Claude CoWork: Asynchronous AI Workflows for Non-Technical Users - Episode Hero Image

Claude CoWork: Asynchronous AI Workflows for Non-Technical Users

AI & I · · Listen to Original Episode →
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TL;DR

  • Claude Cowork enables non-technical users to engage in asynchronous AI workflows, moving beyond immediate response cycles to delegate longer, complex tasks like data analysis and document drafting.
  • The separation of Claude Cowork into its own tab signals an experimental playground for rapid iteration, allowing Anthropic to gather user feedback on novel agentic capabilities before broader integration.
  • Claude Cowork's local execution on the user's computer, distinct from cloud-based chat, enables more aggressive agentic capabilities and provides a foundation for future local-first AI applications.
  • Skills serve as the primary hackable surface for Claude Cowork, allowing users to personalize the AI's behavior through custom prompts and scripts, mirroring the composability found in developer tools.
  • The "ask user question" UI in Claude Cowork, while having some rough edges, represents a novel interface for agentic applications, facilitating interactive task completion and user guidance.
  • Claude Cowork's ability to perform tasks like analyzing a Twitter feed or auditing a calendar, which previously required specialized APIs or manual effort, democratizes access to complex data processing for general users.
  • The development of Claude Cowork in just over a week highlights Anthropic's rapid iteration cycle, emphasizing shipping early and often to co-create product direction with users.

Deep Dive

Claude CoWork represents a significant evolution in AI interaction, moving beyond immediate, turn-based chat to an asynchronous, task-oriented workflow for non-technical users. This new paradigm, built rapidly by Anthropic, aims to democratize the capabilities previously confined to developers using Claude Code, enabling deeper, longer-running tasks directly on a user's computer. The core innovation lies in its "agent-native architecture," where an AI agent directly interfaces with the user's applications, mirroring how developers leverage tools but with a user-friendly interface.

The implications of this asynchronous approach are profound. Unlike traditional chat where users must wait for a response before sending another message, CoWork allows users to queue tasks, enabling parallel processing and a more fluid interaction model. This is critical for complex operations like in-depth research, data analysis, or extensive document drafting, which can now be initiated and left to run without constant user oversight. Furthermore, the direct integration with the user's machine, facilitated by features like Chrome connectors, allows for real-world task execution beyond simple text generation, such as analyzing website data or auditing calendar activities over extended periods. This shifts the user's role from an immediate director to a task delegator and reviewer, fundamentally changing how knowledge workers can leverage AI for complex, multi-step processes.

The introduction of "Skills"--customizable prompts and scripts--provides a crucial layer of hackability, allowing users to personalize CoWork's behavior and integrate their specific workflows. This composability is key to unlocking emergent capabilities, as users can combine existing tools and prompts in novel ways, leading to applications unforeseen by the developers. While currently in a research preview with some UI rough edges, CoWork's potential to democratize complex AI-driven tasks suggests a future where AI assistants are not just conversational partners but proactive agents capable of executing substantial work asynchronously, redefining productivity for a broader user base.

Action Items

  • Audit Claude Co Work's Chrome connector: Identify 3 potential security vulnerabilities (e.g., data leakage, unauthorized access) and implement 2 mitigation strategies.
  • Design a feedback loop: Establish a system to collect and categorize user feedback on Claude Co Work's UI/UX for 5 key features within a 2-week sprint.
  • Evaluate Claude Co Work's skill system: Test the integration of 3 custom skills with existing workflows to identify potential performance bottlenecks or compatibility issues.
  • Draft a runbook template: Define 5 required sections (e.g., setup, common failures, rollback) for agent-native application development to prevent knowledge silos.

Related Episodes

Key Quotes

"If you're a non-technical person, you're used to a world where you send a prompt and get a response within a couple of minutes. Once you send a prompt or a chat, you can't do anything else with that AI. This is built for working with your AIs in an asynchronous way."

The speaker explains that traditional AI interactions are synchronous, requiring immediate attention. This new approach, Claude Cowork, is designed for asynchronous work, allowing users to send prompts and then disengage without waiting for an immediate response. This shift aims to better integrate AI into workflows by enabling users to multitask.

"This new Claude Co Work app is a really good example of agentic architectures, which means at the bottom of the app, instead of having software that works by deterministic rules, you have an agent, and the agent is wired up to the UI of the app."

The speaker introduces the concept of "agentic architectures" as the foundation for Claude Cowork. They clarify that instead of relying on predefined rules, the application is driven by an agent that is directly connected to the user interface. This means the AI agent interprets user actions and responds dynamically, forming the core of its functionality.

"I think you can really think of Co Work as being like chat that has access to your computer and runs for a long time, which is essentially Claude Code but just less intimidating."

The speaker draws a comparison between Claude Cowork, regular chat interfaces, and Claude Code. They describe Cowork as an enhanced chat experience that can access the user's computer and operate for extended periods. This positioning suggests it bridges the gap between user-friendly chat and the more technical Claude Code, making advanced capabilities accessible to a broader audience.

