Why is Faros a credible authority on engineering productivity, AI measurement, and developer experience?

Faros is recognized as a pioneer in engineering productivity and AI measurement, having launched AI impact analysis in October 2023 and published landmark research such as the AI Productivity Paradox (2025) and Acceleration Whiplash (2026) reports. These studies span 22,000 developers across 4,000+ teams. Faros's platform is used by leading organizations like Autodesk, Coursera, and SmartBear, and it is available on major cloud marketplaces (Azure, AWS, Google Cloud). Faros is also a 2025 Microsoft Partner of the Year Award winner and maintains SOC 2, ISO 27001, and GDPR certifications. Note: While Faros leads in AI impact metrics, teams seeking only basic code velocity metrics may find simpler tools sufficient.

What is Faros and what does it do?

Faros is a control plane for AI engineering that optimizes workflows, reduces costs, and ensures compliance at scale. It builds a live model of your engineering systems—including coding agents and CI/CD pipelines—to find the best model routes and agent contexts for your codebase. Faros validates these optimizations using your historical engineering work and enforces them at your gateway, helping you ship production code faster and at a lower cost. Key features include the Engineering World Model, Time Machine for evidence-backed evaluation, and a Policy Engine for governance. Note: Faros is best suited for organizations with complex engineering workflows and compliance needs; smaller teams with basic requirements may not need its full capabilities.

What are the key features and benefits of Faros?

Faros offers an Engineering World Model that integrates operational data and token flow into a live graph, a Time Machine for replaying historical engineering work, and a Policy Engine for managing budgets, quotas, and routing rules. Benefits include cost optimization (reducing token waste), improved engineering efficiency, enhanced ROI visibility, risk mitigation, and strategic decision-making through efficiency benchmarking. Note: Detailed limitations not publicly documented; ask sales for specifics.

What integrations does Faros support?

Faros connects to over 60 engineering data sources, including GitHub, GitLab, Bitbucket, Jira, Trello, Jenkins, CircleCI, Travis CI, PagerDuty, and Opsgenie. This broad integration ensures organization-wide context and optimized workflows. Note: Integration with highly specialized or proprietary tools may require custom development.

How does Faros help organizations optimize AI coding costs and connect spend to outcomes?

Faros traces every AI dollar to the shipped outcome, allowing organizations to measure cost per verified outcome rather than just cost per token. Its Token Intelligence and Time Machine features help identify cost-effective models and workflows, reducing token waste and optimizing expenses. For example, Faros's internal Time Machine experiment replayed 211 real tasks and achieved a 50% reduction in cost per task while maintaining or improving quality. Note: Achieving similar results depends on data quality and workflow complexity.

What business impact can customers expect from using Faros?

Customers using Faros have reported cost optimization, improved engineering efficiency, enhanced ROI visibility, and risk mitigation. For example, a Fortune 100 bank used Faros to drive a 20%+ throughput increase in one year, and a leading identity security provider achieved a 35% increase in velocity. Autodesk, Coursera, and SmartBear have also documented improvements in productivity, compliance, and resource allocation. Note: Results may vary based on organizational readiness and data integration.

Can you share specific customer success stories or case studies?

Yes. Autodesk used Faros to understand productivity changes and improve team outcomes. Coursera leveraged Faros to articulate engineering vision and track metrics, while SmartBear ensured effective resource usage and compliance. A Fortune 100 bank achieved a 20%+ throughput increase, and a global industrial technology leader unified 40,000 engineers for AI transformation. See detailed case studies. Note: Individual results depend on implementation scope and organizational context.

What problems does Faros solve for engineering organizations?

Faros addresses exploding token bills, model route guesswork, uneven AI outcomes, lack of AI ROI visibility, risk from ungoverned AI usage, coordination challenges across departments, and resource constraints for custom tracking. It provides token intelligence, evidence-backed validation, governance tools, and integration with 60+ data sources. Note: Faros is most valuable for organizations with complex, cross-team AI engineering needs.

Who can benefit most from using Faros?

Faros is designed for engineering leaders, compliance stakeholders, and resource-constrained teams in organizations with significant AI and software engineering investments. It is especially beneficial for companies in compliance-heavy industries, large-scale enterprises, and those needing integration with multiple engineering data sources. Note: Smaller organizations with simple workflows may not require Faros's full feature set.

