are usually not that detailed. We still do prioritization; it still exists as a document, but usually it's just a few bullet points, not some overly designed, beautiful table.

About Planning and Vision

  • The technology field we are in changes extremely fast, with new models constantly emerging and the pace of updates getting faster. Therefore, for us, even a one-year vision is somewhat unrealistic, let alone a two-to-five-year vision, because there are too many unknowns.

About the Future of Designers

  • If you feel the ground moving under your feet, it's because it is. We have to acknowledge that and learn to adapt, while also re-examining our existing ways of working with an open mind.
  • Whenever I feel my profession is being challenged, I think of my engineering colleagues. Their work has already undergone huge transformations, but they not only adapted to these changes but also met the challenges with great courage and humility, ultimately achieving more efficient and better work results. They are my source of inspiration—I tell myself, if these colleagues I highly respect can do it, so can I. They are my role models for adapting to change.

Opening

Peter Yang: Hello everyone, today I am very excited to welcome Jenny, the design lead at Anthropic. Jenny will show us how she uses Claude Cowork and Claude Code to design and release products, while also sharing the internal story of Cowork, and perhaps talking about the next steps for her product.

Jenny, what does a typical day look like for you at work? What tasks take up most of your time?

Jenny:

I don't know if there is a typical typical day, but most of what I spend my time doing is getting the product out there. But I think it might look different than it did a year or two ago; a big part of it is just jamming (improvising collaboratively) in a very informal way with engineers, product people, and the like. Usually, it's everyone looking at a prototype together, then pointing things out and thinking about how it can evolve. Sometimes it's just discussing how a feature performs, sometimes it's me implementing something myself. I think there's still a significant portion of time where I'm designing, prototyping, etc., myself, but the way design work is done now feels much looser.

Peter Yang: Basically, you generate a bunch of prototypes through Claude or something, then just jam with the engineers, give some feedback, and use prompts to have the AI improve it, right?

Jenny:

Actually, they aren't even prototypes often; they are working prototypes already built internally and running in our Claude or Cowork instances. I usually spend time using the feature, pushing the feature, seeing its capabilities, forming opinions, and the next iteration is usually me sitting down with an engineer and saying: Hey, here's what I think. These are the areas I think should change. I think there is still time where I feel iterating, polishing, and refining within design tools is still very, very important. So that part hasn't disappeared. It's just because I'm handling more projects simultaneously, so the more effective way feels very casual, very informal.

Peter Yang: I think that has always been the part I enjoyed most as a product manager or designer, pulling designers and engineers together and watching the product iterate together. So do you do less of that spec document, Figma file, planning document stuff now? Or do you just iterate on prototypes directly in code?

Jenny:

I still use Figma. But we don't do spec documents as often now, and they are usually not that detailed. Yes. We still do prioritization; it still exists as a document. Actually, it's very helpful for handing things over to security or legal teams so they understand what's being released, but usually it's just a few bullet points. Not some overly designed, beautiful beautiful table. I think our Figma files are the same.

Cowork Hands-On Demo

Peter Yang: Can you show us how you use these products, or what you use each product for respectively?

Jenny:

Sure. Let me talk about how I use Cowork. I actually have a little secret: apart from very detailed production code work, I now use Cowork for almost everything. For scenarios that require focusing on specific code details, I still use Claude Code. But for daily communication and collaboration, I now rely entirely on Cowork.

I think the thing that amazes me most about Cowork is its ability to organize information. I like to call it "Garbage In, Treasure Out." It can gather information from various sources, quickly find the key points, extract valuable content, and turn it into something tangibly productive.

For example, right now I have a folder connected that contains some user interview transcripts. Our Cowork team places great emphasis on staying closely connected with users, which is also one of the keys to our success. We do traditional user experience research (UXR), talking directly to users, and also through internal dogfooding, like we have a dedicated Slack channel for collecting feedback. Additionally, we pay attention to discussions on social media and listen to feedback from passionate users. It's because we always maintain close contact with users and can iterate quickly that we can continuously improve and achieve the results we have today.

So what I do now is, I'll tell Claude: Hey, I have this interview folder, but I'll also have Claude check social media, Reddit, and other Cowork customer reviews, and tell me what the biggest insights are. It might take a little time because it really has to process that much data and work on it. But it will do things like sometimes spawn sub-agents to process in parallel, and it will spend time searching the web.

