Open Source Meets AI | Red Hat's Scott McCarty

There’s AI agents. There’s AI tooling. Do either drive business impact or are they just more things your dev team is supposed to stay on top of?Birgitta Boeckeler, Global Lead for AI Assisted Software Delivery at ThoughtWorks, joins the show to discuss the practical applications of AI in software delivery. She shares her research on AI agents, highlights areas where AI hasn't lived up to the hype, and offers concrete examples of useful AI tools for development teams.Dan Lines then joins the conversation to provide his perspective on how engineering leaders can leverage these insights to effectively implement AI within their own teams. He also discusses LinearB's efforts in helping software teams measure the business impact of AI.Show Notes:2025 Engineering Benchmarks Insights WebinarRefactoring x Dev Interrupted SurveyBirgitta’s LinkedInBirgitta’s websiteMartin Fowler MemosSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Open source has transformed software development, but can it do the same for AI?In this episode of Dev Interrupted, Conor Bronsdon talks with Scott McCarty, Senior Principal Product Manager at Red Hat, about the potential of open source AI to revolutionize enterprise DevOps. They discuss the challenges and opportunities of open source AI, including licensing, security, and the need for community-driven development. McCarty argues that open source AI is crucial for building trust and ensuring that AI benefits everyone, not just a select few.Show Notes:2025 Engineering Benchmarks Insights WebinarRefactoring x Dev Interrupted SurveyScott’s LinkedInSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Everyone knows the era of growth at all costs is over, but where does that leave us? And specifically, where does that leave founders? The answer is straightforward: founders have to start thinking like business people. This week, Conor Bronsdon interviews Ashish Aggarwal, founder and CTO of Productive and an active investor in over 30 companies.Ashish shares his insights on how startups are adapting to the new “efficient growth” environment, why this paradigm shift is an opportunity for founders, and how the pressures of efficiency have created incentives for companies to move towards geo-distributed teams instead of co-located teams.Show Notes:Refactoring x Dev Interrupted SurveyAshish’s LinkedIn2024 State of SaaS Consolidation ReportSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

It’s time we recognize the idea of a ‘Golden Path’ is unrealistic.In this episode of Dev Interrupted, host Dan Lines is joined by Cory O'Daniel, CEO of MassDriver, to discuss Cory’s provocative article 'DevOps is Bullshit'. They cover the pitfalls of DevOps, the evolution of cloud operations and whether or not platform engineering is the solution the industry needs .Cory shares insights on why many organizations struggle with DevOps implementation, the impact of cloud technology on traditional operations, and how internal developer platforms are reshaping the industry.Topics:01:03 Where has DevOps gone wrong?04:19 Have we changed or does DevOps mean something different?11:51 Platform engineering in 202420:10 How can platform engineering leaders measure success?26:40 Why are new hires being put in charge of DevOps?29:53 Getting buy in for a better platform engineering experience39:13 Are internal developer platforms a fad? Show Notes:Refactoring x Dev Interrupted SurveyCory O'DanielMassdriver - Standardize Infrastructure | Enhance Developer Experience | Enable Self-ServiceCory O’Daniel k8s/acc (@coryodaniel) / XDevOps is BullshitBridging Cloud Talent GapSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

This week, host Conor Bronsdon chats with Dheeraj Pandey, CEO and co-founder of DevRev. Dheeraj shares his incredible journey from leading Nutanix to a valuation of $16 billion, to now striving to build another unicorn with DevRev.Dheeraj opens up about the lessons learned from his entrepreneurial journey, emphasizing the significance of having a holistic approach to building products and companies. He explores how his experiences at Nutanix have shaped his vision at DevRev, especially in terms of integrating AI as a core component rather than a mere add-on.The discussion also covers a range of topics including the transformative power of AI in business operations, customer-centric design, and the importance of balancing innovative technology with intuitive user experience.Topics:02:49 What inspired you to start DevRev?08:38 How did you decide not to take a bolt on approach to AI?11:30 What can other entrepreneurs learn from you about levelling up their abilities?16:42 How are you approaching scaling up DevRel?28:11 How is DevRev thinking about AI driven design?44:52 What's happening with DevRev's leadership in AI?Links:Dheeraj PandeyDheeraj PandeyDheeraj Pandey (@dheeraj) / XDevRev (@devrev)Dheeraj PandeyDownload the Engineering Leader’s Guide to Accelerating Developer ProductivityUnified SupportOpening WindowsFounder ModeOvercoming Growth CrisesZanzibar: Google’s Consistent, Global Authorization SystemSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

This week, co-host Conor Bronsdon sits down with Daniela Miao, co-founder and CTO of Momento, to discuss her journey from DynamoDB at AWS to founding the real-time data infrastructure platform Momento. Daniela covers the importance of observability, the decision to rebuild Momento's stack with Rust, and how observability can speed up development cycles. They also explore strategies for aligning technical projects with business objectives, building team trust, and the critical role of communication in achieving success. Tune in for valuable insights on leadership, technical decision-making, and startup growth.Topics:02:01 Why is observability often treated as an auxiliary service?06:14 Making a push for observability13:32 Picking the right metrics to observe and pay attention to15:49 Has the technical shift to Rust paid off?19:23 How did you create trust and buy in from your team to make a switch?26:31 What could other teams learn from Momento’s move to Rust?38:15 Advice would you give for other technical founders?Links:Daniela MiaoThe Momento BlogMomento: An enterprise-ready serverless platform for caching and pub/subUnpacking the 2023 DORA Report w/ Nathen Harvey of Google CloudGoogle SRERust Programming LanguageSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

