Episodit
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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?
2025 Engineering Benchmarks Insights WebinarRefactoring x Dev Interrupted SurveyBirgitta’s LinkedInBirgitta’s websiteMartin Fowler Memos
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.
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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:
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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:
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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:
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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.
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?
Topics: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:
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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.
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?
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: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:
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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:
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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 solutions
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 world
Topics:Links:
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:
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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.
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 code
Chapters:Links:
Supercharge Your Operations with AI-Powered Agents | MemraAmir BehbehaniManaging Bot-Generated PRs & Reducing Team Workload by 6%Support the show:
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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.
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
Episode Highlights:Show Notes:
Aarathi on LinkedInClosing the Tech Talent GapManaging Bot-Generated PRs & Reducing Team Workload by 6%Support the show:
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Gen AI for dev teams has been a focal point of conversation for the last few years, but the technology and application are both still very nascent. How can you find the best Gen AI use case for your team, and implement it safely?
This week, our host Dan Lines sits down with Peter McKee, Vice President of Developer Relations and Community at Sonar. They explore the benefits and risks associated with Gen AI, and whether this new tooling is most impactful for junior or senior developers. Regardless of the persona, there needs to be an emphasis on quality control, static code analysis, and the new coaching strategies to help the influx of new code.
Tune in to hear Dan and Peter offer practical advice for engineering leaders on safely experimenting with and integrating Gen AI tools to enhance productivity without sacrificing quality.
00:33 The ins and out of being a VP of Developer Relations and Community04:48 The Importance of wisdom and experience when applying Gen AI08:32 Is there more of a risk for junior developers in this age?19:51 How tooling can help with the influx of Gen AI Code 26:02 The safe ways to roll out Gen AI to developers29:21 Where to start applying Gen AI for your team
Episode Highlights:Show Notes:
Peter McKee (@pmckee) / XPeter McKeeBetter Code & Better Software | Ultimate Security and Quality | SonarDownload The Engineering Leader’s Guide to Accelerating Developer ProductivitySupport the show:
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In an organization as big as Shopify, how can you pioneer exceptional developer experience not only for your team but also for external developers using your product?
This week we’re joined by Eytan Seidman, Director of Product at Shopify to unpack Shopify's approach to building elite engineering teams. Eytan highlights how Shopify’s high-context, high-autonomy culture empowers engineers and product managers to innovate and drive impact. By leveraging a mission-driven culture, Shopify ensures that internal and external developers can contribute effectively to the platform, without being bottlenecked back by inefficient processes or developer experience.
Tune in this week, and discover how you can implement the same processes that have made Shopify so successful.
00:50 What makes engineering and product roles at Shopify special?03:31 How Shopify onboards new hires to drive impact09:05 Pioneering developer experience at Shopify13:28 How Shopify defines success for their platform 17:50 Building high-context, empowered teams29:35 Leveraging AI and LLM’s as a growth opportunity35:29 Advice for product and engineering leaders thinking about their next career step
Episode Highlights:Show Notes:
Eytan Seidmanx.com/eytanseidmanShopifyShopify Developers Platform—Build. Innovate. Get paid.Download your copy of the 2024 Software Engineering Benchmarks Report hereSupport the show:
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Both the aerospace and defense sectors are renowned for long project timelines rife with silos and hurdles that get in the way of productivity. With over 20 years of experience at Lockheed Martin and elsewhere, Robin Yeman literally wrote the book Industrial DevOps on how to implement DevOps principles at traditional behemoths to build faster, safer systems.
As Space Domain Lead at Carnegie Mellon's Software Engineering Institute, Robin’s pioneering work reveals how applying DevOps principles can significantly improve speed, quality, and collaboration at traditional enterprises. She emphasizes the importance of cross-functional teams, modular architectures, and a growth mindset in driving innovation and overcoming the challenges of digital transformation within the aerospace and defense sectors.
Tune in to gain practical insights about the application of DevOps in large-scale systems, the role of organizational design in fostering communication, and how these principles have helped government software teams.
Robin YemanIndustrial DevOpsWiring the Winning Organization - IT RevolutionDownload your copy of the Gen AI Impact Report today
Episode Highlights:
- 01:12 Robin’s book Industrial DevOps
- 04:00 How did Robin’s work at Lockheed Martin lead to Carnegie Mellon?
- 05:46 How should you get started thinking about industrial DevOps?