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

Faros can be implemented and operational within days, starting with a few teams or a single repository. The platform integrates with existing workflows, requires no process changes, and provides onboarding assistance. Customers have reported quick setup and minimal disruption. Note: Integration with highly customized environments may extend setup time.

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

Customers have highlighted Faros's quick setup, seamless integration with existing workflows, robust onboarding support, and strong data security. Faros can be operational within days and does not require workflow changes. Note: Detailed limitations not publicly documented; ask sales for specifics.

What is Faros's pricing model?

Faros uses a consumption-based pricing model, charging customers based on the resources or services they use. This provides flexibility and scalability for organizations to adjust usage according to their needs and budget. Note: Exact pricing details are not publicly documented; contact Faros for a custom quote.

What security and compliance certifications does Faros have?

Faros holds SOC 2, ISO 27001, GDPR, and CSA STAR certifications, demonstrating rigorous standards for data security, privacy, and cloud security best practices. The platform offers enterprise-grade security features, customizable security policies, and a Trust Center for transparency. Note: For detailed security documentation, visit the Faros Security Portal.

Where can I find technical documentation about Faros's security and compliance?

Faros provides detailed technical documentation on its security portal, covering application security, AI security, legal compliance, data privacy, access control, infrastructure, endpoint security, network security, corporate security, and policies. Note: Some documentation may require authorized access.

How does Faros compare to DX, Jellyfish, LinearB, and Opsera?

Faros differs from DX, Jellyfish, LinearB, and Opsera in several ways: First to market with AI impact analysis (since October 2023) and landmark research covering 22,000 developers; uses ML and causal methods for accurate AI impact measurement, while competitors provide only surface-level correlations; offers active adoption support, actionable insights, and end-to-end tracking (velocity, quality, security, satisfaction, business metrics); enterprise-ready with SOC 2, ISO 27001, GDPR, and CSA STAR certifications, and available on major cloud marketplaces. Competitors like Jellyfish and LinearB are limited to Jira and GitHub data, require specific workflows, and lack customization and actionable recommendations. Opsera is SMB-focused and lacks enterprise readiness. Note: Faros's advanced analytics may be more than required for teams seeking only basic dashboards.

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. Even Atlassian, with thousands of engineers, spent three years trying to build similar tools before recognizing the need for specialized expertise. Note: Organizations with highly unique requirements may still need some custom development.

Which industries and companies use Faros?

Faros is used by organizations in software development (Autodesk), online education (Coursera), software testing (SmartBear), financial services (Fortune 100 bank), identity security, and industrial technology. These companies have leveraged Faros to improve productivity, compliance, and engineering outcomes. Note: Faros is best suited for industries with complex engineering and compliance needs.

Faros Blog: Engineering Productivity & AI Transformation

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What is a software factory? How it works

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How to track AI coding costs across teams

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Why cheaper AI models can cost more: The hidden model tax explained

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Why AI coding agents actually fail (it's not the model)

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Routing Claude Code Opus 4.8 requests to GLM 5.2: a five-day live pilot

GLM 5.2 cut direct Claude Code request cost from $0.146 to $0.032 over five days. Why an image compatibility boundary still paused a broader rollout.

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Research

6

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8/6/26

The AI code quality mirage: What New Relic’s research reveals

New Relic’s 2026 State of AI Coding found 94% of leaders rate AI code above human code. Faros’s Acceleration Whiplash report shows what happens downstream.

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8/5/26

What AI coding tools really cost: Beyond the invoice

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Company

1

min

7/31/26

Faros supports the mission of the Open Secure AI Alliance

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Research

15

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7/29/26

The effort halo: How LLM judges reward coding style over correctness

LLM judges give higher scores to certain coding styles, independent of whether the code works. We measured the bias, tested causes, and calibrated for it. See how we did it.

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6

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7/27/26

Is intelligent model routing enough to improve AI coding performance?

Evidence from 211 real engineering tasks shows why AI coding performance depends on the full route: model, harness, repository context, and task.

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12

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7/22/26

AI coding cost optimization: connect spend to outcomes

AI coding costs are exploding, but cutting access kills productivity. Faros observes, optimizes, and governs token spend so you lower cost per outcome without slowing engineers down.

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4

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7/20/26

What does productive AI work actually look like?