This week, our host Dan Lines chats with Malte Ubl, CTO of Vercel, about why iteration speed is a game-changer for teams trying to deliver more efficiently. Malte shares how accelerating the development cycle and embracing platform engineering can supercharge productivity, helping teams ship faster and innovate more effectively.We explore what it really means to streamline workflows, reduce bottlenecks, and create an environment where developers can focus on what they do best—building great products. Malte also gives us a behind-the-scenes look at how engineering strategies are evolving to keep up with the ever-growing demands.Topics:01:14 How do you see platform engineering changing the way modern software engineering functions?04:52 Decentralized vs. centralized teams?11:40 How Vercel is using AI13:30 All about AI SDKs20:41 How should platform engineering teams should be using AI?28:02 Power struggles between high level ICs and a high level managers?30:10 Key factors to focus on when optimizing AI applications?35:11 Advice for other CTOs or engineering leadersLinks:Malte Ubl (@cramforce)About Malte UblMalte Ublv0 by VercelVercel: Build and deploy the best web experiences with the Frontend CloudDownload the Engineering Leader’s Guide to Accelerating Developer ProductivitySupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

What are the limitations of general large language models, and when should you evaluate more specialized models for your team’s most important use case?This week, Conor Bronsdon sits down with Brandon Jung, Vice President of Ecosystem at Tabnine, to explore the difference between specialized models and LLMs. Brandon highlights how specialized models outperform LLMs when it comes to specific coding tasks, and how developers can leverage tailored solutions to improve developer productivity and code quality. The conversation covers the importance of data transparency, data origination, cost implications, and regulatory considerations such as the EU's AI Act.Whether you're a developer looking to boost your productivity or an engineering leader evaluating solutions for your team, this episode offers important context on the next wave of AI solutionsTopics:00:31 Specialized models vs. LLMs01:56 The problems with LLMs and data integrity12:34 Why AGI is further away than we think16:11 Evaluating the right models for your engineering team23:42 Is AI code secure?26:22 How to adjust to work with AI effectively 32:48 Training developers in the new AI worldLinks:Brandon Jung on LinkedInBrandon Jung (@brandoncjung) / XTabnine (@tabnine) / XTabnine AI code assistant | Private, personalized, protectedManaging Bot-Generated PRs & Reducing Team Workload by 6%Support the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Engineering teams are already seeing efficiency gains by leveraging Gen AI solutions like Copilot, but the next wave of AI workflows has the potential to 10X productivity.This week, we’re exploring the world of Agentic AI with Amir Behbehani, Chief AI Engineer and Founder of Memra. Agentic AI can be defined as AI agents or systems that have the capacity to make decisions or take actions on their own based on the objectives they are programmed to achieve. These AI systems act independently, gathering information, processing it, and then choosing or executing actions without direct human intervention.Amir shares how Memra is leading the way in developing AI agents capable of handling complex tasks, decision-making, and improving productivity across industries. He also discusses the implications of AI in reshaping how businesses operate, and how organizations can prepare for a future where AI plays a central role in both day-to-day operations and high-level strategic decisions.Whether you're an AI enthusiast, an engineering leader, or curious about the future of automation, this episode offers a deep dive into the possibilities and challenges of Agentic AI and what it means for the future of work.Chapters:01:23 Defining Agentic AI 07:02 Frameworks for thinking about Agentic AI 12:52 Unpacking AI as a black box 13:58 How Agentic AI will benefit software engineers 22:55 What would be a good starting point to leverage agents on an engineering team?26:46 Will agents replace freelancers and the gig economy?36:20 What is the synthetic marketplace?40:11 How Agentic AI impacts writing codeLinks:Supercharge Your Operations with AI-Powered Agents | MemraAmir BehbehaniManaging Bot-Generated PRs & Reducing Team Workload by 6%Support the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

According to a LinkedIn study, engineers with strong soft skills are promoted 13% faster than those with only technical skills. Given how AI will continue to reshape market demands for developers and engineering leaders, how can you adapt to these changes and further your career?This week we’re joined by Aarathi Vidyasagar, VP of Engineering at LinkedIn, to explore the growing importance of soft skills and how leadership, communication, and empathy are becoming just as critical as technical expertise.Aarathi shares how LinkedIn is preparing engineers to thrive in this new environment, focusing on upskilling teams to navigate AI and empower collaboration and innovation through strong interpersonal skills. She offers valuable takeaways into building engineering teams that balance hard technical abilities with the soft skills needed to lead, mentor, and work effectively in diverse teams.For anyone interested in the future of engineering and the rising demand for soft skills, this episode offers an important perspective on how to equip your teams for long-term success in an AI-driven world.Episode Highlights:00:56 How industry changes have impacted the need for communication and soft skills 04:31 How software development is going to continue to change 12:33 Generalists vs Specialists 15:52 How is LinkedIn positioned for the new era of hiring?31:11 How is LinkedIn approaching developer experience and productivity?36:33 How to support devs in automating migrations Show Notes:Aarathi on LinkedInClosing the Tech Talent GapManaging Bot-Generated PRs & Reducing Team Workload by 6%Support the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever