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

marsbitPublié le 2026-03-31Dernière mise à jour le 2026-03-31

Résumé

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.

Questions liées

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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Ce manque de transparence peut découler de l'engagement du projet envers la décentralisation—une éthique que de nombreux projets web3 partagent, privilégiant les contributions collectives plutôt que la reconnaissance individuelle. En centrant les discussions autour de la communauté et de ses objectifs collectifs, SPERO,$$s$ incarne l'essence de l'autonomisation sans désigner des individus spécifiques. Ainsi, comprendre l'éthique et la mission de SPERO reste plus important que d'identifier un créateur unique. Qui sont les investisseurs de SPERO,$$s$ ? SPERO,$$s$ est soutenu par une diversité d'investisseurs allant des capital-risqueurs aux investisseurs providentiels dédiés à favoriser l'innovation dans le secteur crypto. L'objectif de ces investisseurs s'aligne généralement avec la mission de SPERO—priorisant les projets qui promettent des avancées technologiques sociétales, l'inclusivité financière et la gouvernance décentralisée. Ces fondations d'investisseurs s'intéressent généralement à des projets qui non seulement offrent des produits innovants, mais qui contribuent également positivement à la communauté blockchain et à ses écosystèmes. Le soutien de ces investisseurs renforce SPERO,$$s$ en tant que concurrent notable dans le domaine en rapide évolution des projets crypto. Comment fonctionne SPERO,$$s$ ? SPERO,$$s$ utilise un cadre multifacette qui le distingue des projets de cryptomonnaie conventionnels. Voici quelques-unes des caractéristiques clés qui soulignent son unicité et son innovation : Gouvernance décentralisée : SPERO,$$s$ intègre des modèles de gouvernance décentralisée, permettant aux utilisateurs de participer activement aux processus de décision concernant l'avenir du projet. Cette approche favorise un sentiment de propriété et de responsabilité parmi les membres de la communauté. Utilité du token : SPERO,$$s$ utilise son propre token de cryptomonnaie, conçu pour servir diverses fonctions au sein de l'écosystème. Ces tokens permettent des transactions, des récompenses et la facilitation des services offerts sur la plateforme, améliorant ainsi l'engagement et l'utilité globaux. Architecture en couches : L'architecture technique de SPERO,$$s$ supporte la modularité et l'évolutivité, permettant une intégration fluide de fonctionnalités et d'applications supplémentaires à mesure que le projet évolue. Cette adaptabilité est primordiale pour maintenir la pertinence dans le paysage crypto en constante évolution. Engagement communautaire : Le projet met l'accent sur des initiatives dirigées par la communauté, utilisant des mécanismes qui incitent à la collaboration et aux retours d'expérience. En cultivant une communauté forte, SPERO,$$s$ peut mieux répondre aux besoins des utilisateurs et s'adapter aux tendances du marché. Accent sur l'inclusion : En proposant des frais de transaction bas et des interfaces conviviales, SPERO,$$s$ vise à attirer une base d'utilisateurs diversifiée, y compris des individus qui n'ont peut-être pas engagé auparavant dans l'espace crypto. Cet engagement envers l'inclusion s'aligne avec sa mission globale d'autonomisation par l'accessibilité. Chronologie de SPERO,$$s$ Comprendre l'histoire d'un projet fournit des aperçus cruciaux sur sa trajectoire de développement et ses jalons. Voici une chronologie suggérée cartographiant les événements significatifs dans l'évolution de SPERO,$$s$ : Phase de conceptualisation et d'idéation : Les idées initiales formant la base de SPERO,$$s$ ont été conçues, s'alignant étroitement avec les principes de décentralisation et de concentration sur la communauté au sein de l'industrie blockchain. Lancement du livre blanc du projet : Suite à la phase conceptuelle, un livre blanc complet détaillant la vision, les objectifs et l'infrastructure technologique de SPERO,$$s$ a été publié pour susciter l'intérêt et les retours de la communauté. Construction de la communauté et engagements précoces : Des efforts de sensibilisation actifs ont été entrepris pour construire une communauté d'adopteurs précoces et d'investisseurs potentiels, facilitant les discussions autour des objectifs du projet et recueillant du soutien. Événement de génération de tokens : SPERO,$$s$ a organisé un événement de génération de tokens (TGE) pour distribuer ses tokens natifs aux premiers soutiens et établir une liquidité initiale au sein de l'écosystème. Lancement de la première dApp : La première application décentralisée (dApp) associée à SPERO,$$s$ a été mise en ligne, permettant aux utilisateurs d'interagir avec les fonctionnalités principales de la plateforme. Développement continu et partenariats : Des mises à jour et des améliorations continues des offres du projet, y compris des partenariats stratégiques avec d'autres acteurs de l'espace blockchain, ont façonné SPERO,$$s$ en un acteur compétitif et évolutif sur le marché crypto. Conclusion SPERO,$$s$ se dresse comme un témoignage du potentiel du web3 et de la cryptomonnaie pour révolutionner les systèmes financiers et autonomiser les individus. Avec un engagement envers la gouvernance décentralisée, l'engagement communautaire et des fonctionnalités conçues de manière innovante, il ouvre la voie vers un paysage financier plus inclusif. Comme pour tout investissement dans l'espace crypto en rapide évolution, les investisseurs et utilisateurs potentiels sont encouragés à mener des recherches approfondies et à s'engager de manière réfléchie avec les développements en cours au sein de SPERO,$$s$. Le projet illustre l'esprit d'innovation de l'industrie crypto, invitant à une exploration plus approfondie de ses nombreuses possibilités. Bien que le parcours de SPERO,$$s$ soit encore en cours, ses principes fondamentaux pourraient en effet influencer l'avenir de nos interactions avec la technologie, la finance et entre nous dans des écosystèmes numériques interconnectés.