Peter Yang: In your actual work, do you have things like weekly insight reports or something that automatically summarizes everything and sends it to you and the team?

Jenny:

Actually, we can do that directly through Cowork now. I think one of our researchers has one that gets sent out, and we also have a version that pings us in Slack. We also listen directly to internal Slack channels; we rely heavily on internal and our most power users to give us that cutting-edge feedback because internal people are really willing to be honest with you, they often push features to the limit, and they are also the easiest to follow up with.

Peter Yang: I think that's how it should happen, and I feel like in most companies teams are too siloed, but Anthropic doesn't feel like that at all.

Jenny:

I think this is also a big part of Claude Code's success—listening to the frontline users. And it's also something we did a lot at Figma, a lot of internal dogfooding. Because especially when it comes to interaction design and polishing those details, internal people will really poke at those details, while external users often give feedback more like "does it fit their user flow," so it provides a completely different level of feedback.

User Boundaries: Cowork vs Claude Code

Peter Yang: I know that marketing, product managers at Anthropic are now basically using Claude Code to do things, especially since Cowork became available internally. How do you view the different types of usage scenarios? Or how do people use Cowork and Claude Code?

Jenny:

We've noticed that Cowork's overall application is gradually expanding and is starting to be used in some scenarios similar to what the early power users of Claude Code were trying. Remember when we first started developing Cowork, the internal sales team was a major source of information for us. A few of them were heavy users of Claude Code, using it to generate lead lists, write call scripts, etc. When I first saw these use cases, I was very surprised because I hadn't even thought Claude Code could be used for these tasks at the time. And now, these users have almost completely switched to Cowork, and even their colleagues have started using Cowork frequently.

It's because there's a nice UI now, so I think that's all it really needed. And part of it is also that it's very close to the other work they're doing—they were already using the chat feature, and they can continue using Claude Code from this desktop app, so I think it fits their existing workflow better than opening a command line.

Full Process from Insights to Executable Artifacts

Jenny:

Here there are seven different themes, and they are different every week. I can basically just tell it: Help me create this document X, and it's already automatically saved in a folder on my computer. I can also launch two parallel tasks simultaneously. For example, I can say: These insights are great, but based on these, what product features should I actually build? Then I can do another thing in parallel—based on the insight document you just helped me with, turn this content into a presentation I can share with the team at the kickoff this week.

But from here I can even start the design process—it will give me various feature options. From there I can even have Claude help me create some wireframes for these features. It might give me a bunch of different options, I can take them into Figma to really refine them, or take them into Claude Code to make them into real things using our actual design system components, and start from there.

Also what I can do is, set both of these up as scheduled tasks. So I would probably have it help me schedule this task to run automatically every Monday at 10 AM. So every Monday at 10 AM I would start the week with this presentation, with three or four different product ideas, to kick off the week. It compresses the iteration cycle from feedback to tangible things or ideas the team can see very tightly, helping us iterate on the product quickly and make it better fast.

Peter Yang: Everything is about iteration, everything is about iteration. I've gotten lazy now too, I always let the AI do the first version, then I react to it.

Jenny:

Yes. So if you really want me to organize these insights into some kind of feature prioritization from scratch, it would take much longer now than before.

I operate the same way. For example, with these podcast notes you sent me, I have a personal notes folder with 1:1 meeting contents, random thoughts, etc., and I just say: Read my personal notes, help me think of the talking points for this podcast, and help me think about what I want to say here. Of course I won't read it verbatim, but it really helps me open up my thinking, helps me evolve my thoughts, rather than getting stuck.

Skills & Personal Knowledge Base

Peter Yang: What skills do you use? Or do you have personal dedicated skills for making these documents and slides?

Jenny:

We have a few internal skills specifically for making documents and slides because it helps us keep brand consistency. I don't really have a personal skill library; most of the time I borrow existing internal skills and use them for different purposes.

Peter Yang: For example, I have a writing skill that tells the AI not to use those AI slop words.

Jenny:

But actually I find that now, using Cowork's folders—I have all my personal notes, etc., in there—the way it understands me through these folders is already very useful for me. I feel less and less need for memory and skills instead. Of course I still think skills have their applicable scenarios, but for my current use cases, I personally feel the need isn't that great.

