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AmplifyGenAI
Is GenAI benefiting your dev team?
Get the live dashboard that shows how AI coding assistants impact your team across projects, tasks, and developers.
Try it free now
200+ people have signed up
Benefits
Measure impact, then multiply it
Understand your team's GenAI usage
Track adoption and usage patterns
Track the impact of AI on tasks & projects
Measure delivery outcomes, code share, and speed
See what's working and what's not
Identify strong use cases so you can scale what works
Why it matters
You can’t fix what you can’t see
Unknown outcomes
Most teams don’t know if GenAI speeds things up or slows them down.
Unknown outcomes
Most teams don’t know if GenAI speeds things up or slows them down.
Scaling blind
Managers can’t prove ROI, spot bad patterns, or scale good ones.
Scaling blind
Managers can’t prove ROI, spot bad patterns, or scale good ones.
Invisible costs
Without visibility, you risk wasted budget and hidden delivery risk.
Invisible costs
Without visibility, you risk wasted budget and hidden delivery risk.
Features
All your GenAI answers in one place
Usage trends
See how much of your code is driven by GenAI today
Performance signals
Track the effect of AI code on productivity
Task analysis
Analyze GenAI usage across tasks and projects
Task-level activity
Dive into task activity to see where and how GenAI is used
Usage trends
See how much of your code is driven by GenAI today
Performance signals
Track the effect of AI code on productivity
Task analysis
Analyze GenAI usage across tasks and projects
Task-level activity
Dive into task activity to see where and how GenAI is used
How it works
From plug-in to clarity, fast
1. Connect
Link your repo or team members' IDEs and see detailed analysis of GenAI use
2. Track
AmplifyGenAI maps AI usage across projects, tasks, and developers
3. Explore
Double-click into metrics to see who’s using GenAI, where it works, and where it causes churn
1. Connect
Link your repo or team members' IDEs and see detailed analysis of GenAI use
2. Track
AmplifyGenAI maps AI usage across projects, tasks, and developers
3. Explore
Double-click into metrics to see who’s using GenAI, where it works, and where it causes churn
Demo
See it in action
What people are saying
Everyone is trying to measure GenAI's impact
“Rapid deployment creates dangerous technical debt. In brownfield environments with legacy systems, AI-generated code compounds existing problems when it's deployed by inexperienced developers.”
Inbal Shani, Twilio Chief Product Officer (2025)
“More than 97% of respondents… said they had used AI coding tools at work, but only 38% of US-based developers said their organizations actively encouraged adoption.”
GitHub’s AI in Software Development 2024 survey
“Rapid adoption of generative Al ... is leading to a surge in new technical debt. Companies must be proactive and vigilant to ensure they are creating clean, readable, efficient and high-quality code.”
Source: Accenture, 2025
“By incorporating GitHub Copilot into Visual Studio Code… we saw programmers reduce ten-minute tasks, such as writing a small function, down to the 30 seconds it took to write a comment that explains the function. Often these Copilot functions work out of the box without any need for changes.”
Joe Walsh, Principal Technologist at Launch Consulting
“Companies are no longer as limited by the number of engineers they can hire, but rather by the degree to which they can augment them with AI…”
DX “AI Measurement Framework” report, 2025
“Code copilots lead the charge with 51% adoption, making developers AI’s earliest power users. GitHub Copilot’s rapid ascent to a $300 million revenue run rate validates this trajectory.”
Menlo Ventures “State of GenAI in the Enterprise report
“Rapid deployment creates dangerous technical debt. In brownfield environments with legacy systems, AI-generated code compounds existing problems when it's deployed by inexperienced developers.”
MIT Sloan Management Review, 2025
“By incorporating GitHub Copilot into Visual Studio Code… we saw programmers reduce ten-minute tasks, such as writing a small function, down to the 30 seconds it took to write a comment that explains the function. Often these Copilot functions work out of the box without any need for changes.”
Joe Walsh, Principal Technologist at Launch Consulting
“Rapid deployment creates dangerous technical debt. In brownfield environments with legacy systems, AI-generated code compounds existing problems when it's deployed by inexperienced developers.”
Inbal Shani, Twilio Chief Product Officer (2025)
“Companies are no longer as limited by the number of engineers they can hire, but rather by the degree to which they can augment them with AI…”
DX “AI Measurement Framework” report, 2025
“Code copilots lead the charge with 51% adoption, making developers AI’s earliest power users. GitHub Copilot’s rapid ascent to a $300 million revenue run rate validates this trajectory.”
Menlo Ventures “State of GenAI in the Enterprise report
“More than 97% of respondents… said they had used AI coding tools at work, but only 38% of US-based developers said their organizations actively encouraged adoption.”
GitHub’s AI in Software Development 2024 survey
Limited access
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200+ people have signed up
FAQs
What tech leaders want to know
Tech Lead
It tracks how GenAI affects real engineering work — coding, testing, and reviews — showing concrete gains in speed, quality, and reduced rework.
How does this tool measure productivity?
Tech Lead
It tracks how GenAI affects real engineering work — coding, testing, and reviews — showing concrete gains in speed, quality, and reduced rework.
How does this tool measure productivity?
Chief Technology Officer
Absolutely. It compares adoption and impact across tools so you know which deliver value and which don’t justify their cost.
Will it help us decide which GenAI tools to keep?
Chief Technology Officer
Absolutely. It compares adoption and impact across tools so you know which deliver value and which don’t justify their cost.
Will it help us decide which GenAI tools to keep?
Engineering Manager
Baseline data appears in days, early trends in weeks, and within a quarter you’ll see a clear ROI and adoption story.
How quickly will we see insights?
Engineering Manager
Baseline data appears in days, early trends in weeks, and within a quarter you’ll see a clear ROI and adoption story.
How quickly will we see insights?
Engineering Lead
Yes. It translates engineering improvements into business outcomes like faster delivery, lower costs, and fewer defects in production.
Can it show ROI?
Engineering Lead
Yes. It translates engineering improvements into business outcomes like faster delivery, lower costs, and fewer defects in production.
Can it show ROI?
Executive
The tool monitors for issues like code churn, poor quality output, or unusual usage patterns, helping teams set safe AI governance policies.
How does it handle risks?
Executive
The tool monitors for issues like code churn, poor quality output, or unusual usage patterns, helping teams set safe AI governance policies.
How does it handle risks?
Engineering Lead
Yes. It combines usage data with lightweight surveys, showing both adoption levels and how developers feel about GenAI tools.
Can it measure developer adoption and experience?
Engineering Lead
Yes. It combines usage data with lightweight surveys, showing both adoption levels and how developers feel about GenAI tools.
Can it measure developer adoption and experience?
Chief Investment Officer
Other tools track outcomes like DORA metrics. This isolates GenAI’s unique impact on speed, quality, and developer experience.
How is this different from DevOps dashboards?
Chief Investment Officer
Other tools track outcomes like DORA metrics. This isolates GenAI’s unique impact on speed, quality, and developer experience.
How is this different from DevOps dashboards?
AmplifyGenAI
AmplifyGenAI
AmplifyGenAI
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Powered by CodeTogether, by developers for developers.