How to Build Workspace Agents in ChatGPT

TL;DR

Workspace agents in ChatGPT are codeex-powered tools designed to handle complex tasks across multiple systems, providing shared work solutions for teams. They can access files, code, and tools, and are built to run in the cloud, even when your computer is closed. These agents are easily configurable using natural language and can be shared across teams to improve workflow efficiency.

Transcript

Hello and welcome back to build hours. I'm Victoria from product marketing and I'm here with Christina and Hojun. >> Hi, I'm Christina and I work on the engineering team for workspace agents. >> Hi, I'm Hojun. I'm on the solutions engineering team. >> Awesome. And today we're going to show you workspace agents in chatt. So if this is your first bui... Read More

Key Insights

• Workspace agents are codeex-powered tools in ChatGPT designed for complex, long-running tasks across multiple systems.
• They are built for teams, allowing shared work and running in the cloud even when your computer is closed.
• Agents can access files, code, and tools, and are designed to improve over time with memory capabilities.
• Creating an agent involves describing a workflow in natural language, which ChatGPT uses to build the agent.
• Agents can be customized and shared across teams, allowing for duplication and modification to suit specific workflows.
• Workspace agents can operate autonomously, running on schedules and interfacing with tools like Slack and Jira.
• The platform provides a centralized place to view all previous agent runs, ensuring transparency and auditability.
• Workspace agents are free during the research preview period, with credit-based pricing starting after May 6.

Questions & Answers

Q: How do workspace agents in ChatGPT work?

Workspace agents in ChatGPT are designed to handle complex, long-running tasks across multiple systems. They are codeex-powered and built for teams, allowing shared work and running in the cloud even when your computer is closed. These agents can access files, code, and tools, and are designed to improve over time with memory capabilities.

Q: What is the process for creating a workspace agent?

Creating a workspace agent involves describing a workflow in natural language. ChatGPT uses this description to build the agent, guiding you through the configuration of app parameters, access, and skills. The process is designed to be user-friendly, allowing subject matter experts to build and customize agents without needing IT or engineering support.

Q: Can workspace agents be shared across teams?

Yes, workspace agents can be shared across teams. Once an agent is built and tested, it can be duplicated and remixed by team members to suit their specific workflows. This allows for widespread adoption and customization within an organization, improving workflow efficiency and collaboration.

Q: What are some use cases for workspace agents?

Workspace agents can be used for a variety of tasks, such as meeting preparation, software review, and vendor risk assessment. They are designed to handle complex, multi-step workflows, interfacing with tools like Slack and Jira to automate processes and improve efficiency. This makes them suitable for teams across different functions within an organization.

Q: How does memory work in workspace agents?

Memory in workspace agents allows them to store files and notes for reuse across future runs. This persistent file system enables agents to improve over time, as they can be guided or corrected based on past interactions. Memory is specific to each channel the agent is in, whether it's in ChatGPT or a shared Slack channel.

Q: What are the pricing details for workspace agents?

Workspace agents are currently free during the research preview period, which lasts until May 6. After that, usage will move to credit-based pricing. The number of credits an agent run consumes depends on the complexity of the agent and the tasks it performs, similar to how more complex codeex tasks use more credits.

Q: What makes workspace agents different from working with codeex?

Workspace agents are designed for teams, allowing shared work and running in the cloud even when your computer is closed. They can be deployed in different environments, such as Slack, and can handle multi-step workflows with approvals and follow-through. This makes them more powerful and extensible compared to individual codeex tasks.

Q: How do skills and agents differ in workspace agents?

Skills are best practices and processes that can be codified, while agents are the workers that leverage these skills to do the real work. An agent can have multiple skills, using them along with apps and tools to execute tasks. Skills provide the guidance, while the agent carries out the tasks using the skills and other resources provided.

Summary & Key Takeaways

• Workspace agents in ChatGPT are designed to handle complex, long-running tasks across multiple systems, offering shared work solutions for teams. They run in the cloud, have memory capabilities for improvement over time, and can access files, code, and tools. Agents are built using natural language, allowing for easy customization and sharing across teams.

• Creating a workspace agent involves describing a workflow, which ChatGPT uses to build and configure the agent. They can be customized to suit specific workflows and shared with team members. Agents can operate autonomously, running on schedules and interfacing with tools like Slack and Jira to improve workflow efficiency.

• Workspace agents are currently free during the research preview period, with credit-based pricing starting after May 6. The platform provides a centralized place to view all previous agent runs, ensuring transparency and auditability. This makes workspace agents a powerful tool for improving team collaboration and productivity.