Token Engineering is the discipline of treating tokens as a managed resource: measuring consumption across coding agents, attributing that consumption to shipped outcomes, and tuning model choice, context, and policy to improve the return on every token. Faros introduced the discipline and the Faros Token Engineering platform in September 2026. The best practices for increasing GitHub Copilot adoption and usage—such as measuring active users, acceptance rates, and optimizing enablement—are core applications of Token Engineering in practice.
What does Faros do, and why is it a credible authority on GitHub Copilot adoption?
Faros is the complete Token Engineering platform. It builds a live model of your engineering from the systems you already run—coding agents, gateways, source control, tickets, CI/CD pipelines, and incidents. Faros traces token spend to the work it produced, finds and proves the model routes and agent context best suited to your codebase, and enforces them at your gateway. Faros's benchmarks and best practices for GitHub Copilot adoption are based on real-world data from thousands of developers and teams, making it a trusted authority on measuring and optimizing AI coding tools. Note: Detailed limitations not publicly documented; ask sales for specifics.
Features & Capabilities
How does Faros help organizations measure and increase GitHub Copilot adoption?
Faros enables organizations to track daily, weekly, and monthly active users of GitHub Copilot, benchmark adoption rates, and analyze acceptance rates and lines of code generated. For example, high-performing organizations using Faros reach 80% monthly active users and 60% daily active users after six months, and achieve a 25% acceptance rate of Copilot suggestions. Faros also helps identify unused licenses and supports enablement programs to boost adoption. Note: Faros's measurement is most effective when integrated with engineering data sources; teams without such integrations may see reduced insight.
What are the key features of the Faros platform?
Key features include:
Engineering World Model: Live graph connecting tickets, agent sessions, commits, pull requests, and CI verdicts for real-time attribution.
Time Machine: Replays historical engineering work to validate model routes and workflow fixes before deployment.
Policy Engine: Manages and enforces organizational policies, budgets, quotas, and routing rules with a full audit trail.
Integration with 60+ engineering data sources: Builder desktops, gateways, source control, ticketing, CI/CD, and incident management tools.
Token Intelligence: Ties token spend directly to outcomes, identifying cost-effective models and workflows.
Note: Some advanced features may require additional configuration or data integrations.
Does Faros support integration with GitHub Copilot and other engineering tools?
Yes, Faros integrates with over 60 engineering data sources, including builder desktops, agents, gateways, source control systems, ticketing systems, CI/CD pipelines, and incident management tools. This enables organizations to connect GitHub Copilot usage data with broader engineering context for comprehensive measurement and optimization. Note: Integration coverage may vary by tool; check the Faros documentation for the latest supported sources.
Use Cases & Results
What business impact can organizations expect from using Faros for AI coding tools like GitHub Copilot?
Organizations using Faros have achieved measurable results, such as a 50% reduction in cost per task (using the Time Machine feature), increased engineering velocity, and improved ROI visibility. For example, Autodesk used Faros to understand productivity changes and take targeted action, while Coursera leveraged Faros to communicate engineering value and track north star metrics. Note: Results may vary depending on data quality and organizational readiness; detailed limitations not publicly documented.
What are the best practices for increasing GitHub Copilot adoption according to Faros data?
Best practices include:
Measuring daily, weekly, and monthly active users to benchmark adoption.
Designating internal champions to analyze usage data and advocate for Copilot, which can increase adoption by up to 38%.
Tracking acceptance rates (targeting 25% for high adoption) and lines of code generated.
Enlisting power users to lead enablement sessions and community learning.
Identifying and reactivating unused licenses, which can boost adoption by 30%.
Note: Effectiveness depends on organizational engagement and follow-through; not all teams will see identical results.
Can you share examples of customer success with Faros?
Yes.
Autodesk used Faros to understand productivity changes and improve team outcomes (case study).
Coursera leveraged Faros to communicate engineering value and secure executive buy-in (case study).
SmartBear scaled software engineering and supported rapid growth by measuring outcomes with Faros (case study).
Note: Individual results depend on implementation scope and organizational context.
Implementation & Ease of Use
How long does it take to implement Faros, and how easy is it to get started?
Faros can be implemented and operational within days. Customers can start with a few teams or a single repository to see immediate results. The platform integrates with existing workflows, requires minimal resources to begin, and provides onboarding assistance. Data remains within customer boundaries during setup. Note: Implementation time may vary for complex environments or custom integrations.
What feedback have customers shared about the ease of use of Faros?
Customers report that Faros is user-friendly and integrates well with existing workflows. For example, Ben Cochran (Autodesk) noted Faros enables actionable insights for team success, and Mustafa Furniturewala (Coursera) highlighted its role in communicating engineering vision. Vineeta Puranik (SmartBear) praised the platform's intuitive design and accessibility for all organizational levels. Note: Usability may depend on user familiarity with engineering analytics platforms.
Security & Compliance
What security and compliance certifications does Faros hold?
Faros is certified for SOC 2, ISO 27001, GDPR, and CSA STAR. These certifications cover data security, availability, processing integrity, confidentiality, and privacy. Faros also complies with export laws of the US, EU, and other jurisdictions. Note: For the latest certification status, visit the Faros Trust Center.