Peter Yang: Is it because it automatically updates its memory based on your conversations every day?

Jenny:

Yes, it's basically a memory I maintain myself because I'm always taking notes in it.

Team Collaboration Nodes

Peter Yang: So at what point in the whole process do you bring the team in? Or do you iterate with the AI and then switch back and forth iterating with the team, or how does that work?

Jenny:

I mean, things like actual UXR interviews, that's something I wouldn't do myself—either the product manager, or a researcher on the team, or someone else on the team will do it. And then through this, you just share the artifact, pull them in, and this can become the basis for how the team operates.

Our team, at least, is quite bottom-up and democratic, so how we operate is, we give the insights and goals to everyone, and then everyone goes off and makes prototypes, tries things, ideas come from everywhere. It's not me as the designer coming up with all the solutions, but "Hey, here are the insights. This is the goal we're trying to achieve this month, how do we all get there together?"

I think with this, we still don't hand everything over to Claude to do. We still rely on ourselves to do a lot of the judgment, and our ability to manage and decide what to actually build and do.

Peter Yang: When people talk about taste and judgment online, I think the way these abilities are cultivated is actually by continuously getting a lot of product feedback from both inside and outside. In this process, you gradually develop an intuition, an ability to detect where things are wrong and need fixing. Because you are listening to and processing this feedback every day, over time, you develop a keen judgment for problems.

Jenny:

As for design, one feature of Claude is that it can generate wireframe-like sketches and provide multiple design options. As a designer, I really like this approach. Even if these sketches aren't very high-fidelity, they allow me to visually see different possibilities without having to rely entirely on my own imagination. This approach helps me decide on the next design direction faster.

So, I think having Claude directly generate these initial options can save me the time and effort of manually creating sketches. From these options, I will choose a direction and start iterating on a small scale. Next, I might code this direction into a preliminary prototype, and then continue optimizing and refining the design based on that.

The True Story of Cowork's Birth

Peter Yang: Let's talk about how Cowork was born. There are many stories online about it being built in 10 days, but there must have been a lot of iteration before that, right?

Jenny:

That saying "they built it in 10 days" was actually taken out of context from some interview or media report, and people just kept discussing that point. But the real situation is, we had been brainstorming this direction for Cowork since I joined Anthropic a year ago; we were always thinking about how to build a "thinking partner" that could help all general knowledge workers. Although Claude Code was very good at handling code-related tasks, our goal was to cover all knowledge work scenarios. I think the real challenge was: How should we execute this idea? What architecture is most suitable? What is the right user experience (UX)?

Over the past year, we tried many different prototype designs, some ideas were even more ambitious than the current goal. We also conducted many technical experiments, testing various AI agent frameworks, but some of these attempts were not successful. Eventually, we gradually settled on the current direction. We referenced prototypes developed by the lab team, and also studied prototypes built by our own product team. In the end, timing and execution became key, like lightning striking the target.

When we decided to release this product, the whole process was very fast—from "we should release" to "the product is live," it only took 10 days. This was mainly because we saw its potential during the Claude Code holidays. During the holidays, many people finally had time to try Claude Code, and even some non-technical users started using it, like using it to parse podcast transcripts or perform complex data analysis. We found that Claude Code's agent framework was starting to show early product-market fit even among non-technical users. Actually, we already had a working prototype internally, originally planned for release a bit later, but this feedback made us realize "now is the best time." So, we decided to seize this opportunity, which led to those crazy 10 days.

Peter Yang: If I understand correctly, over the past year you shared many prototypes internally on Slack, collected a lot of feedback, and finally settled on a viable prototype. Then, because you saw market demand for it, you did a quick sprint and launched the product.

Jenny:

That's right, that's roughly it. We originally planned to launch in a few more weeks, but at that time we felt "now is the best time." This also prompted us, under time pressure, to narrow the product's scope to a more realistically feasible level, and we invested all our energy and resources, ultimately succeeding in the launch.

Early Design Iteration: From Workflow Tool to Minimalist Chat

Peter Yang: Can you share some experiences about the early iterations, or show some things that were in development?

Jenny:

Sure. I specifically gathered some early screenshots to show our design thinking and iteration process at the time.