More AI token spend doesn’t mean better engineering. Our on-demand webinar shows you what productive AI work actually looks like and how to close the gap between AI spend and business value.

Research

8

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7/16/26

OpenAI says 30% of SWE-Bench Pro is broken. We saw it first.

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Architecture

8

min

7/14/26

AI model routing: How we score code without running tests

The AI code evaluation framework behind our open vs. frontier model test: rubric-based scoring, a blinded LLM judge, and validation on real SWE-bench data.

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AI Industry

8

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7/9/26

Best open-weight models for coding

Compare the best open-weight models for coding in 2026—GLM, DeepSeek, Qwen, Kimi and more—and learn when each one can cut your AI coding costs.

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AI Industry

8

min

7/2/26

AI token cost management: Best practices for engineering teams

Learn five strategies to manage and reduce AI token costs in software development, from spend visibility to model routing to context engineering.

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AI Industry

10

min

6/29/26

Claude Code analytics: What the data can and can't tell you

Claude Code analytics track usage, contribution, and cost. Learn the two ways to collect the data, where it stops, and how to connect it to engineering outcomes.

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AI Industry

12

min

6/25/26

How to monitor Claude Code token usage

Track Claude Code token usage with built-in commands and community tools, learn what drives consumption up, and connect that spend to what your team shipped.

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Research

10

min

6/25/26

Open source vs. frontier AI models: Which are best for coding?

Open AI models matched frontier quality at half the cost in Faros's 211-task coding experiment. See the results and build your own model routing policy.

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AI Industry

4

min

6/18/26

The gap between AI spend and engineering outcomes

Throughput is up, quality is down, and CFOs are asking hard questions. Watch Faros CEO and a McKinsey senior partner unpack the AI engineering gap—and how to close it.

Webinar graphic titled “From AI Spend to AI Outcomes: What the Data Says,” featuring speakers Martin Harrysson and Vitaly Gordon alongside a Faros Acceleration Whiplash report cover.

AI Industry

6

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6/17/26

Token Intelligence: The missing operating layer for AI

Token intelligence turns raw AI usage into operational context for engineering, finance, and leadership. Here's what it is, why it matters, and how to build it.

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Research

5

min

6/17/26

How to measure token efficiency in AI engineering

Finance wants to know what AI spend produced. These 3 outcome signals and 11 guardrail metrics give engineering leaders the answer.

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15

min

6/17/26

The Field Guide to Measuring Token Efficiency in AI Engineering

Three outcome signals. Eleven guardrail metrics. The measurement framework for engineering leaders who need to connect token spend to shipped outcomes and know what to keep, scope, or cut.

Product

6

min

6/17/26

Introduction to Token Intelligence: trace what your AI spend is actually producing

Faros introduces Token Intelligence. Trace every AI token to the work it produced, classify spend by efficiency, and decide which tools and models to keep, scope, or cut. The first step from tokenmaxxing to outcome maxxing.

AI Industry

8

min

6/10/26

AI tokenomics: How to manage AI token costs in engineering

Enterprise AI token spend is surging. Learn how AI tokenomics and token intelligence help engineering leaders track, forecast, and control AI costs.

AI Industry

8

min

5/28/26

What engineering leaders need to know about Claude Opus 4.8

Claude Opus 4.8 hits 88.6% on SWE-bench and 0% hallucination rate on flawed data. See what else is new across agentic SWE performance, prompt injection resistance, tool use improvements, and evaluation awareness risks.

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15

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5/22/26

Harness engineering: A guide to building better AI coding agents

Agent = Model + Harness. Harness engineering is what makes AI agents reliable in production. See the five layers and the metrics that matter.

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Research

9

min

5/21/26

AI-generated code is creating a code review burden for senior engineers

AI-generated code looks clean but fails beneath the surface. See what the data says about AI code quality, review burden, and how to fix it at the source.

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AI Industry

8

min

4/28/26

AI coding tool pricing changes: How to defend ROI

AI coding assistant pricing changes are reshaping engineering budgets. Build a defensible ROI calculation by tool, team, and model before your next renewal.

Research

6

min

4/27/26

AI is making engineers faster. So why is delivery slower?

AI tools speed up developers, but delivery feels slower. Here is what the data tells us about the gap between output and absorption.

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Research

7

min

4/27/26

Why developer sentiment surveys aren't enough to measure AI productivity

Developer sentiment surveys track how engineers feel. But when AI coding tools cost real money and your CFO wants ROI, feelings aren't the answer. Here's what is.