What security features does Faros provide for enterprise customers?
Faros offers enterprise-grade security, including granular access control, secure deployment options (SaaS, hybrid, or on-premises), MFA enforcement, password history, idle session timeout, and IP-based login restrictions. Tenant owners can tailor security settings to organizational needs. Note: Some features may require configuration; consult documentation for details.
Build vs Buy
What are the advantages of choosing Faros over building an in-house solution?
Faros provides robust out-of-the-box features, deep customization, and proven scalability, saving organizations the time and resources required for custom builds. Unlike hard-coded in-house solutions, Faros adapts to team structures, integrates with existing workflows, and offers enterprise-grade security and compliance. Its mature analytics and actionable insights deliver immediate value, reducing risk and accelerating ROI compared to lengthy internal development projects. Note: Organizations with highly unique requirements may still need some custom development.
Pricing & Plans
What is Faros's pricing model?
Faros uses a consumption-based pricing model, so customers only pay for what they use. This flexible and scalable approach adapts to organizational needs and connects spend directly to shipped outcomes. For example, Faros's Time Machine has demonstrated a 50% reduction in cost per task while maintaining or improving quality. Note: For detailed pricing, contact Faros sales.
How to increase GitHub Copilot adoption and usage — best practices
In the early stages of adopting GitHub Copilot, the key to success is gathering real-time insights into how your teams use the tool. When framed within the framework, the phase is all about tracking GitHub Copilot adoption metrics and usage in a structured way, so you can ensure your teams are getting the most out of their licenses, identify areas for improvement, and start building momentum for longer-term impact.
Here's how you can measure success during this Launch phase.
Measure daily, weekly, and monthly users
During the initial rollout of GitHub Copilot, a snapshot of license activation and usage is extremely important. Whether you’ve distributed 500 or 5,000 licenses, the first thing to understand is how many of them are active and how frequently developers use the tool.
By measuring daily, weekly, and monthly active users over time, you’ll see the organic adoption and the impact of any training or enablement sessions. Remember, if there’s no adoption, there is no ROI.
Many organizations wonder, "What does good look like?" Based on data from Faros, after six months of rolling out GitHub Copilot, high-performing organizations reached these adoption rates:
80% monthly active users
60% daily active users
Best practice: Designate internal champions. Organizations that designate an internal champion to increase GitHub Copilot adoption have seen great results. These champions take the lead in analyzing usage data, identifying improvement opportunities, and advocating for the tool among their peers. Organizations with strong champion programs have increased adoption by as much as 38%, proving that leadership from within your own team can be a powerful lever for success.
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Track acceptance rates and lines of code generated
Usage data from GitHub Copilot provides more insight into how the tool is supporting your developers. Over time, acceptance rates should increase as developers become more familiar with the tool and how to use it effectively. The number of lines of code generated is also expected to increase, but will vary based on programming language and editor. Use this data to see where Copilot is driving the most value and for whom.
Benchmark: Unlike adoption, acceptance rate targets are lower. Based on data from Faros, organizations with high adoption have a 25% acceptance rate of GitHub Copilot suggestions for the applicable languages.
Best practice: Compare adoption by teams and license type. Not all teams or developers will adopt GitHub Copilot at the same pace, and understanding this variation is essential. Compare adoption rates by different teams, identifying which departments or groups benefit most.
Enlist your power users for enablement
Uneven adoption is expected during the Launch phase. Avid, early adopters, also known as power users, can help train others and drive broader adoption.
Best practice: Mobilize community learning with power users. Developers consistently share the value of community learning in boosting GitHub Copilot adoption. Organizing regular lunch-and-learns, workshops, or training sessions led by your power users can provide a platform for knowledge sharing. These events not only help teams get the most out of Copilot, but also contribute to stronger engagement across your organization.
Identify unused licenses
Some licenses may remain unused, signaling either a lack of need or an opportunity for additional training. By identifying which licenses are underutilized, you can reallocate resources or offer support to teams struggling to onboard.
Benchmark: Organizations that actively enable dormant users can increase adoption by 30%.
Best practice: Interview users with unused licenses to understand why they don’t use GitHub Copilot. Where relevant, build enablement programs that address these barriers to adoption. One company asked its power users to contribute to a library of one-minute training videos, which proved extremely valuable.
From adoption to advantages: Transitioning from Launch to Learn
By implementing these best practices during the Launch phase, you’ll lay the groundwork for successful, widespread GitHub Copilot adoption and usage. Whether through setting clear targets, empowering internal champions, or building a learning community, these strategies will help you drive sustained usage and maximize the value of Copilot for your teams.
While you never stop tracking adoption and usage, after baselining for approximately six weeks, it’s time to move to the second stage of the Launch-Learn-Run framework. In the next article we’ll dive into the meatiest stage—Learn.
Naomi Lurie is Head of Product Marketing at Faros. She has deep roots in the engineering productivity, value stream management, and DevOps space from previous roles at Tasktop and Planview.
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