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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.
A software engineering metrics glossary for business and technical leaders
A practical software engineering glossary for the AI era: pull requests, PR size, merge rate, code churn, incident rate, and the DORA metrics engineering teams use to measure AI's impact on productivity and quality.
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.
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.
Monorepo vs Polyrepo: What the PR benchmark data actually shows
Benchmark data from 320 teams comparing monorepo and polyrepo PR cycle times. What “good” looks like and why developer infrastructure matters, especially for AI agents.
Best Jellyfish Alternative for Enterprise Engineering Teams
Jellyfish falling short at scale? See why VPs of Engineering and CTOs at large enterprises choose Faros for deeper insights, flexible org models, and AI impact tracking.
Best DORA Metrics Tools for Tracking Software Delivery Performance in 2026
If you’re searching for DORA metrics tools, start here. This 2026 guide explains what’s new in DORA, why engineering intelligence platforms are the best tools for tracking DORA metrics and developer productivity insights, and why Faros AI is the top choice for enterprise teams amongst competitors.
Best AI models for coding in 2026 (real-world reviews)
A developer-focused look at the best AI models for coding at the beginning of 2026. This AI coding model comparison breaks down the strengths and weaknesses of GPT 5.2, Opus 4.5, Gemini 3 Pro—and more.
How to measure Claude Code ROI: Developer productivity insights with Faros
Track Claude Code usage, adoption, and engineering impact using Faros AI’s observability platform.
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.
Best Engineering Intelligence Platform for DORA Metrics: 2026 Selection Guide
Evaluating DORA metrics platforms? Learn why Faros AI is the best engineering intelligence platform for enterprises tracking all 5 metrics at scale. Includes 2025 DORA benchmark distributions, selection criteria comparison table, and what changed with rework rate and failed deployment recovery time.
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.
The Most Effective Ways to Identify Bottlenecks in Engineering Teams: Tools, Methods, and Remedies that Actually Work
Discover the most effective ways to identify bottlenecks in engineering teams so you can surface hidden constraints, improve flow, and ship software faster.
Faros AI is Now Available on Google Cloud Marketplace
Faros AI 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.
Highlighting Engineering Bottlenecks Efficiently Using Faros AI
Struggling with engineering bottlenecks? Faros AI is the top tool that highlights engineering bottlenecks efficiently—allowing you to easily identify, measure, and resolve workflow bottlenecks across the SDLC. Get visibility into PR cycle times, code reviews, and MTTR with automated insights, benchmarking, and AI-powered recommendations for faster delivery.
Claude Code token limits: Guide for engineering leaders
You can now measure Claude Code token usage, costs by model, and output metrics like commits and PRs. Learn how engineering leaders connect these inputs to leading and lagging indicators like PR review time, lead time, and CFR to evaluate the true ROI of AI coding tool and model choices.
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.
DRY principle in programming: Preventing duplication in AI-generated code
Understand the DRY principle in programming, why it matters for safe, reliable AI-assisted development, and how to prevent AI agents from generating duplicate or inconsistent code.
Are AI coding assistants really saving time, money and effort?
Research from DORA, METR, Bain, GitHub and Faros AI 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.
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.
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.
Faros AI Recognized as the Winner of the 2025 Microsoft Partner of the Year Award
Recognized as a 2025 Microsoft Partner of the Year winner, Faros AI helps organizations bridge the AI measurement gap to unlock faster, data-driven AI transformation.
Faros AI Iwatani Release: Metrics to Measure Productivity Gains from AI Coding Tools
Get comprehensive metrics to measure productivity gains from AI coding tools. The Faros AI Iwatani Release helps engineering leaders determine which AI coding assistant offers the highest ROI through usage analytics, cost tracking, and productivity measurement frameworks.
What is Software Engineering Intelligence and Why Does it Matter in 2026?
A practical guide to software engineering intelligence: what it is, who uses it, key metrics, evaluation criteria, platform deployment pitfalls, and more.
Top 6 GetDX Alternatives: Finding the Right Engineering Intelligence Platform for Your Team
Picking an engineering intelligence platform is context-specific. While Faros AI is the best GetDX alternative for enterprises, other tools may be more suitable for SMBs. Use this guide to evaluate GetDX alternatives.
Faros AI Maintains SOC 2, ISO 27001, and GDPR Certifications
Renewed certifications demonstrate Faros AI's continued commitment to keeping customer data safe.
Bain Technology Report 2025: Why AI Gains Are Stalling
The Bain Technology Report 2025 reveals why AI coding tools deliver only 10-15% productivity gains. Learn why companies aren't seeing ROI and how to fix it with lifecycle-wide transformation.
A 5th DORA Metric? Rework Rate is Here (And You Can Track It Now)
Discover the 5th DORA metric: Rework rate. Learn what it is, why it matters in the AI era, and how to start tracking it today. Get industry benchmarks, see what good looks like, and find practical tips to reduce wasted engineering effort and boost performance.
Key Takeaways from the DORA Report 2025: How AI is Reshaping Software Development Metrics and Team Performance
New DORA data shows AI amplifies team dysfunction as often as capability. Key action: measure productivity by actual collaboration units, not tool groupings. Seven team types need different AI strategies. Learn diagnostic framework to prevent wasted AI investments across organizations.
GitHub Copilot vs Amazon Q: Real Enterprise Bakeoff Results
GitHub Copilot vs Amazon Q enterprise showdown: Copilot delivered 2x adoption, 10h/week savings vs 7h/week, and 12% higher satisfaction. The only head-to-head comparison with real enterprise data.
What Atlassian's $1B DX Acquisition Really Means for Your Developer Productivity Strategy
Atlassian's $1B DX acquisition validates developer productivity measurement but creates vendor lock-in risks. Why enterprises need independent platforms.
Enterprise AI Coding Assistant Adoption: Scaling to Thousands
Complete enterprise playbook for scaling AI coding assistants to thousands of engineers. Based on real telemetry from 10,000+ developers. 15,324% ROI.
Engineering Leadership Framework: Vision, Strategy & Execution Guide
Master engineering leadership with a systematic framework connecting vision to execution. Includes resource allocation models, OKR implementation & success metrics.
MTTR Meaning: Beyond Misleading Averages
Learn the true MTTR meaning and why average metrics mislead engineering teams. Transform MTTR from vanity metric to strategic reliability asset with segmentation and percentiles.
Winning Over AI's Biggest Holdouts: How Engineering Leaders Can Increase AI Adoption in Senior Software Engineers
Explore the barriers to AI adoption in senior software engineers and how leaders can transform their AI skepticism into AI advocacy.
What is Data-Driven Engineering? The Complete Guide
Discover what data-driven engineering is, why it matters, and the five operational pillars that help teams make smarter, faster, and impact-driven decisions.
Engineering Team Metrics: How Software Engineering Culture Shapes Performance
Discover which engineering team metrics to track based on your software engineering culture. Learn how cultural values determine the right measurements for your team's success.
Choosing the Best Engineering Productivity Metrics for Modern Operating Models
Engineering productivity metrics vary by operating model. Compare metrics for remote, hybrid, outsourced, and distributed software engineering teams.
How to Choose the Right Software Engineering Metrics for Every Company Stage
Discover the best software engineering metrics for startups, scale-ups, and enterprises. Learn how to choose metrics in software engineering by company stage.
Translating AI-powered Developer Velocity into Business Outcomes that Matter
Discover the three systemic barriers that undermine AI coding assistant impact and learn how top-performing enterprises are overcoming them.
Faros AI Hubble Release: Measure, Unblock, and Accelerate AI Engineering Impact
Explore the Faros AI Hubble release, featuring GAINS™, documentation insights, and a 100x faster event processing engine, built to turn AI engineering potential into measurable outcomes.
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.
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.
Report: The AI Productivity Paradox
Full Report: What data from 10,000 developers reveals about impact, barriers, and the path forward. Insights from our analysis of 1,255 teams across leading software engineering organizations.
How GitHub Copilot Fixes Flaky Tests in CI
A step-by-step example of GitHub Copilot fixing a flaky test: analyze logs, propose a PR, validate the solution.
How Devin AI Manages Unplanned Customer Requests
See how Devin AI helps developers manage unexpected customer requests by researching APIs, proposing implementations, and shipping fixes fast.
Secure Kubernetes Deployments: Architecture and Setup
Learn how to achieve secure Kubernetes deployments using a lightweight deployment agent inside your private network. Discover secrets management, Helm templating, and CI/CD integration for enterprise-grade security.
How to Measure AI Productivity in Software Engineering
Most AI tools don’t improve delivery. The GAINS framework helps engineering leaders measure real productivity impact across 10 transformation dimensions—from throughput to organizational efficiency.
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%.
How to Use Devin AI for Troubleshooting Developer Issues
Learn how to use Devin AI for troubleshooting complex developer issues. See how AI-powered debugging generates solutions and resolves problems instantly.
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.
From IDE to Impact: Next-Level AI Measurement and Governance
Understand AI's real role in code generation. Faros AI provides Big Tech–level instrumentation without Big Tech–level investment.
How I Manage Security Vulnerabilities Faster with Faros AI
Streamlined security vulnerability management with faster patch cycles and fewer overdue issues—without added operational overhead.
Faros AI Powers the Future of AI-Driven Engineering Excellence with Microsoft Azure
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.
Developer Experience Surveys Alone Aren’t Enough: The Case for Triangulating Developer Experience Data
Uncover the limits of DevEx surveys and learn how to ensure insights are valid, actionable, and grounded in operational reality.