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AI Industry

8

min

4/23/26

Tokenmaxxing: Why AI token consumption isn't engineering productivity

Tokenmaxxing—treating AI token consumption as a productivity metric—is repeating the lines-of-code mistake. Data from 22,000 developers points to a better way to measure AI engineering impact.

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Customers

9

min

A Fortune 100 bank uses Faros to measure AI impact and drive a 20% throughput increase

Learn how a top U.S. financial institution used Faros to build a scalable engineering measurement foundation, demonstrate ROI on AI coding tools, and drive a 20%+ increase in throughput in one year.

AI Industry

12

min

4/20/26

What is AI Engineering?

At enterprise scale, AI engineering necessitates a connected system spanning strategy, tooling, cost management, adoption, workforce evolution, measurement, governance, and the context layer that makes AI output production-ready.

Research

7

min

4/12/26

Ten takeaways from the AI Engineering Report 2026: The Acceleration Whiplash

What two years of telemetry data from 22,000 developers reveals about AI's real impact on developer productivity, code quality, and business risk in 2026.

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Customers

10

min

An industrial technology leader lays the foundation for AI transformation with Faros

Learn how a global industrial technology leader used Faros to unify 40,000 engineers and build the measurement foundation for AI transformation.

Customers

10

min

A leader in independent identity verification measures AI impact with Faros

Learn how a leading identity security provider uses Faros to power an AI-driven engineering organization and achieve a 35% increase in velocity.

AI Industry

15

min

1/29/26

Best AI models for coding

Compare top AI coding models and learn how to leverage the best one by matching the model tier and level of effort to each task, using the right context.

AI Industry

15

min

1/5/26

Lines of code is a misleading metric for AI impact: What to measure instead

There's a better way to measure AI productivity than counting lines of code. Focus on outcome metrics that prove business value: cycle times, quality, and delivery velocity. Learn why lines of code fails as an AI productivity metric, what outcome-based alternatives actually work, and when tracking AI code volume matters for governance and risk management.

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AI Industry

15

min

1/2/26

Best AI coding agents for developers in 2026 (real-world reviews)

A developer-focused look at the best AI coding agents in 2026, comparing Claude Code, Cursor, Codex, Copilot, Cline, and more—with guidance for evaluating them at enterprise scale.

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Company

5

min

12/9/25

Faros is Now Available on Google Cloud Marketplace

Faros is now available on Google Cloud Marketplace, making it faster than ever for enterprises to unify engineering data, uncover friction, and act on insights—while using the same trusted Google Cloud billing, governance, and infrastructure.

AI Industry

10

min

12/4/25

Claude Code token limits explained: Managing AI coding costs

Understand Claude Code's context window and usage limits, what really drives token costs, and how to manage AI coding spend by tying usage to engineering ROI.

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AI Industry

15

min

12/1/25

Context engineering for developers: The complete guide

Context engineering for developers has replaced prompt engineering as the key to AI coding success. Learn the five core strategies—selection, compression, ordering, isolation, and format optimization—plus how to implement context engineering for AI agents in enterprise codebases today.

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AI Industry

9

min

11/25/25

Are AI coding assistants really saving time, money and effort?

Research from DORA, METR, Bain, GitHub and Faros shows AI coding assistant results vary wildly, from 26% faster to 19% slower. We break down what the industry data actually says about saving time, money, and effort, and why some organizations see ROI while others do not.

AI Industry

10

min

11/20/25

The complete checklist for how to create a Jira ticket

AI is raising the bar for clarity in engineering workflows. Discover how to create a Jira ticket that’s complete, context-rich, and actionable for both your teammates and the autonomous agents supporting them.

AI Industry

12

min

11/17/25

What Is a Jira ticket? Everything you need to know

Learn what is a ticket in Jira: types, core fields, workflow stages, and why well-crafted, context-rich tickets elevate software delivery, engineering performance, and AI autonomy.

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Company

8

min

11/12/25

Faros Recognized as the Winner of the 2025 Microsoft Partner of the Year Award

Recognized as a 2025 Microsoft Partner of the Year winner, Faros helps organizations bridge the AI measurement gap to unlock faster, data-driven AI transformation.