101 vues totalesPublié le 2024.12.17Mis à jour le 2024.12.17

Qu'est ce que $S$

Qu'est ce que AGENT S

Agent S : L'avenir de l'interaction autonome dans Web3 Introduction Dans le paysage en constante évolution de Web3 et des cryptomonnaies, les innovations redéfinissent constamment la manière dont les individus interagissent avec les plateformes numériques. Un projet pionnier, Agent S, promet de révolutionner l'interaction homme-machine grâce à son cadre agentique ouvert. En ouvrant la voie à des interactions autonomes, Agent S vise à simplifier des tâches complexes, offrant des applications transformantes dans l'intelligence artificielle (IA). Cette exploration détaillée plongera dans les subtilités du projet, ses caractéristiques uniques et les implications pour le domaine des cryptomonnaies. Qu'est-ce qu'Agent S ? Agent S se présente comme un cadre agentique ouvert révolutionnaire, spécifiquement conçu pour relever trois défis fondamentaux dans l'automatisation des tâches informatiques : Acquisition de connaissances spécifiques au domaine : Le cadre apprend intelligemment à partir de diverses sources de connaissances externes et d'expériences internes. Cette approche double lui permet de construire un riche répertoire de connaissances spécifiques au domaine, améliorant ainsi sa performance dans l'exécution des tâches. Planification sur de longs horizons de tâches : Agent S utilise une planification hiérarchique augmentée par l'expérience, une approche stratégique qui facilite la décomposition et l'exécution efficaces de tâches complexes. Cette fonctionnalité améliore considérablement sa capacité à gérer plusieurs sous-tâches de manière efficace et efficiente. Gestion d'interfaces dynamiques et non uniformes : Le projet introduit l'Interface Agent-Ordinateur (ACI), une solution innovante qui améliore l'interaction entre les agents et les utilisateurs. En utilisant des Modèles de Langage Multimodaux de Grande Taille (MLLMs), Agent S peut naviguer et manipuler sans effort diverses interfaces graphiques. Grâce à ces fonctionnalités pionnières, Agent S fournit un cadre robuste qui aborde les complexités impliquées dans l'automatisation de l'interaction humaine avec les machines, préparant le terrain pour d'innombrables applications en IA et au-delà. Qui est le créateur d'Agent S ? Bien que le concept d'Agent S soit fondamentalement innovant, des informations spécifiques sur son créateur restent insaisissables. Le créateur est actuellement inconnu, ce qui souligne soit le stade naissant du projet, soit le choix stratégique de garder les membres fondateurs sous le radar. Quoi qu'il en soit, l'accent reste mis sur les capacités et le potentiel du cadre. Qui sont les investisseurs d'Agent S ? Étant donné qu'Agent S est relativement nouveau dans l'écosystème cryptographique, des informations détaillées concernant ses investisseurs et soutiens financiers ne sont pas explicitement documentées. Le manque d'aperçus publiquement disponibles sur les fondations d'investissement ou les organisations soutenant le projet soulève des questions sur sa structure de financement et sa feuille de route de développement. Comprendre le soutien est crucial pour évaluer la durabilité du projet et son impact potentiel sur le marché. Comment fonctionne Agent S ? Au cœur d'Agent S se trouve une technologie de pointe qui lui permet de fonctionner efficacement dans divers environnements. Son modèle opérationnel est construit autour de plusieurs caractéristiques clés : Interaction homme-ordinateur semblable à l'humain : Le cadre offre une planification IA avancée, s'efforçant de rendre les interactions avec les ordinateurs plus intuitives. En imitant le comportement humain dans l'exécution des tâches, il promet d'élever l'expérience utilisateur. Mémoire narrative : Utilisée pour tirer parti des expériences de haut niveau, Agent S utilise la mémoire narrative pour suivre les historiques de tâches, améliorant ainsi ses processus de prise de décision. Mémoire épisodique : Cette fonctionnalité fournit aux utilisateurs un accompagnement