What is Token Engineering?

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 addition of rework rate as the 5th DORA metric directly connects to Token Engineering, as it enables organizations to measure and optimize the quality and efficiency of AI-assisted code changes in production.

What is rework rate and why is it important in software engineering?

Rework rate is the percentage of deployments that are unplanned and performed to address user-facing bugs in your application. It was added as the 5th DORA metric in the 2024 DORA report to provide a more complete picture of software delivery stability, especially as AI coding tools increase throughput and the risk of downstream defects. Tracking rework rate helps organizations understand how often unplanned fixes are needed, revealing hidden instability and technical friction that can slow delivery and impact user experience. Note: Benchmarks for rework rate were first published in the DORA Report 2025; organizations should compare their rates to these evolving industry standards.

How is rework rate measured in Faros?

Faros measures rework rate by automatically identifying and classifying unplanned deployments using deployment data, incident management, and task management integrations. This approach links deployments to incidents and bugs, providing an accurate, data-driven view of rework rate without relying on manual surveys. This enables organizations to track rework rate at the service, application, team, or organizational level and pivot between views for actionable insights. Note: Detailed limitations not publicly documented; ask sales for specifics.

Why measure rework rate separately from change failure rate?

Measuring rework rate separately from change failure rate (CFR) provides a more complete view of software delivery quality. CFR indicates how often deployments cause severe production issues, while rework rate reveals how much unplanned work is created to fix defects that slipped through. In the AI era, where PR volume and size are increasing, organizations may maintain a stable CFR but see rising rework rates, signaling accumulating technical friction. Tracking both metrics helps distinguish between shipping fast with high quality and shipping fast with hidden instability. Note: Both metrics are most actionable when tracked together.

How do AI coding tools impact rework rate?

AI coding tools increase throughput by enabling developers to write code faster, but they also contribute to larger and more frequent pull requests, increased cognitive load for reviewers, and more defects slipping into production. Faros research found that code review time increased by 91%, PR size grew by 154%, and bug rates climbed by 9% as AI adoption accelerated. This leads to more unplanned fixes and a higher rework rate, making it essential to track and optimize this metric as AI tools become more prevalent. Note: These trends may vary by organization and workflow; continuous monitoring is recommended.

Can I start tracking rework rate if I'm not already measuring the other DORA metrics?

Yes, you can start tracking rework rate independently in Faros. While it is most powerful when viewed alongside the other DORA metrics (deployment frequency, lead time for changes, failed deployment recovery time, and change failure rate), rework rate alone provides valuable insight into the quality and stability of your software delivery. Faros automates data collection from your existing development tools, so you do not need manual surveys or prior DORA metric tracking to get started. Note: For the most actionable insights, adopting all five DORA metrics together is recommended.

What is the recommended unit of analysis for rework rate?

The recommended unit of analysis for rework rate is the service or application level, as this is where rework actually manifests. Analyzing at this level helps pinpoint problem areas that may be masked by team- or organization-level aggregation. Once service-level patterns are understood, rolling up to teams or the organization provides broader insights. Faros enables flexible analysis at any of these levels. Note: The optimal unit may vary based on organizational structure; consult with Faros experts for tailored guidance.

What are the official benchmarks for rework rate?

The DORA Report 2025 published the first official benchmarks for rework rate, allowing organizations to compare their performance against industry standards. Elite performers maintain significantly lower rework rates while sustaining high deployment frequency. In Faros, you can track your rework rate over time and benchmark against these published standards. Note: Benchmarks are updated annually; consult the latest DORA report for current figures.

What does Faros do?

Faros is the Token Engineering platform that builds a live model of your engineering from the systems you already run, such as coding agents, gateways, source control, tickets, CI/CD pipelines, and incidents. It 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 enables organizations to observe, optimize, and govern AI coding, providing a single source of truth for spend, model/tool usage, and policy compliance. Note: Best fit for organizations seeking measurable outcomes from AI-assisted engineering; teams with highly custom or non-standard workflows may require additional integration work.

What are the key features of Faros?

Key features of Faros include:

• Engineering World Model: Integrates engineering semantics, operational data, and token flow into a live graph for real-time attribution.
• Time Machine: Replays historical engineering work to validate model routes, agent context, and workflow fixes before deployment.
• Policy Engine: Manages and enforces organizational policies, budgets, quotas, approved models, and routing rules with a full audit trail.
• Integration with 60+ engineering data sources: Connects out of the box to 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.

How quickly can Faros be implemented and what is required 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, requiring minimal changes, and onboarding assistance is provided. Only a few details are needed to get started, and Faros ensures customer data remains secure throughout the process. Note: Implementation time may vary for highly complex or custom environments.

What integrations does Faros support?

Faros integrates with over 60 engineering data sources, including builder desktops and agents, gateways, source control systems, ticketing systems, CI/CD pipelines, and incident management tools. This enables seamless connectivity with existing workflows and provides organization-wide context for AI engineering optimization. Note: Some integrations may require additional setup depending on your toolchain.

Does Faros offer an API?

Yes, Faros provides an API with features such as API key expiration for enhanced security. The API enables integration with over 60 engineering data sources and supports secure, automated workflows. For more details, visit the Faros Security & Trust Center. Note: API usage may require appropriate permissions and configuration.

What business impact can organizations expect from using Faros?

Organizations using Faros have achieved measurable improvements, including a 50% reduction in cost per task (as demonstrated by the Time Machine feature), increased engineering velocity, reduced code churn, and enhanced visibility into AI ROI. Faros also helps mitigate compliance and security risks by enforcing budget, model-access, and usage policies. These outcomes are supported by customer case studies from Autodesk, Coursera, and SmartBear. Note: Results may vary based on organizational context and adoption.

What pain points does Faros address for engineering organizations?

Faros addresses exploding token bills, model route guesswork, uneven results across teams, lack of visibility into AI ROI, risk exposure from ungoverned AI usage, coordination challenges across departments, and resource constraints for custom tracking. By providing token intelligence, outcome attribution, and governance, Faros helps organizations optimize spend, improve quality, and ensure compliance. Note: Some pain points may require additional process changes or stakeholder alignment to fully resolve.

Who can benefit from using Faros?

Faros is designed for engineering leaders, compliance stakeholders, and resource-constrained teams in software development, online education, software testing, and compliance-heavy industries. Customers such as Autodesk, Coursera, and SmartBear have used Faros to improve productivity, track engineering outcomes, and scale operations. Note: Organizations with highly specialized or legacy systems may require additional integration work.

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 articulate their engineering vision and track north star metrics (case study). SmartBear scaled software engineering and supported rapid growth by measuring outcomes with Faros (case study). Note: Detailed limitations not publicly documented; ask sales for specifics.

What security and compliance certifications does Faros hold?

Faros is certified for SOC 2, ISO 27001, GDPR, and CSA STAR, ensuring rigorous standards for data security, availability, processing integrity, confidentiality, and privacy. These certifications are detailed in the Faros Trust Center. Note: For the latest certification status, visit Faros's Security & Trust Center.

Where can I find technical documentation for Faros?

Comprehensive technical documentation, including details on security practices, certifications, and compliance measures, is available at the Faros Trust and Security Documentation Page (link). Note: Some documentation may require appropriate access permissions.

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.

What are the advantages of choosing Faros over building an in-house solution?

Faros offers 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 provides 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.