Amplitude and GitHub Launch Agent-to-Agent Integration to Accelerate Intelligent Product Development
Amplitude, Inc. the leading digital analytics platform, today announced a new collaboration with GitHub to launch an agent-to-agent integration designed to revolutionize how enterprise product and engineering teams work together. The integration bridges Amplitude’s product insights with GitHub’s code workflows, enabling AI-powered, automated collaboration between product managers and developers.
Through this integration, Amplitude effectively acts as an agentic product manager, transforming insights from user behavior directly into actionable development tasks. Combined with GitHub’s powerful AI-driven workflows, the integration dramatically reduces the manual effort required for software development, from ideation to implementation.
Redefining Product Development Through Intelligent Collaboration
The Amplitude–GitHub partnership represents a step forward in the evolution of AI-driven product development. By aligning product analytics with automated coding assistance, the collaboration eliminates traditional bottlenecks between data analysis and software execution.
This new agentic workflow enables teams to:
1. Surface High-Impact Opportunities Backed by Real Data
Amplitude’s analytics tools allow teams to identify what’s working and what needs improvement based on actual user behavior. Instead of relying on intuition or anecdotal feedback, teams can pinpoint the features that drive engagement and revenue. This ensures development resources are directed toward the highest-impact opportunities that align with user needs and business goals.
2. Eliminate Manual, Repetitive Tasks
The integration reduces friction and context-switching between tools. With automated workflows, Amplitude can generate detailed, data-backed product requirements directly within GitHub, removing the need for manual ticket creation. This frees up time for strategic thinking, innovation, and faster decision-making—allowing teams to focus on building rather than administrating.
3. Turn Insights Into Code Seamlessly
GitHub Copilot, GitHub’s AI coding agent, closes the loop between insight and implementation. Once Amplitude surfaces a prioritized product requirement, GitHub Copilot automatically translates those insights into code, opening a pull request and preparing it for review. This automation bridges the gap between product managers and developers, enabling faster time to market and stronger alignment with user expectations.
4. Continuously Learn and Improve With Every Release
Once new features are deployed, Amplitude continues to track performance and user engagement in real time. Teams can monitor how users respond to new features, measure adoption, and identify opportunities for improvement. These insights are then fed back into the roadmap, ensuring that every product iteration becomes smarter, more targeted, and more effective.
Leaders Speak: Data and AI Transforming the Product Lifecycle
“Product and engineering teams move fastest when they’re aligned around real-time data and a shared understanding of customer needs,” said Spenser Skates, CEO and co-founder of Amplitude. “By bringing Amplitude and GitHub agents together, companies can now build the right products and ship them faster.”
Mario Rodriguez, Chief Product Officer at GitHub, emphasized the broader impact of agentic AI on software development. “AI is reshaping how software is built, and the future lies in agents that can understand context and take action. By bringing business context directly into the developer workflow, we’re enabling teams to build at the speed of their ideas with intelligent agents that make better decisions and drive faster outcomes.”
Introducing the Amplitude Feature Experimentation Custom Agent
Alongside the new integration, Amplitude also unveiled the Feature Experimentation Custom Agent, developed in collaboration with GitHub. This specialized version of the GitHub Copilot Coding Agent includes Amplitude-specific prompts and tools built on the Model Context Protocol (MCP), an open standard for embedding context into AI systems.
The custom agent allows teams to:
- Query product insights directly from Amplitude without leaving GitHub
- Add and manage feature instrumentation
- Create and control feature flags
- Automatically design and run experiments on new features
By combining the capabilities of Amplitude’s analytics and GitHub Copilot’s AI coding, organizations can automate experimentation and validation within the same workflow—shortening feedback loops and enabling data-driven innovation at scale.
Powered by the Model Context Protocol
Both the integration and the Feature Experimentation Custom Agent are powered by MCP, which allows Amplitude’s rich product and customer data to flow directly into GitHub Copilot-powered workflows. This shared data context enables AI agents from both platforms to collaborate intelligently, reducing manual handoffs and minimizing tool switching.
Amplitude’s MCP Server is now also listed in the GitHub MCP Registry, making it accessible for developers and enterprises adopting AI-based automation standards.
A Step Toward the Future of Agentic Software Development
The Amplitude–GitHub integration demonstrates how the next generation of AI agents can work together to accelerate software development cycles. By uniting business insights and engineering execution under a shared, automated system, companies can move from data to deployment faster than ever before.
For modern product teams, the impact is clear: fewer manual steps, smarter prioritization, faster feedback, and continuous improvement driven by real-world usage data.
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