Visual Studio Code Agents
Overview
- Ship complete coding tasks without babysitting the process, because agents autonomously research, edit, run commands, and verify their own results from a single task description
- Manage several projects in one workday by running multiple tasks at once and working in parallel across different codebases
- Start and finish work wherever you are, since agents operate in VS Code, command line interfaces, browsers, and on mobile devices
- Match the workflow to the task by switching freely between high-level task delegation and a code-first flow
- Connect any AI model from any provider, including OpenAI, Anthropic, and Google, using Native MCP support with your own API key
- Keep every team's standards baked in by creating custom agent personas tuned to your conventions and most frequent tasks
- Never lose track of running work with a unified view for managing and monitoring all agent sessions
- Handle GitHub work without leaving your terminal, where agents engage issues and pull requests, plan changes, edit across files, and run commands
- Scale from a laptop to the cloud on demand, choosing local or cloud execution for GitHub Copilot, custom, and third-party agents
- Edit across multiple files and directories without losing context, so changes stay consistent across the whole codebase
Pros & Cons
Pros
- Open platform
- Supports multiple agents
- Supports GitHub Copilot
- Autonomous task planning
- Editing, running commands, research capabilities
- Checks own results
- Runs multiple tasks simultaneously
- Parallel work across projects
- Operates in various environments
- Operates in VS Code
- CLI operation
- Browser-based operations
- Mobile app operation
- Tasks can be initiated anywhere
- High-level tasks and code-first flow options
- Native MCP integration
- Can run locally or cloud-based
- Scalability support
- Allows custom agent personas
- Unified viewing of agent sessions
- Workflow management
- GitHub-native agent operation
- Tasks planning
- Editing across files
- Command-line flow integration
- Coding from prompt to completion
- Allows switching between high-level tasks and code-first flow
- Autonomous operation
- Enables custom instructions
- Supports adding skills
- Allows customizations
- Supports model swap
- Provides dozens of models
Cons
- Doesn't support other version controls
- Limited custom agent personas
- Difficult to switch workflows
- Too many environments
- Agent monitoring can be complex
- Browser management may need setup
- Custom agent creation unintuitive
- Excessive switching between agent-first and code-first
- No unified documentation for models
- Scalability dependent on local/cloud decision
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❓ Frequently Asked Questions
Visual Studio Code Agents is an open platform for AI agents. It supports GitHub Copilot, custom agents, and third-party agents. The platform enables these agents to plan and execute tasks autonomously, including aspects like researching, editing, running commands, and checking their own results. Developers using this platform can start and complete tasks from anywhere as these agents operate in multiple environments such as VS Code, command line interfaces, browsers, and on mobile devices.
Visual Studio Code Agents supports Github Copilot by serving as a platform where Github Copilot can operate effectively and autonomously. Github Copilot can plan and execute tasks, edit across files, run commands, and check on its own results, all within the Visual Studio Code Agents' platform.
Autonomous task planning in Visual Studio Code Agents refers to the ability of AI agents to independently plan and execute tasks. This includes researching, editing, running commands, and checking their own results, without any need for continuous developer input.
Visual Studio Code Agents can operate in various environments, providing users with optimal flexibility. These agents can work in environments including Visual Studio (VS) Code, command line interfaces, browsers, and on mobile devices. This diverse range of operation environments enables tasks to be started and finished from practically anywhere.
Visual Studio Code Agents facilitates task flexibility by allowing developers to switch between high-level tasks and a code-first flow according to the task requirements. In addition, multiple tasks can be run at once, and work can be carried out in parallel across different projects. Visual Studio Code Agents further supports task flexibility by allowing tasks to be initiated and finished from any environment, including VS Code, command line interfaces, browsers, and on mobile devices.
Code-first flow in Visual Studio Code Agents refers to a development approach where one starts with writing code, followed by task detailing. It's a method that allows developers to engage deeply with their code and tweak complex details instead of focusing primarily on the conceptual side of things. Visual Studio Code Agents' platform provides the ability to switch between this mode and high-level tasks based on task demands.
Visual Studio Code Agents integrates Native Model Context Protocol (MCP). This built-in support allows developers to connect AI agents to various databases, APIs, and services through the MCP servers, enhancing interoperability and data exchange between different components. This integration allows the AI agents to conveniently use any model from any provider, including models hosted by developers themselves.
With Visual Studio Code Agents, developers can connect to various AI models across multiple providers. These include prominent AI organizations like OpenAI, Anthropic, and Google, among others. Developers can bring their API key and use models from any provider of their choice.
Developers can create custom agent personas on Visual Studio Code Agents platform. These custom personas can be tuned to follow a team’s conventions and the most frequent tasks. This allows for greater efficiency and customization, as developers can create agents that fulfill the specific needs and requirements of their team.
Visual Studio Code Agents manages workload by maintaining a unified view for managing and monitoring all agent sessions. This enables fluid workflow management by letting developers keep track of the progress of each task and agent. Developers can also kick off multiple tasks at once, working in parallel across different projects.
Visual Studio Code Agents offers the capability to run AI agents either locally on a developer's machine or in a cloud based environment, providing the flexibility to choose the execution environment based on specific needs. This option is available for GitHub Copilot, custom, or third-party agents.
Visual Studio Code Agents supports scalability by offering the flexibility to run AI agents either locally or in the cloud. If a developer needs to scale up their operations, they can simply move their AI agents to the cloud to take advantage of greater computational power and storage, as cloud-based systems can adapt to varying scale requirements.
Visual Studio Code Agents supports GitHub-native agent operations by enabling agent operation directly in a developer’s terminal. This functionality allows agents to directly engage with issues and pull requests, plan changes, and edit across files without disrupting the command-line flow. Such a feature streamlines the workflow when working with GitHub repositories.
With Visual Studio Code Agents, editing across files can be easily handled by AI agents. Given a task, an AI agent can make necessary edits in multiple files and directories, thus saving time and ensuring consistency. They can perform cross-file operations without losing context.
Visual Studio Code Agents allows developers to delegate command running to AI agents. After being given a task, an AI agent can autonomously execute necessary terminal commands for task completion. This allows developers to focus on high-level tasks, while the AI handles routine or repetitive commands.
Autonomous coding in Visual Studio Code Agents refers to the ability of AI agents to code independently, from task description to task completion. Given a goal or task, the AI agent does the work of researching, editing, running commands, and checking its own results without needing continuous user input.
Yes, Visual Studio Code Agents allows developers to run multiple tasks across different projects simultaneously. This feature enables developers to manage multiple projects at once, offering an efficient and streamlined approach to multi-project management.
Visual Studio Code Agents manages and monitors agent sessions by maintaining a unified view. With this, a user can monitor and manage all agent sessions, regardless of whether they run locally or in the cloud. The unified view also simplifies the task of managing multiple agents and workflows.
Visual Studio Code Agents provides the flexibility to switch freely between high-level tasks and a code-first flow. Depending on the demands of the task, a developer can choose to instruct AI agents with a high-level task, review and approve the strategy even before a single line of code is written. Alternatively, they can also switch to a code-first workflow, where agents run alongside the code editor to help accomplish coding tasks.
Visual Studio Code Agents supports task initiation and finishing from anywhere by offering cross-environment functionality. AI agents can operate in environments including Visual Studio Code, command line interfaces, browsers, and mobile devices. This means tasks can be started and completed from wherever a developer prefers or finds most convenient.
Pricing
Pricing model
Free
Paid options from
Free
