Latest articles

Supercharging the AI transformation with data-driven insights and orchestration built for the enterprise SDLC. Fully integrated with Microsoft and GitHub products, available on the Marketplace with MACC.

Uncover the limits of DevEx surveys and learn how to ensure insights are valid, actionable, and grounded in operational reality.

Dive into leading developer productivity research to uncover the multidimensional drivers shaping engineering efficiency.

Does GitHub Copilot improve code quality? Our causal analysis reveals its true impact on PR size, code coverage, and code smells.

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

Unearth the truth about ghost engineers and the hidden underperformance lurking within engineering organizations.

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

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.

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.

See how real-world user insights drove the latest evolution of Faros AI’s Chat-Based Query Helper—now delivering responses 5x more accurate and impactful than leading models.

All you need to know about the DORA metrics, and how to measure them. | Faros.ai

Bridge the Gap Between Engineering and Business with Engineering Data Unification

A guide to converting GitHub Copilot advantages into productivity gains.

Strategies to increase GitHub Copilot adoption to turn usage into impact.

Maximize your return with a complete guide to GitHub Copilot best practices.

Advice and benchmarks for converting GitHub Copilot benefits into meaningful ROI.

Machine learning models signal when it’s time to pay down technical debt.

Is the Build Time metric the right measure to demonstrate the ROI of Developer Productivity investments? Does it stand up in court? We examine through real-life trial and error.

A guide to measuring continuous integration metrics, such as CI Speed and CI Reliability, and an introduction to the most important developer productivity metric you never knew existed.

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

Four sprint metrics any engineering team can track to improve developer productivity and unlock better outcomes.

Revisiting McKinsey's software engineering productivity framework, Vitaly Gordon reflects on what's changed and how to implement McKinsey's visibility recommendations within days.

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

Midway through the year, we surveyed 85 technology leaders about the questions they wish their engineering data could answer. Three themes emerged.

Wondering if GitHub Copilot is worth it in 2026? Being the data-driven folks that we are, we put it to the test. Explore the latest product news, features, and available alternatives. Plus, learn what research says about the best practices for a successful AI transformation.

If teams struggle to weigh the tradeoffs without your involvement, it may be a reflection of the systems you’ve put in place as a leader.

As analysts, Intellyx relentlessly mocked bi-modal IT. Today, they caution not to allow the advent of AI-based development tooling to create another such pace separation that throws off the cadence of our engineering organizations.

Three ways to improve how you scope, estimate, and communicate your R&D commitments.

Jason Bloomberg of Intellyx challenges the assumption that all code must be tested before deploying it to production.

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

For many organizations, acting on employee surveys is challenging due to problems in the survey itself and the partial picture it paints. A novel approach is blending survey and systems data to create a more holistic understanding.

How does McKinsey's developer productivity model stand up to scrutiny when comparing the contributions of two very different developers? Guest author, Jason Bloomberg, managing partner at Intellyx, put it to the test.

AI vendors aren't waiting for our normal annual budgeting cycles, nor should you. Be an effective champion with this guide on how to build a business case for unplanned spending.

The costs of continuing down an internal build path are high, while the risks of inaction are rising. The AI revolution signals it's time to take a fresh look at adopting an integrated data platform.

The concept of measuring the performance of software development teams is nothing new, but it recently returned to the public consciousness with a little controversy, thanks to a McKinsey article. Guest Author, Jason English shares his perspective on why everyone hasn't already jumped on the measurement bandwagon?

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

What’s the difference between these pull and push options and which approach may work best for your data source?

A product manager at a leading US bank had to drive to a branch to confirm a new ATM feature was live. Faros AI is delivering those answers to your Inbox or Slack.

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.

New and renewed certifications demonstrate Faros's continued commitment to keeping customer data safe.

Seasoned pros share tips on getting the timing right, harnessing the insights, avoiding "big brother", and whether to build or buy — or perhaps both...?

A simple checklist can help engineering managers achieve net positive gains in team productivity, lead time, and quality.

GitHub Copilot is one of the fastest adopted tools in the history of software development. One year after its release, over 1 million developers and 20,000 organizations are using the tool. But how to measure its impact on your engineering operations? Read on..

Is platform engineering the future of DevOps? Read this interesting post, which includes a generous reference to related articles on this subject and analyzes whether it is just another cool buzzword?

Digital transformation strategies must be based on a comprehensive understanding of an organization's software engineering practices. Learn how top consulting firms (like Accenture, McKinsey, Deloitte, EY) partner with customers to gain a comprehensive view of their practices to drive most effective transformations.

The lessons learned from the modern data stack (MDS) come in when building data pipelines to connect data from disparate tools. In this episode, Lars Kamp and Vitaly Gordon discuss about engineering productivity, DORA Metrics, Faros Open-source community edition, and more...

Everything you need to know about Mean Time to Recovery (MTTR): A Key Metric in DevOps.

The 2022 Accelerate State of DevOps Report by Google Cloud’s DevOps Research and Assessment team (DORA) came out just a few weeks ago and the results are honestly quite shocking (or maybe not so after all?) - let’s discuss.

Adding more headcount to an organization is an expensive band-aid fix that substantially increases the complexity of the system and often slows it down. Read this candid perspective to learn how software engineering teams can "do more with less".

Since Accelerate was published in 2018, “DORA metrics” have become increasingly popular for measuring IT performance. More vendors are creating dashboards or integrating these metrics into their existing pipeline tooling. However, the context is getting lost in the race to deliver these features to customers.

The State of OSS Report - We decided to evaluate top open-source projects from GitHub on their EngOps performance, and, by treating an open-source community as an engineering organization, see how they compare to their closed source counterparts. Some interesting findings in here.

A comprehensive guide on "Deployment Frequency", one of the 4 key DORA Metrics - What it means, Why it is important, and how to measure it. Read on...

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

It was strikingly obvious that the engineering function in most companies my peers and I worked for, have not been able to fully leverage all the data in a unified manner. The problem - data is often scattered across disparate systems. A better data-driven approach is a must if we want to move from gut-feeling and guesswork to intelligent actions that impact real business outcomes.

A comprehensive guide on "Change Failure Rate", one of the 4 key DORA Metrics. Read on to learn all about it and how to measure Change Failure Rate.

One of the predictive metrics for measuring your pace of software delivery is sprint velocity. Calculating this metric doesn't magically make your engineering team more productive overnight, but it does help you better plan projects and predict realistic timelines.

Lead time measures the velocity of an engineering organization in delivering software — from idea to production. Shorter lead times mean shorter turnaround times for new feature requests, incident resolutions, bug fixes etc. In this blog post, learn more about lead time and cycle time for software delivery, and how to measure them.

With the right tools, engineering leaders can use data to identify bottlenecks, measure progress, better support teams and accurately assess impact over time.