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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.

Tech organizations can now interpret value and ROI signals across engineering operations to improve resource allocation and navigate the adoption of AI coding assistants.

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.

Finally, automation is optimizing software development capitalization, a vital but laborious accounting practice.

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.

Half the improvement battle is diagnosing engineering challenges correctly. Lighthouse AI now diagnoses them for you and recommends solutions.

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

The leading data platform for software engineering organizations and the AI transformation takes a quantum leap.

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.

Six metrics any engineering manager can use to get the most value out of contractors and justify the expense.

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

How Faros is maximizing the productivity of human and AI-powered engineering and strengthening internal collaboration with business partners

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..

I am delighted to announce that we have raised $20M in Series-A financing, led by one of the most successful VC investors in Silicon Valley and the first board member in iconic companies like Gitlab, Splunk, Fastly, and Bill.com, David Hornik of Lobby Capital...

Today we are very excited to reveal Lighthouse AI - the foundational artificial intelligence engine built into the Faros platform, designed to help engineering organizations make sense of the vast amounts of data that they produce every single day. Learn more...

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 Faros AI infrastructure leverages a proven modern data stack: Airbyte, Hasura, Metabase, Activepieces, and dbt — specially customized to handle the nuances of Engineering Operations data. And unlike blackbox solutions, it is designed to grow with the growing needs of your engineering organization. Read On ...

As an engineer at an early-stage startup I wear a lot of different hats. Some days I focus on coding; on others, I focus on designing features and defining the work for our contractors. Read this post to learn more about how I leverage Faros AI to make my job easier.

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.

I’m excited to share the news that I am joining Faros to lead the global BD and Partnerships efforts.

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".

The synergy between McKinsey’s Agile360 methodology and Faros’s software engineering intelligence is strong, and the benefit to our mutual clients is boundless. Read more to learn about the joint capabilities...

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.

Value Stream Management is a lean business practice that focuses on increasing the flow of value from customer demand to delivery. This article will provide a brief overview of value stream management, explain how value stream flow can be measured, and discuss how to get started with value stream management.

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.

I’m very proud of the Faros team and all the innovation they have accomplished up to this point. And I’m thrilled to join full-time and help build and scale the Marketing function.

Listen to this interesting conversation with George Anadiotis, ZDNet and learn more about Faros AI!

Faros AI has raised $16 million in seed funding led by SignalFire, Salesforce Ventures, Global Founders Capital and Operator Collective.

The open-source community edition of Faros — Faros CE — now available for free on GitHub. Faros CE provides ELT, APIs, BI, and automation for engineering operations data.

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