étape par étape, permettant au cadre d'offrir un soutien contextuel au fur et à mesure que les tâches se déroulent. Support pour OpenACI : Avec la capacité de fonctionner localement, Agent S permet aux utilisateurs de garder le contrôle sur leurs interactions et flux de travail, s'alignant avec l'éthique décentralisée de Web3. Intégration facile avec des API externes : Sa polyvalence et sa compatibilité avec diverses plateformes IA garantissent qu'Agent S peut s'intégrer sans effort dans des écosystèmes technologiques existants, en faisant un choix attrayant pour les développeurs et les organisations. Ces fonctionnalités contribuent collectivement à la position unique d'Agent S dans l'espace crypto, alors qu'il automatise des tâches complexes en plusieurs étapes avec un minimum d'intervention humaine. À mesure que le projet évolue, ses applications potentielles dans Web3 pourraient redéfinir la manière dont les interactions numériques se déroulent. Chronologie d'Agent S Le développement et les jalons d'Agent S peuvent être encapsulés dans une chronologie qui met en évidence ses événements significatifs : 27 septembre 2024 : Le concept d'Agent S a été lancé dans un document de recherche complet intitulé “Un cadre agentique ouvert qui utilise les ordinateurs comme un humain”, présentant les bases du projet. 10 octobre 2024 : Le document de recherche a été rendu publiquement disponible sur arXiv, offrant une exploration approfondie du cadre et de son évaluation de performance basée sur le benchmark OSWorld. 12 octobre 2024 : Une présentation vidéo a été publiée, fournissant un aperçu visuel des capacités et des caractéristiques d'Agent S, engageant davantage les utilisateurs et investisseurs potentiels. Ces jalons dans la chronologie illustrent non seulement les progrès d'Agent S, mais indiquent également son engagement envers la transparence et l'engagement communautaire. Points clés sur Agent S Alors que le cadre Agent S continue d'évoluer, plusieurs attributs clés se distinguent, soulignant sa nature innovante et son potentiel : Cadre innovant : Conçu pour offrir une utilisation intuitive des ordinateurs semblable à l'interaction humaine, Agent S propose une approche nouvelle de l'automatisation des tâches. Interaction autonome : La capacité d'interagir de manière autonome avec les ordinateurs via une interface graphique signifie un bond vers des solutions informatiques plus intelligentes et efficaces. Automatisation des tâches complexes : Avec sa méthodologie robuste, il peut automatiser des tâches complexes en plusieurs étapes, rendant les processus plus rapides et moins sujets aux erreurs. Amélioration continue : Les mécanismes d'apprentissage permettent à Agent S de s'améliorer grâce à ses expériences passées, améliorant continuellement sa performance et son efficacité. Polyvalence : Son adaptabilité à travers différents environnements d'exploitation comme OSWorld et WindowsAgentArena garantit qu'il peut servir un large éventail d'applications. Alors qu'Agent S se positionne dans le paysage Web3 et crypto, son potentiel à améliorer les capacités d'interaction et à automatiser les processus représente une avancée significative dans les technologies IA. Grâce à son cadre innovant, Agent S incarne l'avenir des interactions numériques, promettant une expérience plus fluide et efficace pour les utilisateurs à travers divers secteurs. Conclusion Agent S représente un saut audacieux en avant dans le mariage de l'IA et de Web3, avec la capacité de redéfinir notre interaction avec la technologie. Bien qu'il soit encore à ses débuts, les possibilités de son application sont vastes et convaincantes. Grâce à son cadre complet abordant des défis critiques, Agent S vise à mettre les interactions autonomes au premier plan de l'expérience numérique. À mesure que nous plongeons plus profondément dans les domaines des cryptomonnaies et de la décentralisation, des projets comme Agent S joueront sans aucun doute un rôle crucial dans la façon dont la technologie et la collaboration homme-machine évolueront à l'avenir.

