LinearB

We are proud to be recognized as one of Forbes’ 2025 Best Start-Up Employers, ranking #64 overall and #1 in our category. 💪 This recognition highlights our commitment to fostering an exceptional workplace culture, attracting top talent, and delivering cutting-edge technology to software engineering teams around the globe. 💬 “At LinearB, we’ve built a culture that values collaboration, innovation, and continuous improvement—both for our employees and the engineering teams we support.” - Ori Keren, CEO and Co-Founder of LinearB. As we continue to expand, we are also pleased to welcome Patrick McKinney, ex-Sonar, as our new Chief Revenue Officer (CRO). Patrick brings extensive experience in scaling high-growth SaaS companies and will lead sales, technical services, customer success, and operations. Patrick will lead our go-to-market strategy as we bring AI-powered developer experience and workflow automation to more teams worldwide. 💬 “LinearB’s commitment to improving engineering productivity and developer experience is second to none. The combination of an exceptional product, a data-driven approach to software delivery, and a culture that prioritizes innovation made this an easy decision for me. I’m excited to help accelerate LinearB’s impact as we empower engineering organizations worldwide.” With continued investment in AI-driven workflows, software engineering intelligence, and developer experience solutions, we are excited to lead the future of the engineering productivity movement. For more information about career opportunities, visit: https://linearb.io/careers

Velocity is a diagnostic tool, not a productivity KPI. On Stack Overflow’s Leaders of Code podcast, our Co-founder and COO Dan Lines sat down with Ben Matthews (Sr. Director of Engineering at Stack Overflow) to talk about what engineering leaders should be measuring. They cover: • How DevEx teams drive cross-functional alignment • Where AI and automation are making room for more complex, meaningful work • How non-technical teams are contribute to engineering tasks through the democratization of technology Listen here: https://lnkd.in/eJZQPYTB

You adopted Copilot.  Now what? AI isn’t just assisting developers anymore, it’s orchestrating the entire software delivery lifecycle. Join us on June 4th or 5th for a 35-minute workshop* on what’s next for AI in software development, where you’ll learn how enterprises use AI workflows to drive developer productivity and experience. Our goal is for you to walk away with: Your next AI initiative: We’re entering a new phase of AI – one that doesn’t just assist, but acts. We’ll be identifying opportunities to pilot agentic AI in critical workflows. Translations of AI adoption to business impact: Learn how enterprise leaders shift the conversation from innovation to bottom-line results. Real stories from the enterprise: Understand how modern teams like yours are shifting to AI-orchestration workflows and gaining a competitive advantage. *All registrants will get the recording + our newest data report The DevEx Guide to AI-Driven Software Development to share with their teams. Reserve your spot → https://lnkd.in/gGMCG4CR 

How do you scale routine code migrations across thousands of files and multiple languages, without burning out your developers? Google just shared how they used LLMs to automate identifier migrations (32-bit → 64-bit) across their codebase. AI wrote nearly 75% of the code, and developers say it boosted productivity by 50% Compared to a similar manual effort that took two years, this approach cut the workload in half. Better yet, the process was repeatable, validated, and safe. Rather than chasing experimental use cases, Google focused on high-effort, low-complexity tasks that AI could handle well. This is a practical blueprint for engineering leaders looking to deploy AI for real outcomes. Break down the strategy and see how it applies to your team: https://lnkd.in/gNRSp5vK