- 08:01 How Robin’s research came together across varied experiences
- 10:25 What patterns can you adapt to be more successful?
- 16:54 Quantitative vs. qualitative data when making long term plans
- 20:27 Shifting left in Industrial DevOps
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Scaling new product lines within a growing company can be both an opportunity and quite challenging. Semgrep's Head of Engineering Adam Berman joined us this week to share his own experience developing Semgrep's second product line.
Adam was instrumental in developing Semgrep's second product line, and he shares practical strategies for moving from a single-product to a multi-product organization. He unpacks the challenges of organizational design, the importance of fast iteration and feedback loops, and how to build a cohesive company identity with so many moving parts.
If you want to learn how to effectively scale products and how to drive product growth, this episode is a must-listen.
Episode Highlights:
1:10 The challenges of new product lines 4:25 Scaling teams for success and strategies for growth7:30 Finding the right balance between practicality and innovation12:15 A startup within a startup mentality 18:40 Learning through experimentation23:55 Key considerations when navigating product market fit28:20 Driving growth in engineering teamsShow Notes:
Adam Berman on LinkedInAdam Berman (@adamberman_13) / XSemgrepDownload your copy of the Essential Guide to Software Engineering Intelligence PlatformsSupport the show:
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This week, co-host Conor Bronsdon sits down with Amanda Sopkin, Engineering Manager at Asana. Amanda shares her journey from software engineer to manager, discussing the pivotal moment she chose to pursue management over an individual contributor path. We cover the indicators of a successful manager, the red flags to watch for, and the importance of mentorship.
Amanda emphasizes the value of finding the right fit for team members, tailoring leadership styles, and developing a balanced team. Tune in for insights on managing senior versus junior engineers, promoting team members, and striking a balance between professional growth and personal fulfillment.
Amanda Sopkin on LinkedInAmanda Sopkin on Twitter / XAmanda Sopkin’s websiteAmanda Sopkin on GitHubAsana Project Management Software
Episode Highlights:
00:49 Amanda’s Path to Engineering Management
04:58 How to tailor your leadership style to your team
06:40 Unlocking the potential of your team
13:25 Keeping track of your team members individual needs
17:43 Management career goals
20:31 What Amanda is passionate about within engineering
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“If you're not careful, cloud computing can lose more money faster than any invention in history” - Mark Robinson, Infrastructure Engineer at Plaid
This week, guest host Ben Lloyd Pearson sits down with Plaid’s Mark Robinson to learn how he helped Plaid save 25% in costs by optimizing existing resources and eliminating waste in cloud computing.
Mark explains the importance of understanding your cloud bill, identifying areas of overspend, and implementing changes that lead to significant savings. From the basics of tagging resources to the intricacies of optimizing network and storage costs, Mark offers practical tips that can help you uncover countless optimization opportunities.
Tune in to learn about the rewards of improving cloud cost efficiency, the role of organizational buy-in, and the benefits of making cost optimization a company-wide value.
Download your copy of the Essential Guide to Software Engineering Intelligencehttps://www.finops.org/https://www.linkedin.com/in/mark-robinson-944084b
Episode Highlights:
00:56 How did cloud computing get so expensive?
02:34 Digging into what your costs actually are
04:55 How can you account for the various services you use?
07:35 Where are organizations going to get the most value out of?
12:26 Cloud costs relation to better code quality
16:08 Blockers in organizations to cost savings
19:32 Getting buy-in from leadership on cutting cloud costs
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AI is the biggest hype cycle happening in tech right now, but how do you know what’s actually going to make an impact for your product and team vs. what’s just new and shiny?
This week, LinearB COO & Co-founder Dan Lines sits down with Louis Brandy, Member of Technical Staff OpenAI and ex-VP of Engineering at Rockset. Louis shares his unique perspective on the evolution of AI, drawing from his experiences with early days AI work at Meta and now with OpenAI following their acquisition of Rockset. He shares grounded insights into the realities of AI, separating fact from fiction in an industry often clouded by buzzwords and unrealistic expectations.
Listeners will learn about the practical applications of AI, the challenges and opportunities it presents, and how to go past the hype to find AI's potential. Whether you're an AI enthusiast, a skeptic, or a professional looking to understand the true impact of AI for engineering teams, this episode offers an insightful look at one of the most talked-about topics in tech today.