759 vues totalesPublié le 2025.01.14Mis à jour le 2025.01.14

Qu'est ce que AGENT S

Comment acheter S

Bienvenue sur HTX.com ! Nous vous permettons d'acheter Sonic (S) de manière simple et pratique. Suivez notre guide étape par étape pour commencer votre parcours crypto.Étape 1 : Création de votre compte HTXUtilisez votre adresse e-mail ou votre numéro de téléphone pour ouvrir un compte sur HTX gratuitement. L'inscription se fait en toute simplicité et débloque toutes les fonctionnalités.Créer mon compteÉtape 2 : Choix du mode de paiement (rubrique Acheter des cryptosCarte de crédit/débit : utilisez votre carte Visa ou Mastercard pour acheter instantanément Sonic (S).Solde :utilisez les fonds du solde de votre compte HTX pour trader en toute simplicité.Prestataire tiers :pour accroître la commodité d'utilisation, nous avons ajouté des modes de paiement populaires tels que Google Pay et Apple Pay.P2P :tradez directement avec d'autres utilisateurs sur HTX.OTC (de gré à gré) : nous offrons des services personnalisés et des taux de change compétitifs aux traders.Étape 3 : stockage de vos Sonic (S)Après avoir acheté vos Sonic (S), stockez-les sur votre compte HTX. Vous pouvez également les envoyer ailleurs via un transfert sur la blockchain ou les utiliser pour trader d'autres cryptos.Étape 4 : tradez des Sonic (S)Tradez facilement Sonic (S) sur le marché Spot de HTX. Il vous suffit d'accéder à votre compte, de sélectionner la paire de trading, d'exécuter vos trades et de les suivre en temps réel. Nous offrons une expérience conviviale aux débutants comme aux traders chevronnés.

1.4k vues totalesPublié le 2025.01.15Mis à jour le 2025.03.21

Comment acheter S

Discussions

Bienvenue dans la Communauté HTX. Ici, vous pouvez vous tenir informé(e) des derniers développements de la plateforme et accéder à des analyses de marché professionnelles. Les opinions des utilisateurs sur le prix de S (S) sont présentées ci-dessous.

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