Earlier this year, we had an early prototype, which I collaborated on with another designer. At that time, we tried to make the tool more task-oriented or workflow-oriented. Because we were worried about whether users would understand, using a product like Cowork, whether they could complete certain specific tasks, or achieve some clear outcomes, like creating a dashboard, or integrating data from different sources. So, at that time, we designed the user interface very structured, almost like a workflow tool—like "add these contents, these are inputs, these are outputs." And the chat function was placed in a secondary position.

But it felt like it took many steps to complete. In this era of 2025, why are we still making it so complicated? Why not just let Claude handle it?

This was an early design direction for us, but later we decided to change our approach, make it simpler, like a chat box. We tried to guide users towards more specific goals this way, like analysis or document generation. We also designed a functional prototype—users click and see various options, each with buttons to adjust, like the length of the document, or choose the document type, like a memo or presentation, but this design ultimately made users feel too complex and oppressive.

So through multiple explorations and attempts, we were always trying to find a balance: should we define the usage scenarios more explicitly, or maintain a free-form style like a chat box.

Eventually, the version we released a few weeks ago is what it is now. We had tried an almost "wizard-like" user experience, where users would click and see prompts, like "create a document, three to five pages long," etc.

At that time, we also added many elements to the interface, hoping to make it look different from a normal chat box. But later we found that this design made the interface seem too complex, with too much visual competition. So, we decided to simplify the design and removed most of the unnecessary elements.

The user interface you see now has been greatly simplified. We removed heavy sidebars, made it closer to a traditional chat box, but made some changes on the homepage to make it look more like a "to-do list" shared by me and Claude, rather than a chat tool full of complex suggestions and guidance.

Peter Yang: Maybe in the future it could support multiple agents, and you could drag tasks on it to manage workflows.

Jenny:

Maybe that's a possibility in the future. But I want to emphasize, the UI was completely different about four or five weeks ago; we have been constantly learning, exploring what design works best, what doesn't work so well, while trying to find the best way to present this technology to users.

Differentiation Positioning of Cowork and Claude Code

Peter Yang: While using Claude Code, I often share some feedback on Twitter. It has many slash commands built-in, requiring users to learn them bit by bit. This experience is a bit like a "treasure hunt" at Costco; you never know what new feature you'll discover.

But for newcomers, this approach isn't very friendly. It's more like a game; as you use it more, you gradually become familiar and master it. I feel Cowork might be trying to explore a middle ground between ordinary chat tools and Claude Code. It doesn't hide all the features, while also being able to guide users to use it better in some way.

Jenny:

Yes. Cowork still supports using slash commands, but they are not the primary interaction method. I personally feel that Cowork is at least a tool for professionals. We've observed that many users are already using it in very power-user ways, and a community of power users has emerged. These users are usually willing to spend time learning more complex functions, like creating their own skills, sharing with teams, or using shorthand commands.

However, our goal is to make these functions secondary interaction methods, not mandatory learning. That is, even if users don't know all the commands, they can still use Cowork easily. We want the interaction between users and Claude to be natural and intuitive, not something that must be done by remembering a series of commands.

Planning Process and Vision

Peter Yang: What is Anthropic's planning process like? Do you do annual planning and goal setting? Or do you rely more on prototyping and constant experimentation?

Jenny:

Our planning method is different each time. On my team, we do monthly planning. We have a spreadsheet, at least for the Cowork part, listing up to about 12 tasks, which are our highest priorities (P0). Each task has a directly responsible individual (DRI), and we check weekly: Are we still on the right track? We also do some quarterly or half-year planning, usually where a lead points out: "I think we should move in this direction, these are the things we need to focus on." But these plans aren't strict to the point of having to execute specific projects. It's more about providing an overall direction for the team, so it's relatively flexible.

Peter Yang: Relatively flexible, right? It's interesting, I find the most innovative companies often do less annual planning and instead rely more on constant iteration and learning from users. In your career, have you ever done something like a North Star vision deck? Do you find those useful?

Jenny:

I have done one, I did a North Star vision deck last year. I think vision does have its value; it points the team in a direction and helps keep us clear about the work ahead. However, because the technology field we are in changes so rapidly, with new models constantly emerging and the update pace getting faster, for us, even a one-year vision is somewhat unrealistic, let alone a two-to-five-year vision, because there are too many unknown factors.

