Podcasts about engineering leadership

In this episode, we're joined by Eric Ries, creator of The Lean Startup, to discuss insights from his latest book, Incorruptible: Why Good Companies Go Bad… and How Great Companies Stay Great. Eric shares what inspired him to write the book and why we need to move beyond and redefine what true profit looks like. He shares the history behind businesses transitioning from serving public interests to shareholder primacy and why leaving behind a people-first business approach can actually reduce profitability. Additionally, Eric discusses financial gravity, the “harder is easier” principle, and how these practices connect to AI & current engineering leadership challenges.   ABOUT ERIC RIES Over the last two decades, Eric Ries's ideas about continuous innovation, long-term thinking, governance, and market reform have reshaped company building and management practices. He is the creator of the Lean Startup method, and the author of the New York Times bestseller The Lean Startup; The Leader's Guide; and The Startup Way. As a founder, he has put his own ideas into practice with The Long-Term Stock Exchange (LTSE); Answer.AI, an AI R&D lab; Virgil, a legal services startup; and IMVU. On The Eric Ries Show, he talks with world-class technologists, thought leaders, and executives building for the long-term. He lives in the San Francisco Bay Area with his wife and three children.   Unblocked: The context engine your coding agents are missing. Give your coding agents the context your best engineers have. Your agents can read code, but they don't know how your team works. Rules and MCPs give access to information but not understanding. That's why you still have to tell them where to look and what to look for. Unblocked gives your agents the history, conventions, and decisions behind your code so they generate mergeable output without the back and forth. It automatically surfaces the right context for every task, so agents stay on track without the set up tax or the correction loops. getunblocked.com/elc   SHOW NOTES: The inspiration behind Eric's new book Incorruptible (5:22) What it means to redefine profit (8:03) Understanding profit considerations like externality, ethics, and inputs (10:44) Why human life / value can never be an input factor of production (12:31) The history behind business practices benefitting the public (15:00) When businesses transitioned to shareholder primacy over public interest (17:16) Navigating the tension between mission vs. fiduciary responsibility (21:01) The role of financial gravity & shareholder primacy in the Silicon Valley bank story (25:04) Using Eric's book to build a mission-driven roadmap (29:12) How committing to a principled way of business can drive profitability (31:15) An example of the principle “harder is easier” (33:40) How this connects to AI & emerging eng leadership challenges (36:53)   LINKS AND RESOURCES Incorruptible: Why Good Companies Go Bad and How Great Companies Stay Great - Drawing on two decades of work with founders, CEOs, and investors, best-selling author Eric Ries reveals the forces that make companies vulnerable to destruction from within and without. Then he offers solutions that safeguard against them for the long-term. Incorruptible is the blueprint for companies that will prosper and endure without losing their soul. Its lessons and tools are designed to help founders, executives, investors, and citizens of all kinds build organizations – and a society – truly aligned with human flourishing. https://news.theleanstartup.com/ - Eric's newsletter with ideas about how and why to build companies focused on human flourishing — and stories of the people who are doing it. The Eric Ries Show - Founder, entrepreneur, and best-selling author of The Lean Startup Eric Ries discusses how to build profitable companies for the long-term benefit of society. Ries talks with world-class technologists, thought leaders, executives, and others working to create a new ecosystem of trustworthy organizations with limitless potential for growth and a deep commitment to purpose. Together, they uncover the tools and methods to ensure the next generation of companies are designed to maximize human flourishing for generations.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In Elixir Wizards S15E04, Charles Suggs and Emma Whamond are joined by Somtochi Onyekwere, a software engineer at Fly.io and contributor to the Corrosion distributed database project, to talk about distributed systems, infrastructure resilience, and the growing fragility of centralized cloud platforms.   We discuss what recent outages across major providers reveal about modern infrastructure and why more teams are starting to rethink assumptions around reliability, failover, and system design. Somtochi explains how Fly.io approaches geographic distribution, eventual consistency, and replication across nodes, along with the trade-offs that come with building systems this way.   