GitHub Copilot previews agent mode as market for agentic AI coding tools accelerates

Agentic AI is all the rage today across multiple sectors, including application development and coding.

Today at long last, GitHub has joined the agentic AI party with the launch of GitHub Copilot agent mode. The promise of agentic AI in development is about enabling developers to build more code with just a simple prompt. The new agent mode will enable Copilot to iterate on its own code and fix errors automatically. Looking forward, GitHub is also previewing a fully autonomous software engineering agent, Project Padawan, that can independently handle entire development tasks.

The new agentic AI features mark the latest step in the multi-year evolution of the AI-powered coding development space that GitHub helped to pioneer. The Microsoft-owned GitHub first previewed GitHub Copilot in 2021, with general availability coming in 2022. In the AI world, that’s a long time ago, before ChatGPT became a household name and most people had ever heard the term “generative AI.”

GitHub has been steadily iterating on Copilot. Initially, the service relied on the OpenAI Codex large language model (LLM). In October 2024, users gained the ability to choose from a variety of LLMs, including Anthropic’s Claude, Google’s Gemini 1.5 and OpenAI’s GPT4o. Alongside the agent mode launch, GitHub is now also adding support for Gemini 2.0 Flash and OpenAI’s o3-mini. Microsoft overall has been emphasizing agentic AI, assembling one of the largest AI agent ecosystems in the market.

AI that supports ‘peer programming’

The new GitHub Copilot agent mode service comes as a series of rivals, mostly led by startups, have shaken up the development landscape. Cursor, Replit, Bolt and Lovable are all chasing the growing market for AI-powered development that GitHub helped to create.

When GitHub Copilot first emerged, it was positioned as a pair programming tool, which pairs with a developer. Now, GitHub is leaning into the term peer programming as it embraces agentic AI.

“Developer teams will soon be joined by teams of intelligent, increasingly advanced AI agents that act as peer-programmers for everyday tasks,” said GitHub CEO Thomas Dohmke. “With today’s launch of GitHub Copilot agent mode, developers can generate, refactor and deploy code across the files of any organization’s codebase with a single prompt command.”

Technical breakdown: How GitHub’s new agent architecture works

Since its initial debut, GitHub Copilot has provided a series of core features. Among them is intelligent code completion, which is the ability to suggest code snippets to execute a given function. Copilot also functions as an assistant, allowing developers to input natural language queries to generate code, or get answers about a specific code base. The system, while intelligent, still requires a non-trivial amount of human interaction.

Agent mode goes beyond that. According to GitHub, the platform enables Copilot to iterate on its own output, as well as the results of that output. This can significantly improve results and code output.

Here’s a detailed breakdown of agent mode operation.

Task understanding and planning:

• When given a prompt, agent mode doesn’t just generate code it analyzes complete task requirements;
• According to GitHub, the system can “infer additional tasks that were not specified, but are also necessary for the primary request to work”.

Iterative execution:

• The agent iterates on both its own output and the result of that output;
• It continues iteration until all subtasks are completed.