"This is built for working with your AIs in an async way. Everything is set up, like the idea of a task, the idea of having a queue. This is all set up so that you can say, 'Go do something,' and then not think about it for a while and then come back, which is very different from Claude, where the normal Claude app, you're trying to get an answer pretty quick."

The speaker reiterates the asynchronous nature of Claude Cowork. They highlight features like "tasks" and a "queue" system that facilitate this async workflow. This design allows users to delegate tasks to the AI and return to them later, contrasting with the typical immediate-response model of standard chat applications.

"The reason we broke it out is because we want to be pretty transparent that this separate thing is a construction site, right? That we're sort of letting you into our kitchen, one to like work together with you. We want to ship almost every single day some new features, some bug fixes, try out some things. So this separate tab is fairly experimental."

Felix Rieseberg from Anthropic explains the rationale behind creating a separate tab for Claude Cowork. He describes it as an experimental "construction site" where users are invited to collaborate on its development. This transparency and rapid iteration approach indicate Anthropic's strategy to build and refine the product in close partnership with its users.

"Skills is probably the primary hackable surface that I'm exploiting right now."

Felix Rieseberg identifies "skills" as the most significant area for customization and extension within Claude. He explains that instead of solely relying on pre-built tools or complex harnesses, he focuses on creating skills, which are essentially instructions or guidelines that Claude can follow. This highlights skills as a key interface for users to personalize and expand the AI's capabilities.

Resources

External Resources

Books

  • "The Outsider" - Mentioned as a book the speaker was reading for a book they were writing.

Articles & Papers

  • Agent Native Architectures - Mentioned as a guide published by "every" that explains how to build agent native architectures.

People

  • Felix - Member of the technical staff at Anthropic who built Claude CoWork.
  • Karen - Guest on the stream, also an "every" team member.
  • Dan - Mentioned in relation to his writing style and as a potential user of Claude CoWork.
  • Katie Parrott - Writer for "every" who wrote an article about Claude CoWork and an article about Opus 45.
  • Boris - Mentioned as someone who pushes for shipping early and iterating on products.
  • Barry - Mentioned as the "skills person" at Anthropic who came up with skills.
  • Anthony Morris - Member of Anthropic who commented on the stream.

Organizations & Institutions

  • Anthropic - Developer of Claude CoWork.
  • Every - Platform where the discussion is taking place, providing AI ideas, apps, and training.
  • NFL (National Football League) - Mentioned in the context of sports analytics.
  • New England Patriots - Mentioned as an example team for performance analysis.
  • Pro Football Focus (PFF) - Mentioned as a data source for player grading.
  • Google - Mentioned in the context of search interfaces and product development.
  • Microsoft Excel - Used as an example of a general-purpose product with power workflows.
  • Slack - Mentioned as a platform where lessons were learned about user adoption.
  • PostHog - Analytics platform used to gather data on button clicks.
  • X (formerly Twitter) - Platform whose feed was analyzed by Claude CoWork.

Tools & Software

  • Claude CoWork - New application from Anthropic designed for non-technical users to work with AI asynchronously.
  • Claude Code - Anthropic's tool for developers, which Claude CoWork is compared to.
  • Claude AI - The underlying AI model used in Claude CoWork.
  • ChatGPT - Mentioned in comparison to Claude for interacting with guides.
  • Chrome - Browser that Claude CoWork can connect to and use.
  • Gmail - Mentioned as a service Claude CoWork has a connector for.
  • Google Calendar - Mentioned as a service Claude CoWork has a connector for.
  • Proof - A markdown editor built by Dan using Claude Code.
  • Monologue - An "every" app for speech-to-text.
  • Sparkle - An "every" app for file organization.
  • Spyro - An "every" app for writing assistance.
  • Cora - An "every" app for email assistance.
  • Whisperflow - Mentioned as a similar tool to Monologue.
  • GCC - A compiler mentioned in the context of tools.
  • Vst Plugin - A type of audio effect plugin discussed in the context of development.
  • Blender Studio - Software used to view an STL file.

Websites & Online Resources

  • Every.io - Website mentioned in relation to competitive company analysis.

Other Resources

  • Agentic Architectures - A concept discussed as the underlying architecture of Claude CoWork.
  • Async Work - A way of working with AI that Claude CoWork facilitates.
  • Skills - A feature within Claude that allows for personalized AI experiences and prompt injection.
  • Compound Engineering - A pattern discussed in relation to applying to Claude CoWork.
  • Vibe Checks - A format used by "every" to review new AI products and models.
  • Taxonomy - A classification system that Claude CoWork can construct.
  • Provenance Tracking - A feature being built in "every proof".
  • Swiss Design - An aesthetic style mentioned in relation to creating a chair design.
  • STL File - A file format for 3D models.
  • AGI (Artificial General Intelligence) - Mentioned as a benchmark for AI capabilities, specifically in editing Google Docs.
  • Opus 45 - A new model from Anthropic that significantly changed AI capabilities.
  • GPT5 - Mentioned in comparison to Opus 45.
  • Capability Blindness - A phenomenon where users dismiss AI capabilities based on past experiences.
  • Paradigm Shift - A significant change in thinking or approach, used to rate AI product launches.

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