The conversation explores CRDTs (Conflict-free Replicated Data Types), consensus, split-brain prevention, and what actually happens when distributed systems fail in production. We also talk about testing strategies, rollback planning, property-based testing tools, and how teams can reduce blast radius when things inevitably go wrong.   Along the way, we discuss AI infrastructure, sandboxing AI agents, and how newer workloads may add pressure to already centralized systems. The episode closes with practical advice for developers who want to build more resilient applications without over-complicating their architecture. Topics Discussed in this Episode: Corrosion and distributed database replication Centralized cloud fragility and recent outage patterns Distributed systems versus traditional cloud architectures Multi-region deployment strategies for Phoenix applications CRDTs and conflict resolution in distributed systems Eventual consistency versus strict consistency tradeoffs Consensus, leader election, and split-brain prevention Testing failover and recovery scenarios Property-based testing and Antithesis Rollback planning for database schema migrations Reducing blast radius through system isolation Health checks and blue-green deployment strategies Fly Proxy request routing and replay behavior Cross-region synchronization and replication challenges Single points of failure inside “redundant” systems Backup restoration testing and disaster recovery planning Network partitions and failure handling in production Infrastructure monitoring and operational visibility AI infrastructure workloads and operational strain Sandboxing and securing AI agents Sprites and AI workflows at Fly.io Latency improvements from geographic distribution Distributed systems tradeoffs in real-world environments Transitive dependency failures across cloud providers Practical resilience strategies for modern engineering teams Links Mentioned: https://fly.io https://github.com/superfly/corrosion https://docs.gitops.weaveworks.org/ FluxCD https://fluxcd.io/ Fly.io Stateful Sandbox Environments https://sprites.dev/ Cloudflare Workers AI Inference Platform https://www.cloudflare.com/products/workers-ai/ “An AI Agent Just Destroyed Our Production Data. It Confessed in Writing” Twitter post from PocketOS founder: https://x.com/lifeof_jer/status/2048103471019434248 Oct 2025 AWS Outage https://www.theguardian.com/technology/2025/oct/24/amazon-reveals-cause-of-aws-outage Dec 2025 Cloudflare Outage https://www.theguardian.com/technology/2025/dec/05/another-cloudflare-outage-takes-down-websites-linkedin-zoom July 2025 Crowdstrike Outage https://www.ibm.com/think/news/recent-crowdstrike-outage-what-you-should-know March 2026 Stryker Cyber Attack https://www.stryker.com/us/en/about/news/2026/a-message-to-our-customers-03-2026.html https://aws.amazon.com/ https://cloud.google.com/ https://azure.microsoft.com/en-us https://fly.io/docs/elixir/ CRDTs!! https://smartlogic.io/podcast/elixir-wizards/s13-e03-local-first-liveview-svelte-pwa/ https://antithesis.com/docs/resources/property_based_testing/ https://hex.pm/packages/proper

Send us Fan MailIn this episode of ENGINEERING CH∆NGE®, I take a systems-centered look at one of the biggest conversations happening across engineering organizations and society right now: AI.While many organizations are focused on AI models, tools, productivity, and technical readiness, this episode explores a deeper question:What happens when AI is introduced into systems that already struggle with communication gaps, lack of trust, inequitable processes, or flawed decision-making?Drawing on examples from industry and recent research, we'll discuss:• The disconnects AI adoption is exposing between leaders and employees• How AI acts as an amplifier within organizational systems• Why “human in the loop” must involve accountability, not just oversight• How people-centered organizational systems shape AI outcomes• Systems-level questions leaders should be asking before scaling AI adoptionI also introduce MESA® (Measure, Evaluate, Strategize, Act), a framework we use at The PEER Group to help organizations navigate change and continuous improvement.If you've been thinking about AI primarily as a technology issue, this episode invites you to consider the organizational systems shaping what AI will ultimately produce.Grab a latte and listen.Request your free copy of the ebook Engineering for Society at engineeringchangepodcast.com.If this conversation resonates with you, follow ENGINEERING CH∆NGE® and leave a five-star review to help more engineers and leaders join the conversation.Support the showENGINEERING CHΔNGE® is a registered trademark held by Dr. Yvette E. Pearson for producing and providing podcasts.