However, the real role of a vision is to guide everyone in the same direction, especially in an environment where everyone can freely build various projects. So I now think the time horizon for a vision is at most three to six months, and it can be presented as a document. I feel when a vision is visual, it's more impactful. This is also the huge value of design—being able to integrate various elements and tell a coherent story over a specific period. Of course, a vision can also be a prototype, not just a static deck. It can help us coordinate work between teams, especially when we have five teams working on very similar or potentially conflicting projects. Design can help these ideas align through curation and show us a path towards an ideal user experience, rather than a fragmented experience.

Peter Yang: So, do you have product manager reviews, or reviews for relevant people? Are these reviews formal, or do they also participate in prototyping?

Jenny:

We do have reviews, but not like at some companies I've been at where every feature needs a review. Our reviews are mainly for those larger, higher-priority projects. The purpose of the review is not to spend a lot of time preparing, but to increase project visibility and get feedback. If there are cross-team, company-impacting important projects, we will do these reviews.

Advice for Designers: How to Find Your Place in the AI Era

Peter Yang: So, for those designers who feel their professional environment is changing rapidly, what advice do you have? Should they start learning to submit PRs (Pull Requests)? Or should designers adopt other ways to adapt?

Jenny:

If you feel the ground moving under your feet, it's because it is. We have to acknowledge that and learn to adapt, while also re-examining our existing ways of working with an open mind. I think the impact on designers is particularly significant right now, especially because we are in the second wave of this trend. Some other professional roles have already undergone similar transformations, and now it's our turn. At the same time, our design tools are also constantly evolving.

Whenever I feel my profession is being challenged, I feel a bit uneasy, like "Oh my god, my job is changing so much, people might not value my work as they used to." But at such times, I think of my engineering colleagues. Their work has already undergone huge transformations, but they not only adapted to these changes but also met the challenges with great courage and humility, ultimately achieving more efficient and better work results. They are my source of inspiration—I tell myself, if these colleagues I highly respect can do it, so can I. They are my role models for adapting to change.

Peter Yang: In a way, these changes free designers from a lot of tedious repetitive labor, like not having to spend time adjusting various boxes, right? So you can put more energy into higher-level thinking and creative work.

Jenny:

Exactly, or these changes allow us to complete more work. For example, when I see my engineering colleagues can now complete a full feature in just a few days, whereas it might have taken weeks before, I find it truly astonishing. So, yes, this change also brings more possibilities.

相關問答

QWhat is the core product philosophy of Cowork as described by Jenny Wen?

AThe core product philosophy of Cowork is 'garbage in, treasure out,' which refers to its ability to take information from various sources, quickly identify key points, extract valuable insights, and transform them into productive outcomes.

QWhat is the real story behind the development of Cowork, as opposed to the 'built in 10 days' narrative?

AThe 'built in 10 days' narrative was a snippet taken from an interview or media report. The reality is that the direction for Cowork had been in the works since Jenny joined Anthropic a year prior. The team had been exploring how to build a 'thinking partner' for general knowledge workers. The 10-day period refers to the final push to launch the product after seeing strong market demand, not the entire development process.

QHow does Jenny Wen describe the use cases for Cowork versus Claude Code?

AJenny uses Cowork for almost everything except very detailed production code work, for which she still uses Claude Code. For daily communication and collaboration, she relies entirely on Cowork. She notes that Cowork's application is expanding and is being used for scenarios that were previously the domain of advanced Claude Code users, such as sales teams generating lead lists and call scripts.

QHow has the design process at Anthropic evolved with the use of tools like Cowork?

AThe design process has become less formal and more iterative. They no longer frequently create detailed specification documents. Priority documents often consist of just a few bullet points instead of over-designed tables. Designers spend more time jamming informally with engineers and product people, looking at prototypes, and iterating quickly based on feedback. Figma is still used, but the workflow is more integrated with live prototypes and code.

QWhat advice does Jenny Wen give to designers who feel their profession is being challenged by AI?

