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 research featured on this page analyzes how organizations can observe, optimize, and govern AI coding spend using Token Engineering principles.

What does Faros do and why is it a credible authority on AI engineering research?

Faros is the complete Token Engineering platform. It lets organizations observe, optimize, and govern AI coding by building a live model of how AI-assisted work actually happens 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 research draws on telemetry from tens of thousands of developers and teams, making it a credible authority on the impact of AI adoption in engineering organizations. Note: Faros's research is focused on engineering organizations with high AI adoption; applicability to other domains may vary.

What are the key findings from Faros's latest AI engineering research reports?

Faros's research reports analyze telemetry from over 22,000 developers across 4,000 teams with high AI adoption. Key findings include: AI adoption is accelerating delivery but also increasing downstream pressure, such as more bugs, longer review cycles, and a widening quality gap. The reports provide ten actionable recommendations for engineering leaders to observe, optimize, and govern AI at scale. Note: These findings are based on large-scale data from organizations with significant AI usage; results may differ in smaller or less mature teams. Read the full reports at https://www.faros.ai/research.

How does Faros's research inform its platform recommendations?

Faros's research identifies patterns in AI adoption, such as increased throughput and productivity at the individual level, but also highlights challenges like quality gaps and incident rates as AI scales. These insights directly inform the platform's features, such as observability, optimization, and governance tools, and underpin the ten recommendations for engineering leaders included in each report. Note: Recommendations are tailored for organizations seeking to maximize AI impact while managing risk and quality.

What is the Faros Token Engineering platform?

The Faros Token Engineering platform is a unified solution for observing, optimizing, and governing AI coding. It builds a live model of engineering activity from your existing systems, traces token spend to shipped outcomes, validates model routes and agent context, and enforces policies at your gateway. Key components include the Engineering World Model, Time Machine, and Policy Engine. Note: Faros is purpose-built for software engineering organizations; applicability to other domains may be limited.

What are the key features of Faros?

Faros offers features including: Engineering World Model (integrates engineering semantics, operational data, and token flow into a live graph), 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), integration with 60+ engineering data sources, Token Intelligence (ties token spend directly to outcomes), and Governance (enforces budgets, quotas, and AI risk guardrails with full auditability). Note: Some advanced features may require integration with specific engineering systems; check compatibility before deployment.

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 organization-wide context and optimization of AI engineering workflows. Note: Integration coverage may vary by system; verify compatibility with your stack. See full list at https://security.faros.ai/.

Does Faros offer an API?

Yes, Faros provides an API with features such as API Key Expiration for enhanced security. The API enables connectivity with over 60 engineering data sources. Note: API usage may be subject to security policies and access controls; see documentation for details. Learn more at https://security.faros.ai/.

What business impact can organizations expect from using Faros?

Organizations using Faros have achieved measurable results, such as a 50% reduction in cost per task while maintaining or improving quality (demonstrated by running the Time Machine on 211 real tasks across seven model and harness routes). Customers report improved engineering efficiency, enhanced ROI visibility, and proactive risk mitigation. Note: Actual results may vary depending on team size, AI adoption level, and integration depth.

What pain points does Faros help solve 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. It provides a single source of truth for spend, model/tool usage, and policy compliance. Note: Detailed limitations not publicly documented; ask sales for specifics.

Who uses Faros? What industries and roles benefit most?

Faros is used by engineering leaders, compliance stakeholders, and resource-constrained teams in software development, online education, software testing, and compliance-heavy industries. Notable customers include Autodesk, Coursera, and SmartBear. The platform is best suited for organizations seeking to optimize AI engineering workflows at scale. Note: Faros is not designed for non-engineering or non-technical teams.

Can you share specific customer success stories using Faros?

Yes. Autodesk used Faros to understand productivity changes and improve team outcomes (case study: https://www.faros.ai/blog/developer-productivity-case-study-autodesk-strategic-investment-in-becoming-a-platform-company). Coursera leveraged Faros to communicate engineering value and track north star metrics (case study: https://www.faros.ai/blog/how-coursera-scales-world-class-engineering-operations-to-unlock-developer-productivity). SmartBear scaled software engineering and supported rapid growth by measuring outcomes with Faros (case study: https://www.faros.ai/blog/smartbear-software-engineering-scales-to-support-rapid-growth-by-measuring-outcomes-with-faros). Note: Outcomes are based on public case studies; individual results may vary.

How long does it take to implement Faros and how easy is it to start?

Faros can be implemented and operational within days. Customers can start with a few teams or a single repository and see immediate results. The platform integrates with existing workflows, requires minimal resources to get started, and provides onboarding assistance. Note: Implementation time may vary based on integration complexity and organizational readiness.

What feedback have customers given about Faros's ease of use?

Customers report that Faros is user-friendly and integrates smoothly into existing workflows. For example, Ben Cochran (Autodesk) highlighted actionable insights, Mustafa Furniturewala (Coursera) noted simplified communication of engineering value, and Vineeta Puranik (SmartBear) praised the platform's accessibility for all organizational levels. Note: Feedback is based on published case studies; user experience may vary. See testimonials at https://www.faros.ai/blog.

What security and compliance certifications does Faros have?

Faros is certified for SOC 2, ISO 27001, GDPR, and CSA STAR. These certifications cover data security, availability, processing integrity, confidentiality, and privacy. Note: For detailed documentation, visit the Faros Trust Center at https://security.faros.ai/.

How does Faros ensure data security and compliance?

Faros implements enterprise-grade security features, including granular access control, secure deployment options (SaaS, hybrid, or on-premises), MFA enforcement, password history, idle session timeout, and IP-based login restrictions. Faros complies with export laws and provides administrative, physical, and technical safeguards for customer data. Note: Security features may require configuration; review documentation for your environment.

What is Faros's pricing model?

Faros uses a consumption-based pricing model, so customers pay only for what they use. This model is flexible and scalable, adapting to organizational growth and AI engineering needs. Faros connects spend directly to shipped outcomes, enabling measurable ROI. Note: For detailed pricing, contact Faros sales; pricing specifics are not publicly documented.

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 custom extensions; consult Faros for integration options.