In this episode, Geddes Munson (SVP of Engineering @ Affirm) joins us to discuss operational / engineering excellence, scaling, and AI-native transformation! We explore Affirm's approach to operational and engineering excellence and how a 2024 outage became a turning point in refining that focus. We deconstruct “AI retooling week”, the internal tools it inspired (including an incident tracing system), how the AI-native transition is impacting operational / engineering excellence, and how to connect these projects to business goals. Plus, we take a look at their early work building in agentic commerce, infrastructure decisions they made years ago setting them up for success now, how they're thinking about designing for agent-first experiences.   ABOUT GEDDES MUNSON Geddes Munson serves as Affirm's SVP, Engineering. Previously, Geddes held several engineering leadership roles at Affirm, including oversight of the merchant engineering group, where he was responsible for the development of Affirm's solutions for key partners including Amazon, Shopify and Walmart. Prior to Affirm, Geddes held various technical leadership roles at rapidly growing startups including Mixpanel, SingleStore and EasyPost. He received his B.A. from Haverford College, where he started the Linux club on campus. Geddes lives in New Jersey with his wife and three children.   Unblocked: The context engine your coding agents are missing. Give your coding agents the context your best engineers have. Your agents can read code, but they don't know how your team works. Rules and MCPs give access to information but not understanding. That's why you still have to tell them where to look and what to look for. Unblocked gives your agents the history, conventions, and decisions behind your code so they generate mergeable output without the back and forth. It automatically surfaces the right context for every task, so agents stay on track without the set up tax or the correction loops. getunblocked.com/elc   SHOW NOTES: Defining operational excellence & what it looks like @ Affirm (4:36) Understand why your company / product matters to your customers (8:11) Key pivot points around engineering excellence @ Affirm (11:10) Creating a genuine culture change of operational / engineering excellence (14:27) Adopting agentic models @ Affirm (16:30) Navigating the balance between transformation, safety & reliability (18:30) Affirm's AI retooling week & hackathon setup (20:57) How the hackathon helped quickly change the company culture (23:15) Ensuring your practices serve your overall organizational vision & goals (26:11) Insights on scaling & increasing CICD investment @ Affirm (28:28) Approaches to building agentic commerce products (30:11) Strategies for building an agent-first experience (33:33) Bridging the gap between engineering & business goals / outcomes (35:44) Rapid fire questions (38:46)   LINKS AND RESOURCES 1929: Inside the Greatest Crash in History – and How It Shattered a Nation - New York Times bestselling author Andrew Ross Sorkin takes readers inside the chaos of the crash, behind the scenes of a raging battle between Wall Street and Washington and the larger-than-life characters whose ambition and naivete in an endless boom led to disaster. The dizzying highs and brutal lows of this era eerily mirror today's world—where markets soar, political tensions mount, and the fight over financial influence plays out once again. Delivering Happiness: A Path to Profits, Passion, and Purpose - a best-selling 2010 memoir by former Zappos CEO Tony Hsieh detailing his entrepreneurial journey and outlines his core philosophy: building a phenomenal corporate culture and focusing on the happiness of employees and customers ultimately drives long-term profits and business success.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In Season 15 episode 3, Charles Suggs sits down with Greg Medland, aka “The Elixir Fixer,” to talk about the current state of hiring and the software jobs market in 2026.   Greg shares what he's seeing from both sides of the hiring process as an Elixir-focused recruiter, from shifting company expectations to the growing importance of specialization, communication skills, and real-world product thinking. We discuss how the market has changed since the 2021–2022 hiring boom, why things feel more uncertain today, and how developers are adapting to a slower, more competitive landscape.   The conversation also explores how AI is affecting hiring workflows, résumé quality, technical interviews, and even the rise of fraudulent candidates. Greg explains why human relationships and reputation still matter more than ever, especially in smaller ecosystems like Elixir where community connections carry real weight.   Along the way, we talk about what junior developers are up against, why senior engineers with domain expertise continue to stand out, and what developers can do to position themselves more effectively in today's market. Greg shares practical advice for building a sustainable career, developing a clear professional identity, and navigating a rapidly changing industry.   Topics discussed in this episode: The current state of the Elixir job market Hiring trends and market shifts since 2021–2022 How AI is changing hiring and recruiting workflows Fraudulent candidates and AI-generated résumés Domain expertise vs. generalist engineering skills Product thinking and customer-focused development What companies are looking for in 2026 Junior developer challenges in the current market Why senior specialists remain in demand Networking and relationship-building in tech Open source contributions and visibility in the Elixir community Standing out in a crowded hiring environment Résumé quality and application strategies The role of personal branding for developers Remote work trends and geographic hiring patterns Technical interview expectations and evaluation changes Startup vs. enterprise hiring differences Human connection in an increasingly automated industry Career resilience and long-term positioning Building a sustainable software engineering career   Links mentioned: Socially Responsible Recruitment https://sr2rec.com/en/ Greg's LinkedIn https://www.linkedin.com/in/elixirfixer/ Greg's email address: greg@sr2rec.com

Andrew McNamara, Director of Applied Machine Learning @ Shopify, joins the ELC podcast to share insights on building agentic platforms at scale, like Sidekick, that must keep reliability for its users at the forefront. Andrew describes the building philosophy behind Shopify and what it means to cultivate a culture of prototype-first while prioritizing hiring early-stage talent. We cover Sidekick's development journey and how user feedback impacted its product vision, why evaluation is so important for determining ground truth sets, and the benefit of user-driven use cases. Andrew also dissects how they went about making product design decisions, such as building proactive agents and identifying subagent specializations.   ABOUT ANDREW MCNAMARA Andrew McNamara is Director of Applied Machine Learning at Shopify, where he leads the team behind Shopify Sidekick, an AI co-founder that gives merchants access to the e-commerce expertise they need to run and grow their business. With 16 years of experience building AI assistants, he brings a rare combination of applied research depth and production-scale thinking to some of the hardest problems in AI: getting systems to work reliably for people who depend on them. Andrew's work pushes Shopify to measure AI quality by whether it achieves what the user set out to do, a core standard in building AI that merchants trust. Outside Shopify, he runs Setting North, a small Canadian maple syrup brand built on the same platform he helps make for everyone else.   Unblocked: The context engine your coding agents are missing. Give your coding agents the context your best engineers have. Your agents can read code, but they don't know how your team works. Rules and MCPs give access to information but not understanding. That's why you still have to tell them where to look and what to look for. Unblocked gives your agents the history, conventions, and decisions behind your code so they generate mergeable output without the back and forth. It automatically surfaces the right context for every task, so agents stay on track without the set up tax or the correction loops. getunblocked.com/elc   SHOW NOTES: How Shopify utilizes reflexive AI & Andrew's building philosophy (2:38) Developing a prototype-first company culture (5:07) Andrew's reflections on building AI-enabled projects like Sidekick at scale (7:25) Translating customer surveys into Sidekick's product vision (9:34) Key inflection points while scaling out Sidekick (11:23) Strategies for evaluation / building a ground truth set (13:26) Analyzing the good & bad within ground truth sets (15:27) Shopify's system openness model to drive user-discovered use cases (17:47) How subagents fit into the Sidekick's model (19:55) Prioritization conversations around subagent specializations (23:06) Designing an agent with high-impact prompt optimization (27:22) Considerations for building highly reliable systems (29:40) Andrew's perspective on latency (31:24) Rapid fire questions (33:49)   LINKS AND RESOURCES Cradle - a New York Times best-selling series from Will Wight following a character's growth as he goes from one of the weakest users of his world's magic to among the strongest. The series features an original magic system inspired by Chinese cultivation and martial arts novels, with a heavy emphasis on anime-style super-powered battles.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In Season 15 episode 2, Elixir Wizards Sundi Myint and Charles Suggs chat with Micah Cooper to talk about distributed systems, data replication, and what it actually looks like to build these ideas in Elixir.   Micah shares his journey from Ruby to Elixir and walks us through Visor, a library he's building based on the Viewstamps replication algorithm. Inspired by systems like TigerBeetle, Visor explores how you can replicate state across nodes using GenServers, giving you fault tolerance and recovery without relying entirely on traditional database patterns.   We talk about the difference between distributed systems and data replication, where things tend to get misunderstood, and what changes when you start thinking about state this way. The conversation also touches on event sourcing, tradeoffs in system design, and how Elixir's distributed model makes some of these concepts more approachable than you might expect.   Along the way, we talk about building for curiosity, experimenting with new ideas, and how projects like this push the ecosystem forward.   Topics discussed in this episode: Building Visor and working with the Viewstamps replication model Replicating GenServer state across nodes Distributed systems vs. data replication Lessons from TigerBeetle and financial system design Event sourcing challenges and tradeoffs Rethinking database-first architectures Snapshotting, recovery, and fault tolerance The role of Elixir's distributed model Experimentation, learning, and building for curiosity   Links mentioned: Micah's GitHub https://github.com/mrmicahcooper Micah's GitLab https://gitlab.com/mrmicahcooper The Visor repository: https://gitlab.com/mrmicahcooper/visor Visor Hex Package https://hex.pm/packages/visor Ruby on Rails https://rubyonrails.org/ Phoenix LiveView Framework https://www.phoenixframework.org/ Zig Programming Language https://ziglang.org/ TigerBeetle https://tigerbeetle.com/ TigerBeetle internal docs https://github.com/tigerbeetle/tigerbeetle/tree/main/docs/internals The BEAM https://www.erlang-solutions.com/blog/the-beam-erlangs-virtual-machine/ GenServer https://hexdocs.pm/elixir/GenServer.html Apache Kafka https://github.com/apache/kafka RabbitMQ https://www.rabbitmq.com/ Redpanda https://www.redpanda.com/ SQL https://www.ibm.com/think/topics/structured-query-language Kubernetes https://kubernetes.io/ YAML https://yaml.org/ Nomad Workload Orchestrator https://developer.hashicorp.com/nomad Flutter https://flutter.dev/ Commanded https://hexdocs.pm/commanded/Commanded.html Go Programming Language https://go.dev/ Clojure Programming Language https://clojure.org/ Nebulex https://hexdocs.pm/nebulex/Nebulex.html Mnesia https://www.erlang.org/doc/apps/mnesia/mnesia.html Cachex https://hexdocs.pm/cachex/Cachex.html libgraph https://hexdocs.pm/libgraph/Graph.html Horde https://hexdocs.pm/horde/Horde.Registry.html NocFree split keyboard https://www.nocfree.com/ Micah's LinkedIn https://www.linkedin.com/in/micah-cooper-4a737560/ 

Agreeing on an idea doesn't mean you both understood the same thing. Dave Sharrock and Peter Maddison dig into why shared context breaks down in practice, and how AI makes that problem harder to ignore.This week's takeaways:Intent is always imperfect. Define how you'll validate it, not just what it is.Ambiguity in context isn't a bug. It's necessary. Validation is how you confirm you're aligned.Drive down the cost of validation, not just the cost of building.If this landed, share it with someone navigating the same tension. And reach out at feedback@definitelymaybeagile.com - we read everything.

Inbal Shani (CPO and Head of R&D @ Twilio) deconstructs the transformation of the R&D org at Twilio! We explore the shift from a GM-led model to a unified platform strategy and “why structure must always follow strategy.” Inbal shares her framework for moving from output-focused metrics to input goals, prioritizing “time-to-value,” and the nuances of measuring AI products. We discuss using "R&D roadshows" as a strategic company transformation tool and why engineering leaders must master product positioning. We also dive into mental models for future-proofing your business, from "working backwards" to solve customer problems, to embedding systems thinking into the DNA of your engineering team, and critical questions to identify and optimize decisions around your company's moat.    ABOUT INBAL SHANI As Chief Product Officer, Inbal leads Twilio's R&D organization, encompassing product, engineering, and R&D operations. She is dedicated to driving platform-wide innovation, empowering customers, and delivering transformative, customer-focused solutions.   Unblocked: The context engine your coding agents are missing. Give your coding agents the context your best engineers have. Your agents can read code, but they don't know how your team works. Rules and MCPs give access to information but not understanding. That's why you still have to tell them where to look and what to look for. Unblocked gives your agents the history, conventions, and decisions behind your code so they generate mergeable output without the back and forth. It automatically surfaces the right context for every task, so agents stay on track without the set up tax or the correction loops. getunblocked.com/elc   SHOW NOTES: Catalysts for Twilio's R&D transformation and the shift away from organizational silos (2:49) Strategy Drives Structure: The lightbulb moment at a strategy offsite that demanded structural change to execute vision (5:14) Why structure must follow strategy and creating a "change-constant" culture (7:23) Implementing the “working backwards” methodology and the internal power of the PRFAQ (13:52) Tactical ways to filter customer signals and find real unmet problems versus feature requests (16:35) Shifting from output-focused goals to input goals and prioritizing "Time to Value" (18:35) Using weekly product reviews to align metrics with qualitative customer feedback (21:34) Measuring AI Products: Why AI products require behavior-based measurement instead of traditional binary testing (23:24) Building security by design with layered protection for AI-generated code environments (26:09) Mental models for future-proofing your business by acting as a "fortune teller" for needs (28:45) The R&D Roadshow: Enabling the entire company on new ways of working through storytelling (32:28) Why engineering leaders must master product positioning to bridge the gap to market (38:33) Relatable storytelling: Explaining Twilio's value to your parents to sharpen your pitch (41:47) Rapid Fire Questions (43:14)   LINKS AND RESOURCES How Minds Change: The Surprising Science of Belief, Opinion, and Persuasion - In this lively journey through human psychology, bestselling author and creator of the You Are Not So Smart podcast David McRaney investigates how minds change--and how to change minds.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Rajat Monga, CVP AI Frameworks @ Microsoft, joins the podcast to discuss his leadership and founder journey, from Google Brain / Tensorflow to inference.io and back to Microsoft. He dissects what it means to refound vs. start from scratch, the value of the open source community, and strategies for discovering what problem to solve when going the startup route. We also cover how to determine your users' hidden incentives and what that means for both product development & marketing, along with navigating the balance between a product's usefulness and consumers' willingness to pay for it. Additionally, Rajat shares about what he's currently up to at Microsoft and the emerging ML / AI technologies he's most excited about.   ABOUT RAJAT MONGA Rajat Monga is responsible for enabling an efficient AI stack at Microsoft from cloud to the edge. Before joining Microsoft, Rajat was founder and CEO of Inference.io, a smart analytics platform powered by AI. During his decade-long tenure at Google, he co-founded and led TensorFlow, and was a founding member of Google Brain. He's built out and led many engineering teams, and designed large scale distributed systems including web scale crawling and eBay's search engine. Rajat is a graduate of IIT Delhi.   Unblocked: The context engine your coding agents are missing. Give your coding agents the context your best engineers have. Your agents can read code, but they don't know how your team works. Rules and MCPs give access to information but not understanding. That's why you still have to tell them where to look and what to look for. Unblocked gives your agents the history, conventions, and decisions behind your code so they generate mergeable output without the back and forth. It automatically surfaces the right context for every task, so agents stay on track without the set up tax or the correction loops. getunblocked.com/elc   SHOW NOTES: Rajat's journey with Google Brain: Scaling deep learning from single PCs to thousands of machines with Jeff Dean & Andrew Ng (2:57) Moving from Google Brain to TensorFlow: Why new hardware and architectures required a total system rebuild (6:02) The "refounding" question: Choosing between starting from scratch or evolving an existing system (8:33) Why Google open-sourced TensorFlow to set industry standards and avoid supporting external copies (10:16) How open-source enabled global innovation, from Japanese cucumber sorting to African plant health (12:02) Transitioning as a leader: Why Rajat left Google during the height of TensorFlow to found a company (13:57) The discovery phase at inference.io: Navigating the pivot from IoT into solving data analytics gaps (15:31) Lessons on PMF: Moving beyond a "useful" product to one that solves a truly critical customer pain point (16:52) Why habits are harder to change than technology and the challenge of competing with established workflows (21:02) Marketing strategies: Tailoring personas for top-down prestige versus bottom-up personal efficiency (23:19) Deciding when to stop: A founder's framework for re-evaluating bets based on current knowledge (24:57) Rajat's new role at Microsoft: Overseeing Edge infrastructure and large-scale Cloud AI inference (27:46) Dissecting ML edge strategy: Using ONNX Runtime to unify AI performance across Windows, iOS, and Android (30:02) Edge AI trends: Shifting from experimental models to production models optimized for cost and privacy (31:20) The future of Edge: How on-device processing will power AI in robotics, smart glasses, and wearables (33:23) Scaling inference: Treating multi-GPU clusters like a distributed operating system for AI models (34:25) Rapid fire questions (37:45)   LINKS AND RESOURCES Epic Disruptions: 11 Innovations That Shaped Our Modern World - Innovation expert Scott Anthony masterfully weaves together the fascinating stories behind history's most transformative disruptions—from ninth-century China to twenty-first-century Silicon Valley. Through eleven pivotal innovations, including the printing press, mass-produced automobiles, the McDonald's revolutionary food system, and the iPhone, Anthony reveals the hidden patterns behind world-changing breakthroughs.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Neal Ford: software architect, author, speaker, and independent consultant (formerly 20+ years at ThoughtWorks), joins Tobias to explore what happens to software architecture when AI agents write the code. We unpack the critical distinction between behavior and capabilities: why everyone focuses on what code does, but too few think about scalability, security, and responsiveness. Neal introduces architectural fitness functions as the essential guardrail for agentic systems, and explains why non-deterministic code generation demands deterministic tests. Finally, we dig into legacy modernization, the Dreyfus scale applied to LLMs, ephemerality as the new architectural dimension, and why AI is a multiplier, not a replacement, for experienced engineers.

Enterprise customers demand 99.9% availability, regardless of how the underlying software is built. In this episode, Murali Swaminathan (CTO @ Freshworks) discusses how enterprises actually win with AI! We explore the “Architecture of Predictability” – proactive architectural safeguards to scale “responsible AI by design” across a global organization serving 75,000 customers. Murali shares his leadership playbook for implementing the technical safeguards and product trust controls that empower hundreds of engineers to build safely. We also dive into the shift from deterministic flowcharts to “workflows with a brain” and why backend systems engineers are the secret bedrock of agentic products. Plus, Murali deconstructs the dual evolution required of modern leaders: mastering strategic thinking at the business level while cultivating systems thinking at the engineering level.   ABOUT MURALI SWAMINATHAN Murali Swaminathan joined Freshworks as Chief Technology Officer in September 2024. Murali is responsible for Freshworks' technology roadmap and strategy, leading the company's global engineering and architecture teams. With over 30 years of experience in software engineering, he has held leadership roles at ServiceNow, Recommind (now OpenText), and CA Technologies (now Broadcom), where he delivered scalable, secure solutions that enabled digital transformation and business agility. Murali holds a master's degree in Software Engineering Management from Carnegie Mellon University and a bachelor's degree in electronics and instrumentation from Annamalai University in India.   SHOW NOTES: Freshworks' operating context: Engineering for 75,000 global customers (2:09) Navigating the tension between rapid AI adoption and enterprise-grade reliability (4:58) Breaking the "Positive Scenario" Trap: Using AI to automate negative test cases and corner-case detection (6:40) Why Responsible AI is a competitive advantage: Building "kill switches" and trust gates (8:31) Responsible AI by Design: Moving from reactive compliance to proactive architectural safeguards (10:48) Technical safeguards: Leveraging hyperscaler frameworks for model compliance and data anonymization (13:39) Product Trust Controls: Demonstrating reliability through role-based access and thresholds (16:25) Why engineering leaders should experiment in small teams before global rollout (20:35) Simulating Chaos: Using Business Continuity Planning (BCP) to test AI system resilience (22:13) Workflows with a brain: Transitioning from deterministic flows to agentic runtime decisions (24:16) The AI Team Profile: Why backend system engineers, not just data scientists, are the bedrock of agentic products (29:25) Cultivating a mindset shift toward agentic system orchestration (32:10) The shift to systems thinking: How engineering roles evolve from "building pieces" to managing end-to-end system flows (33:38) How to approach strategic business thinking as an engineering leader (36:43) Rapid Fire Questions: Guy Kawasaki's "Think Remarkable" and the best way to predict the future (38:23)   LINKS AND RESOURCES Think Remarkable: 9 Paths to Transform Your Life and Make a Difference - Tech titan and creator of the Remarkable People podcast Guy Kawasaki delivers a practical, tactical, and sometimes radical discussion of how to make a difference in the world and live a fulfilling life.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

How do you know if you're a good leader? In engineering, like any profession, leadership is so much more than just getting your team to do what they're told. In this episode of Navigating Major Programmes, Riccardo and Shormila shift their focus to a broader topic: people management. Reaching beyond assessments and management styles, the two long-time leaders unpack their experiences so far. They explore the difference between managing contractors and direct reports, the importance of feedback delivery, and the need for empathy that flows in both directions—up and down the chain of command.Their conversation winds through self-reflection, organizational structures, and the dearth of training for technical experts thrust into people-management roles as the only path for advancement. Along the way, they discuss how leadership evolves over time (and often through mistakes), why emotional intelligence takes deliberate work, and what makes people management uniquely demanding—especially when you're delivering hard news while still remembering there's a human on the other end.They also dig into the realities of leading within complex systems: how to motivate and retain people across generations, why “tone from the top” shapes culture more than any slogan, and how leaders can adapt their style to the individual in front of them. Therapy, organizational design, and the impact of AI on early-career technical roles all receive their due consideration in a thoughtful, candid episode that recognizes leadership is a lifelong practice—not a just title.Key takeawaysThe role of empathy in business, relationships, and company culture;Why self-reflection is essential to every leader's development;Recognizing when to adhere to and when to throw out the org chart;Navigating disconnection from direct reports in enormous corporations;The negative impact of distilling rational reasoning as decisions descend from the top.Quote“Creating corporate culture…all starts from the leader—the tone from the top.” - Shormilla ChaterjeeThe conversation doesn't stop here—connect and converse with our community via LinkedIn:Follow Navigating Major Programmes: https://www.linkedin.com/company/navigating-major-programmes/Read Riccardo's latest at www.riccardocosentino.comFollow Shormila Chatterjee: https://www.linkedin.com/in/shormilac/Follow Riccardo Cosentino: https://www.linkedin.com/in/cosentinoriccardo/

How much has changed in AI during the last two years? Aurecon’s Dave Mackenzie revisits a past conversation he had on the Engineering Reimagined podcast with Nomic CEO Andriy Mulyar. They discuss how AI adoption in complex infrastructure environments has evolved from early experimentation to practical implementation. This episode also considers how roles are changing, with engineers increasingly acting as orchestrators, and reflects on the skills and capabilities needed for future-proofing.See omnystudio.com/listener for privacy information.

Send us Fan MailIs engineering really a meritocracy?We're taught that hard work, strong performance, and clear metrics determine who advances. But what if the system isn't as objective as it seems?In this episode of ENGINEERING CH∆NGE®, I break down how “merit” is often interpreted, or even manufactured, not measured and how the systems we trust to evaluate performance can actully distort it.In this episode: Why performance without context is incomplete and often misinterpreted.How shifting standards and uneven scrutiny reshape who advances.What happens when metrics become targets and start driving behavior instead of reflecting impact.Through real-world examples - from internship decisions to NSF review panels - this episode reveals how evaluation systems can manufacture merit instead of measure it.If you've ever questioned how decisions really get made in academia, engineering, or leadership, this conversation will change how you see performance, potential, and fairness.Ask yourself: Are we rewarding true impact, or just what's easiest to measure?Grab a latte and listen.If this conversation resonates with you, follow ENGINEERING CH∆NGE® and leave a five-star review to help more engineers and leaders join the conversation.Visit the ENGINEERING CH∆NGE® podcast website to learn more and to request a free copy of my new brief, Engineering for Society.Support the showENGINEERING CHΔNGE® is a registered trademark held by Dr. Yvette E. Pearson for producing and providing podcasts.