AJenny advises designers to acknowledge that the ground is indeed shifting and to adapt with an open mind. She draws inspiration from her engineering colleagues, who have already undergone significant transformations in their work. She suggests that if engineers can adapt with courage and humility to achieve greater efficiency and better results, designers can too. She sees this change as an opportunity to focus on higher-level thinking and creative work, moving away from tedious, repetitive tasks.

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理解 SPERO:全面概述 SPERO 簡介 隨著創新領域的不斷演變,web3 技術和加密貨幣項目的出現在塑造數字未來中扮演著關鍵角色。在這個動態領域中,SPERO(標記為 SPERO,$$s$)是一個引起關注的項目。本文旨在收集並呈現有關 SPERO 的詳細信息,以幫助愛好者和投資者理解其基礎、目標和在 web3 和加密領域內的創新。 SPERO,$$s$ 是什麼? SPERO,$$s$ 是加密空間中的一個獨特項目,旨在利用去中心化和區塊鏈技術的原則,創建一個促進參與、實用性和金融包容性的生態系統。該項目旨在以新的方式促進點對點互動,為用戶提供創新的金融解決方案和服務。 SPERO,$$s$ 的核心目標是通過提供增強用戶體驗的工具和平台來賦能個人。這包括使交易方式更加靈活、促進社區驅動的倡議,以及通過去中心化應用程序(dApps)創造金融機會的途徑。SPERO,$$s$ 的基本願景圍繞包容性展開,旨在彌合傳統金融中的差距,同時利用區塊鏈技術的優勢。 誰是 SPERO,$$s$ 的創建者? SPERO,$$s$ 的創建者身份仍然有些模糊,因為公開可用的資源對其創始人提供的詳細背景信息有限。這種缺乏透明度可能源於該項目對去中心化的承諾——這是一種許多 web3 項目所共享的精神,優先考慮集體貢獻而非個人認可。 通過將討論重心放在社區及其共同目標上,SPERO,$$s$ 體現了賦能的本質,而不特別突出某些個體。因此,理解 SPERO 的精神和使命比識別單一創建者更為重要。 誰是 SPERO,$$s$ 的投資者? SPERO,$$s$ 得到了來自風險投資家到天使投資者的多樣化投資者的支持,他們致力於促進加密領域的創新。這些投資者的關注點通常與 SPERO 的使命一致——優先考慮那些承諾社會技術進步、金融包容性和去中心化治理的項目。 這些投資者通常對不僅提供創新產品,還對區塊鏈社區及其生態系統做出積極貢獻的項目感興趣。這些投資者的支持強化了 SPERO,$$s$ 作為快速發展的加密項目領域中的一個重要競爭者。 SPERO,$$s$ 如何運作? SPERO,$$s$ 採用多面向的框架,使其與傳統的加密貨幣項目區別開來。以下是一些突顯其獨特性和創新的關鍵特徵: 去中心化治理:SPERO,$$s$ 整合了去中心化治理模型,賦予用戶積極參與決策過程的權力,關於項目的未來。這種方法促進了社區成員之間的擁有感和責任感。 代幣實用性:SPERO,$$s$ 使用其自己的加密貨幣代幣,旨在在生態系統內部提供多種功能。這些代幣使交易、獎勵和平台上提供的服務得以促進,增強了整體參與度和實用性。 分層架構:SPERO,$$s$ 的技術架構支持模塊化和可擴展性,允許在項目發展過程中無縫整合額外的功能和應用。這種適應性對於在不斷變化的加密環境中保持相關性至關重要。 社區參與:該項目強調社區驅動的倡議,採用激勵合作和反饋的機制。通過培養強大的社區,SPERO,$$s$ 能夠更好地滿足用戶需求並適應市場趨勢。 專注於包容性:通過提供低交易費用和用戶友好的界面,SPERO,$$s$ 旨在吸引多樣化的用戶群體,包括那些以前可能未曾參與加密領域的個體。這種對包容性的承諾與其通過可及性賦能的總體使命相一致。 SPERO,$$s$ 的時間線 理解一個項目的歷史提供了對其發展軌跡和里程碑的關鍵見解。以下是建議的時間線,映射 SPERO,$$s$ 演變中的重要事件: 概念化和構思階段:形成 SPERO,$$s$ 基礎的初步想法被提出,與區塊鏈行業內的去中心化和社區聚焦原則密切相關。 項目白皮書的發布:在概念階段之後,發布了一份全面的白皮書,詳細說明了 SPERO,$$s$ 的願景、目標和技術基礎設施,以吸引社區的興趣和反饋。 社區建設和早期參與:積極進行外展工作,建立早期採用者和潛在投資者的社區,促進圍繞項目目標的討論並獲得支持。 代幣生成事件:SPERO,$$s$ 進行了一次代幣生成事件(TGE),向早期支持者分發其原生代幣,並在生態系統內建立初步流動性。 首次 dApp 上線:與 SPERO,$$s$ 相關的第一個去中心化應用程序(dApp)上線,允許用戶參與平台的核心功能。 持續發展和夥伴關係:對項目產品的持續更新和增強,包括與區塊鏈領域其他參與者的戰略夥伴關係,使 SPERO,$$s$ 成為加密市場中一個具有競爭力和不斷演變的參與者。 結論 SPERO,$$s$ 是 web3 和加密貨幣潛力的見證,能夠徹底改變金融系統並賦能個人。憑藉對去中心化治理、社區參與和創新設計功能的承諾,它為更具包容性的金融環境鋪平了道路。 與任何在快速發展的加密領域中的投資一樣,潛在的投資者和用戶都被鼓勵進行徹底研究,並對 SPERO,$$s$ 的持續發展進行深思熟慮的參與。該項目展示了加密行業的創新精神,邀請人們進一步探索其無數可能性。儘管 SPERO,$$s$ 的旅程仍在展開,但其基礎原則確實可能影響我們在互聯網數字生態系統中如何與技術、金融和彼此互動的未來。

85 人學過發佈於 2024.12.17更新於 2024.12.17

什麼是 $S$

什麼是 AGENT S

Agent S:Web3中自主互動的未來 介紹 在不斷演變的Web3和加密貨幣領域,創新不斷重新定義個人如何與數字平台互動。Agent S是一個開創性的項目,承諾通過其開放的代理框架徹底改變人機互動。Agent S旨在簡化複雜任務,為人工智能(AI)提供變革性的應用,鋪平自主互動的道路。本詳細探索將深入研究該項目的複雜性、其獨特特徵以及對加密貨幣領域的影響。 什麼是Agent S? Agent S是一個突破性的開放代理框架,專門設計用來解決計算機任務自動化中的三個基本挑戰: 獲取特定領域知識:該框架智能地從各種外部知識來源和內部經驗中學習。這種雙重方法使其能夠建立豐富的特定領域知識庫,提升其在任務執行中的表現。 長期任務規劃:Agent S採用經驗增強的分層規劃,這是一種戰略方法,可以有效地分解和執行複雜任務。此特徵顯著提升了其高效和有效地管理多個子任務的能力。 處理動態、不均勻的界面:該項目引入了代理-計算機界面(ACI),這是一種創新的解決方案,增強了代理和用戶之間的互動。利用多模態大型語言模型(MLLMs),Agent S能夠無縫導航和操作各種圖形用戶界面。 通過這些開創性特徵,Agent S提供了一個強大的框架,解決了自動化人機互動中涉及的複雜性,為AI及其他領域的無數應用奠定了基礎。 誰是Agent S的創建者? 儘管Agent S的概念根本上是創新的,但有關其創建者的具體信息仍然難以捉摸。創建者目前尚不清楚,這突顯了該項目的初期階段或戰略選擇將創始成員保密。無論是否匿名,重點仍然在於框架的能力和潛力。 誰是Agent S的投資者? 由於Agent S在加密生態系統中相對較新,關於其投資者和財務支持者的詳細信息並未明確記錄。缺乏對支持該項目的投資基礎或組織的公開見解,引發了對其資金結構和發展路線圖的質疑。了解其支持背景對於評估該項目的可持續性和潛在市場影響至關重要。 Agent S如何運作? Agent S的核心是尖端技術,使其能夠在多種環境中有效運作。其運營模型圍繞幾個關鍵特徵構建: 類人計算機互動:該框架提供先進的AI規劃,力求使與計算機的互動更加直觀。通過模仿人類在任務執行中的行為,承諾提升用戶體驗。 敘事記憶:用於利用高級經驗,Agent S利用敘事記憶來跟蹤任務歷史,從而增強其決策過程。 情節記憶:此特徵為用戶提供逐步指導,使框架能夠在任務展開時提供上下文支持。 支持OpenACI:Agent S能夠在本地運行,使用戶能夠控制其互動和工作流程,與Web3的去中心化理念相一致。 與外部API的輕鬆集成:其多功能性和與各種AI平台的兼容性確保了Agent S能夠無縫融入現有技術生態系統,成為開發者和組織的理想選擇。 這些功能共同促成了Agent S在加密領域的獨特地位,因為它以最小的人類干預自動化複雜的多步任務。隨著項目的發展,其在Web3中的潛在應用可能重新定義數字互動的展開方式。 Agent S的時間線 Agent S的發展和里程碑可以用一個時間線來概括,突顯其重要事件: 2024年9月27日:Agent S的概念在一篇名為《一個像人類一樣使用計算機的開放代理框架》的綜合研究論文中推出,展示了該項目的基礎工作。 