OpenAI Acquires RocksetDownload your copy of the Essential Guide to Software Engineering Intelligence Platforms
Episode Highlights:
00:32 Louis Brandy's background with AI at Meta
04:31 The current AI hype cycle
13:09 How should engineering leaders think about AI and the pressure to use it?
17:58 How to know if you’re falling into the hype cycle
25:50 AI vs. human code
34:42 Real time when it comes to AI
38:36 What should an IC do about AI in their career path?
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When we first saw the talk titled “Space Aliens Are Among Us, Your Product Roadmap is Realistic and Other Lies you Believe,” we knew we had to sit down with Best Egg’s Johnny Ray Austin at LeadingEng SF last year.
Johnny joined our host Conor Bronsdon to discuss how engineering leaders can navigate unrealistic expectations and pressures, drawing from his experiences and relating product roadmaps to the less-than-tangible UFO disclosure we’ve seen in recent years. The conversation explores the pressures engineering leaders face, how to align product roadmaps realistically, and how to manage ambiguity within teams.By aligning engineering goals with business objectives and building a transparent, high-performing engineering culture, you can give your teams the context they need to drive focus and concentration toward the right outcomes.
Episode Highlights:
1:36 Where Johnny came up with the talk title "Space Aliens Are Among Us" 4:15 Advice for engineering leaders struggling with roadmap realism 6:44 Cutting through the noise to find the metrics that matter 11:41 How do teams know if they're moving fast in the right direction? 14:58 How do you handle teams that are getting the wrong input? 20:32 Lies we tell ourselves that we need to get past 28:32 What it’s like to create a new unit inside a company 33:53 Identifying and dealing with ambiguity on your teams 40:45 Johnny’s Thoughts on AIShow Notes
Download your complimentary Gartner® Market Guide: Software Engineering Intelligence (SEI) PlatformsJohnny Ray AustinPersonal Loans | Quick & Easy Application | Best EggSupport the show:
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Engineering leaders have long used value stream management and CI/CD tools to improve software delivery practices. However, an increasing demand for cost and efficiency is leading to the adoption of new technologies. Enterprises are quickly adopting tools that combine deeper levels of visibility into the SDLC with net-new workflow automations, leading to a better developer experience and increased output.
This week's labs episode takes an in-depth look at Software Engineering Intelligence (SEI) Platforms and how engineering teams are using this new technology to gain a competitive advantage. LinearB’s COO and Co-founder Dan Lines along with co-host Conor Bronsdon cover the evolution of SEI, its core capabilities, and how these tools are being used to drive predictability, resource investment strategy and an improved developer experience.
Join our journey into the data insights and workflow automations that are driving the next wave of continuous improvement. Gartner estimates that the adoption of SEI platforms will increase to 50% of engineering teams by 2027 – whether you're a VP, manager, or developer, find out why adopting an SEI Platform is crucial to your future success.
Episode Highlights:
2:39 Digging into the data to find optimizations 4:02 What is Software Engineering Intelligence (SEI)? 9:08 What is profitable engineering and why should it be top of mind? 14:56 How can SEI help a VPE or CTO? 20:43 How does SEI relate to value stream management? 25:05 The role of automation in continuous improvement 29:36 How do SEI platforms help improve GenAI code orchestration? 31:45 What makes a great SEI platform? 34:19 What's next for SEI?Show Notes:
Moneyball (2011) directed by Bennett Miller • Reviews, film + cast • LetterboxdDownload your complimentary Gartner® Market Guide: Software Engineering Intelligence (SEI) PlatformsSupport the show:
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In this episode of Dev Interrupted, Conor Bronsdon is joined by Sanghamitra Goswami, Senior Director of Data Science and Machine Learning at PagerDuty. Sanghamitra shares her expertise in AI and data science, including how engineering teams can effectively leverage both within their organizations. She also explores the history and significance of LLMs, strategies for measuring success and ROI, and the importance of foundational data work. The conversation ends with a discussion about practical applications of AI at PagerDuty, including features designed to reduce noise and improve incident resolution.
LinkedInPagerDutySoftware Engineering Intelligence: Exposed & In Action
Episode Highlights:
00:56 Why are LLMs important for engineering teams to understand?
03:17 How should engineering leaders think about using AI in their products?
07:57 What sort of plan should engineering leaders have to get buy in for AI?
13:22 Are there ways to show ROI on an investment in AI?
15:08 How should we communicate with customers about AI in our products?
18:53 How can companies find a good use case for AI in their product?
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