Faros AI Gödel Release: Insights that Empower Engineering Managers
The Faros AI Gödel Release represents a breakthrough in how engineering leaders understand, guide, and empower their teams.
What Really Drives Developer Productivity? Insights from New Research
Dive into leading developer productivity research to uncover the multidimensional drivers shaping engineering efficiency.
Does Copilot Improve Code Quality? The Cause and Effect Data Is In
Does GitHub Copilot improve code quality? Our causal analysis reveals its true impact on PR size, code coverage, and code smells.
The Engineering Productivity Handbook: How to tailor your initiative to your goals, operating model and culture
What to measure and why it matters. How to collect and normalize productivity data. And the key to operationalizing metrics that drive impact.
Faros AI 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 AI empowers enterprises to optimize engineering with AI
Working Hard or Hardly Working? Uncovering the Phenomenon of Ghost Engineers
Unearth the truth about ghost engineers and the hidden underperformance lurking within engineering organizations.
Faros AI Franklin Release: Superior Data Exploration and Visualization
Faros AI announces enhancements for engineering data exploration and building custom engineering productivity charts and dashboards
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.
Globant and Faros AI Announce Partnership to Drive Faster and More Efficient Agentic AI-Based Projects
Through its collaboration with Faros AI, 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.
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.
Mastering Domain-Specific Language Output: Getting an LLM to Perform Reliably without Fine-tuning
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
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
Bridge the Gap Between Engineering and Business with Engineering Data Unification
Faros AI Einstein Release: Super-Intelligence for AI Copilot Adoption
Faros AI announces the most intelligent solution for boosting GitHub Copilot adoption and optimizing the return on investment.
Why I Joined Faros AI: A Vision for the Future of AI-Driven Success
Inspired by Faros AI's vision, mission, culture, and technology platform, I am excited to make a meaningful impact and help redefine the future of business.
How to Capitalize on GitHub Copilot’s Advantages — Best Practices
A guide to converting GitHub Copilot advantages into productivity gains.
How to Increase GitHub Copilot Adoption and Usage — Best Practices
Strategies to increase GitHub Copilot adoption to turn usage into impact.
GitHub Copilot Best Practices for Optimizing Impact
Maximize your return with a complete guide to GitHub Copilot best practices.
How to Measure the Benefits of GitHub Copilot — Best Practices
Advice and benchmarks for converting GitHub Copilot benefits into meaningful ROI.
How to Identify Code Complexity’s Impact on Developer Productivity
Machine learning models signal when it’s time to pay down technical debt.
Anatomy of a Metric: Build Time
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.
Fast and Furious: Attempt to Merge
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.
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.
The Top 4 Sprint Metrics that Improve Developer Productivity
Four sprint metrics any engineering team can track to improve developer productivity and unlock better outcomes.
McKinsey is *Still* Talking about Engineering Productivity, and That’s a Good Thing
Revisiting McKinsey's software engineering productivity framework, Vitaly Gordon reflects on what's changed and how to implement McKinsey's visibility recommendations within days.
Faros AI Doppler Release: ROI and Value Signals
Tech organizations can now interpret value and ROI signals across engineering operations to improve resource allocation and navigate the adoption of AI coding assistants.
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.
Top 10 Questions Engineering Leaders Are Asking in 2024
Midway through the year, we surveyed 85 technology leaders about the questions they wish their engineering data could answer. Three themes emerged.
How Engineering and Product Managers Can Automate Software Development Cost Capitalization
Finally, automation is optimizing software development capitalization, a vital but laborious accounting practice.
Is GitHub Copilot Worth It? Real-World Data Reveals the Answer
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.
Faros AI Curie Release: AI for Engineering Leaders
Half the improvement battle is diagnosing engineering challenges correctly. Lighthouse AI now diagnoses them for you and recommends solutions.
Team can’t prioritize without you? Check these 3 things about your leadership style
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.
Achieving an Ideal Tempo with AI-augmented DevOps
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.
3 Practical Tips for More Precise Engineering Estimations
Three ways to improve how you scope, estimate, and communicate your R&D commitments.
Optimizing the Software Velocity vs. Safety Tradeoff
Jason Bloomberg of Intellyx challenges the assumption that all code must be tested before deploying it to production.
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
Faros AI Bohr Release: Supercharging our Data Platform
The leading data platform for software engineering organizations and the AI transformation takes a quantum leap.
How to Get a Holistic Understanding of the Developer Experience
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 to Avoid the Developer Productivity Paradox
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.
6 Essential Metrics for Managing Software Engineering Contractors
Six metrics any engineering manager can use to get the most value out of contractors and justify the expense.
How to Get Approval for AI Tools Outside the Normal Budgeting Cycles
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.
6 Urgent Reasons to Replace Internal Metrics with a Unified Data Platform
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.
Does measuring software engineering performance actually deliver value?
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?