2024年10月10日:該研究論文在arXiv上公開,提供了對框架及其基於OSWorld基準的性能評估的深入探索。 2024年10月12日:發布了一個視頻演示,提供了對Agent S能力和特徵的視覺洞察,進一步吸引潛在用戶和投資者。 這些時間線上的標記不僅展示了Agent S的進展,還表明了其對透明度和社區參與的承諾。 有關Agent S的要點 隨著Agent S框架的持續演變,幾個關鍵特徵脫穎而出,強調其創新性和潛力: 創新框架:旨在提供類似人類互動的直觀計算機使用,Agent S為任務自動化帶來了新穎的方法。 自主互動:通過GUI自主與計算機互動的能力標誌著向更智能和高效的計算解決方案邁進了一步。 複雜任務自動化:憑藉其強大的方法論,能夠自動化複雜的多步任務,使過程更快且更少出錯。 持續改進:學習機制使Agent S能夠從過去的經驗中改進,不斷提升其性能和效率。 多功能性:其在OSWorld和WindowsAgentArena等不同操作環境中的適應性確保了它能夠服務於廣泛的應用。 隨著Agent S在Web3和加密領域中的定位,其增強互動能力和自動化過程的潛力標誌著AI技術的一次重大進步。通過其創新框架,Agent S展現了數字互動的未來,為各行各業的用戶承諾提供更無縫和高效的體驗。 結論 Agent S代表了AI與Web3結合的一次大膽飛躍,具有重新定義我們與技術互動方式的能力。儘管仍處於早期階段,但其應用的可能性廣泛且引人入勝。通過其全面的框架解決關鍵挑戰,Agent S旨在將自主互動帶到數字體驗的最前沿。隨著我們深入加密貨幣和去中心化的領域,像Agent S這樣的項目無疑將在塑造技術和人機協作的未來中發揮關鍵作用。

688 人學過發佈於 2025.01.14更新於 2025.01.14

什麼是 AGENT S

如何購買S

歡迎來到HTX.com!在這裡,購買Sonic (S)變得簡單而便捷。跟隨我們的逐步指南,放心開始您的加密貨幣之旅。第一步:創建您的HTX帳戶使用您的 Email、手機號碼在HTX註冊一個免費帳戶。體驗無憂的註冊過程並解鎖所有平台功能。立即註冊第二步:前往買幣頁面,選擇您的支付方式信用卡/金融卡購買:使用您的Visa或Mastercard即時購買Sonic (S)。餘額購買:使用您HTX帳戶餘額中的資金進行無縫交易。第三方購買:探索諸如Google Pay或Apple Pay等流行支付方式以增加便利性。C2C購買:在HTX平台上直接與其他用戶交易。HTX 場外交易 (OTC) 購買:為大量交易者提供個性化服務和競爭性匯率。第三步:存儲您的Sonic (S)購買Sonic (S)後,將其存儲在您的HTX帳戶中。您也可以透過區塊鏈轉帳將其發送到其他地址或者用於交易其他加密貨幣。第四步:交易Sonic (S)在HTX的現貨市場輕鬆交易Sonic (S)。前往您的帳戶,選擇交易對,執行交易,並即時監控。HTX為初學者和經驗豐富的交易者提供了友好的用戶體驗。

1.4k 人學過發佈於 2025.01.15更新於 2025.03.21

如何購買S

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