Is AI actually going to *decrease* developer productivity in 2025?! Last week I spoke with Ori Keren, founder of LinearB, and this was just one of his many hot takes! With Ori we explored how teams are integrating AI into the SDLC, with some… surprising insights. Here are some great takeaways from our chat: ↳ 🧠 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗶𝘀 𝗸𝗶𝗻𝗴 — AI effectiveness depends on context. Current tools often lack crucial info beyond the codebase, like operational data or business goals, limiting their potential. ↳ ⚙️ 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝘁𝗵𝗲 𝘄𝗵𝗼𝗹𝗲 𝗦𝗗𝗟𝗖 — generating code faster creates bottlenecks elsewhere (like in code reviews). So you should focus on making *all* the steps faster, to avoid more toil on humans. ↳ 🧪 𝗘𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁 𝘄𝗶𝘁𝗵 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 — bridge the gap to AI-native development by doing experiments in controlled, low-risk areas, with clear policies on usage and decision making. But don't be afraid to go full AI-first in those! ↳ 🧑💻 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝘀𝗸𝗶𝗹𝗹𝘀 𝗮𝗿𝗲 𝘀𝗵𝗶𝗳𝘁𝗶𝗻𝗴 — critical thinking, reading code effectively, and prompt engineering are becoming essential skills alongside traditional coding expertise, and are here to stay. ↳ 🎓 𝗘𝗱𝘂𝗰𝗮𝘁𝗲 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺𝘀 — proactively create programs to help senior devs adapt to AI tools and ensure junior devs build strong fundamentals and critical thinking skills. I am attaching the full interview in the comments!

LinearB is officially Great Place To Work US® Certified in the U.S. and Israel! This recognition is based entirely on feedback from our employees — the people who make our company such a special place to be. We're incredibly proud of the culture we’re building together across teams, time zones, and countries. Thank you to our amazing team for your trust, voices, and ongoing commitment to growing with us. Your feedback not only earned us this certification but also shapes what comes next. We're excited to keep listening and continue improving together. If you’re looking for a great place to work, check out our careers site: https://linearb.io/careers 

A single zero derailed the logic. AI caught it before we did. This bug was subtle: a value that should have been the smallest in a progression ended up being the largest. LinearB’s AI Code Review flagged the issue immediately. Not just the what, but the why: “This threshold value doesn’t follow the logical progression of thresholds that decrease as PR size increases.” When AI understands context, not just syntax, your team can ship smarter, faster, and with more confidence. This type of insight saves hours of testing, rework, and back-and-forth. Read our blog on AI Code Reviews here: https://lnkd.in/gNKbvF87 

Three major, app-breaking issues, not a single Copilot comment. LinearB’s AI code review caught all of them, with clear explanations. Big shoutout to Sean Erswell and the IKEA engineering team for pushing the boundaries with AI-driven productivity. The reality is that when it comes to PR quality, accuracy, and building developer trust, not all AI reviews are created equal. LinearB's AI code reviews deliver deep, contextual insights to identify risky code, offer actionable fixes, and provide the "why" behind every suggestion. This is what the future of engineering productivity looks like, and it’s only the beginning. Get started here: https://lnkd.in/gmKR68a6

Saying "we saved 16,000 hours with AI automation” might sound impressive, but for the executive team, what’s more powerful is saying: “We reinvested 16,000 hours into higher-value work by automating manual dev processes.” That reframing turns a number into a business outcome. The same goes for metrics like cycle time. It’s a great outcome metric, but not all “2-day” cycles are created equal. Are your devs spending those days building features? Or waiting on CI/CD to deploy? When DevEx and Platform teams communicate impact, the language you use makes all the difference. High-performing teams don’t just optimize metrics. They translate them. Learn how engineering leaders are translating metrics like cycle time and AI impact into language the board understands. Watch our last workshop with Guillermo M. and Yishai Beeri here: https://lnkd.in/gRj7RKEP 

PRs rarely stall because people don't care. They stall because people don't know. In fast-moving teams, even the best intentions can’t fix a review process built on hope and habit. When developers miss PR notifications or have to context-switch just to figure out if a review is urgent, momentum dies. But when the right information surfaces at the right time, something powerful happens: - Pickup time shrinks. - Review depth improves. - Delivery risk drops. All of this without sacrificing speed. LinearB's PR notifications provide context-rich nudges that tell your team exactly where to focus, when it matters most. The result is less friction, faster merges, and stronger code health across the board. Turn code reviews from a bottleneck into a catalyst for delivery, and you might soon find your review time drop to the time it takes to click a single button.