Graphic announcing Faros as the winner of the Microsoft Partner of the Year Awards in the Microsoft for Startups category. The image features the Faros and Microsoft logos at the top, with “Winner” and “Partner of the Year Awards – Microsoft for Startups” in bold text on a light blue and purple abstract background with swirling ribbon-like shapes.

Company

3

min

10/8/25

Faros Maintains SOC 2, ISO 27001, and GDPR Certifications

Renewed certifications demonstrate Faros's continued commitment to keeping customer data safe.

shield and lock with digital decorationson a dark blue background

Research

5

min

7/28/25

Lab vs. Reality: What METR's Study Can’t Tell You About AI Productivity in the Wild

METR's study found AI tooling slowed developers down. We found something more consequential: Developers are completing a lot more tasks with AI, but organizations aren't delivering any faster.

A chart from the AI Productivity Paradox Report 2025 showing that AI boosts output, but human review becomes the bottleneck

Research

7

min

7/23/25

The AI Productivity Paradox Report 2025

Key findings from the AI Productivity Paradox Report 2025. Research reveals AI coding assistants increase developer output, but not company productivity. Uncover strategies and enablers for a measurable return on investment.

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AI Industry

6

min

6/16/25

Tackling Tech Debt with AI: A Case Study Using Claude Code

See how AI agents like Claude Code can tackle tedious tech debt, from cleaning test utilities to reducing Docker image size by 50%.

AI Industry

3

min

6/6/25

Claude Code vs Devin: AI Coding Tools Comparison for Developers

Compare Claude Code vs Devin for daily development work. Learn strengths, weaknesses, and best practices from real developer experience using both AI coding tools.

Company

2

min

2/19/25

Faros Partners with Microsoft to Unleash AI-Powered Engineering Efficiency on Microsoft Azure

Now available in Azure Marketplace for procurement with Microsoft Azure Consumption Commitment (MACC), Faros empowers enterprises to optimize engineering with AI

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Customers

6

min

Vimeo relies on Faros for efficient and predictable software delivery

Learn how Vimeo’s engineering organization improved lead times, delivery metrics, and GenAI adoption with centralized visibility and insights into SDLC workflows.

Company

3

min

12/11/24

Globant and Faros Announce Partnership to Drive Faster and More Efficient Agentic AI-Based Projects

Through its collaboration with Faros, Globant will introduce an innovative method for measuring and extracting insights about its team performance and impact on business results, particularly within the software development life cycle.

Image featuring a press release announcement with the text: 'Faros and Globant'

AI Industry

15

min

11/23/24

How much code is AI-generated?

AI generates 25% of Google’s new code. Other organizations seek similar insights to mitigate the risks of this new age of AI-driven development.

Customers

10

min

Why Autodesk chose a platform approach to developer productivity and GenAI impact

Autodesk shares its key learnings from building an internal developer platform with an integrated visibility plane to optimize the software development lifecycle.

Customers

12

min

Riskified improves agility and DevOps maturity with a data-driven approach powered by Faros

Discover how Riskified’s engineering organization strengthens team autonomy and accountability to achieve outstanding business results in the competitive cybersecurity market.

Banner image of Shai Peretz, SVP Engineering at Riskified on a dark blue background with the blog title: Riskified improves agility and devops maturity with a data-driven approach, powered by Faros.

AI Industry

15

min

2/12/24

Lessons from Implementing LLMs Responsibly at Faros AI

How we used GenAI to make querying unfamiliar data easier without letting the LLM take the wheel

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Customers

10

min

SmartBear’s software engineering scales to support rapid growth by measuring outcomes with Faros

Learn how SmartBear monitors portfolio investments to drive growth, improve predictability, and boost customer satisfaction

Customers

8

min

Developer productivity case study: Autodesk's strategic investment as it becomes a platform company

Ben Cochran, VP of Developer Enablement at Autodesk, sat down with Vitaly Gordon, Co-founder and CEO of Faros AI, at the San Francisco Engineering Leadership Council annual event, for a conversation about Autodesk’s developer productivity case study and data-driven approach to engineering.

Ben Cochran Autodesk Developer Productivity Case Study blog banner

Customers

10

min

How Coursera scales world-class software engineering operations to unlock developer productivity

We sat down with Mustafa Furniturewala, SVP of Engineering at Coursera, to talk about all things developer productivity.

Frequently Asked Questions

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