Jon Hyman (CTO & Co-Founder @ Braze) returns to the podcast to share how he balances a mature, public-company roadmap with visionary AI innovation! We deconstruct Braze's quantitative "Product Health" framework - a scoring system used to resolve competing prioritizations and mandate technical remediation. We also discuss shifting engineering leaders to think like GMs, how to realign teams by connecting abstract “vision” to specific releases, goals & outcomes. Plus, Jon's three-tier mental model for AI products, how to identify AI features that actually drive revenue, and reimaging your product for future channels, teams, and skills.   ABOUT JON HYMAN Jon Hyman is the co-founder and chief technology officer of Braze, the customer engagement platform that delivers messaging experiences across push, email, in-app, and more. He leads the charge for building the platform's technical systems and infrastructure as well as overseeing the company's technical operations and engineering team. Prior to Braze, Jon served as lead engineer for the Core Technology group at Bridgewater Associates, the world's largest hedge fund. There, he managed a team that maintained 80+ software assets and was responsible for the security and stability of critical trading systems. Jon met cofounder Bill Magnuson during his time at Bridgewater, and together they won the 2011 TechCrunch Disrupt Hackathon. Jon is a recipient of the SmartCEO Executive Management Award in the CIO/CTO Category for New York. Jon holds a B.A. from Harvard University in Computer Science.   This episode is brought to you by xMatters! xMatters automates the entire incident lifecycle with their purpose-built AI powered workflow, giving your team the context they need to stop disruptions before they start and minimize resolution times. Head over to xmatters.com to learn more!   SHOW NOTES: Braze's operating environment & key focus on product health / roadmap (2:58) What's next for Braze: Research-driven innovation in the AI era (6:16) Ensuring customers utilize the full breadth of features (9:42) The "Swarming" strategy: Reducing engineering escalation tax through support collaboration (14:19) Shifting engineering leadership think like GMs: Moving from completion goals to business outcomes like revenue, growth rates & regional differences (17:29) How engineering leaders can increase business IQ by understanding margins and adoption (18:20) Deconstructing misalignment, the abstract nature of product vision, and connect teams to tangible business outcomes, goals, and specific releases (22:02) Management infrastructure: Quarterly product health reporting and trending metrics (23:20) Forming a mental model for company maturity, building a visionary roadmap, and more innovative engineering initiatives (25:34) Frameworks for AI Decision-Making: Identifying AI features that drive revenue vs. those that only improve stickiness (31:55) Reimagining your product based on different personas, new channels, “AI omniboxes”, and teams / skills of the future (35:44) Breaking down team silos, customer engagement as a shared responsibility, and the future of full-stack roles orchestrating outcome-based workflows & automations (41:50) Rapid fire questions (45:10)   LINKS AND RESOURCES Everything is Tuberculosis by John Green: A historical look at how the disease has shaped the world braze.com   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

We discuss what effective leadership looks like across three organizational archetypes: product-led, business-led, and design-led companies with Sebastiano Armeli (Engineering Leadership @ Meta). Drawing from his leadership journey at places like  Meta, Spotify, Snap, and PayPal, Sebastiano deconstructs the situational leadership frameworks required to thrive in different environments. Plus we discuss how AI is moving managers from implementation to architecture, why the next bottleneck is managing the overhead of high-velocity experimentation, and the future of team topology where AI enables a single leader to oversee high-scale teams of 30–50 people. Whether you are scaling a design-driven startup or navigating a complex business-led enterprise, this conversation provides a framework for aligning your leadership style with your organization's core incentives.   ABOUT SEBASTIANO ARMELI Sebastiano Armeli is an engineering leader currently at Meta. He has previously served as a Director of Engineering at Upwork and held leadership roles at companies such as Pinterest, PayPal, Snap, and Spotify. His work has spanned diverse domains including shopping, crypto, messaging, video creation, and ads. Sebastiano is passionate about building healthy engineering cultures, mentoring the next generation of leaders, and supporting teams through periods of growth and change. He mentors engineering managers and senior engineers, enjoys speaking at conferences, and shares his perspectives on leadership in his Substack, The Healthy Engineering Leader. He also serves on the board of a community-owned grocery store. In all his work, Sebastiano takes a pragmatic, people-first approach to leadership, focusing on clarity, continuous improvement, and long-term impact.   This episode is brought to you by xMatters! xMatters automates the entire incident lifecycle with their purpose-built AI powered workflow, giving your team the context they need to stop disruptions before they start and minimize resolution times. Head over to xmatters.com to learn more!   SHOW NOTES: Deconstructing company archetypes: A framework for product-led organizations (2:03) Strategic leadership practices for succeeding in product-first cultures (7:33) Leveraging data and business metrics to influence product strategy (9:35) Case Study: The story and leadership lessons behind building Spotify's Ad Studio (11:12) Rapid prototyping: Applying a hackathon mindset to product development (13:16) How AI is reshaping product-led orgs: Clearing the feature backlog, scaling experimentation and velocity (16:01) Balancing iteration velocity and product quality with AI (18:12) Sebastiano's observations on effective leadership in business led orgs (19:49) Design-led dynamics: Anticipating the impact of AI on creative-first orgs (23:24) Maintaining engineering excellence within design-driven constraints (25:40) Cultivating high-alignment, valuable design partnerships (27:01) The role of metrics and data in design-focused decision making (28:33) Emerging AI capabilities enhancing leadership leverage (31:16) Scaling management: The potential for 30-50 person teams via AI assistance (33:58) The ethical imperative: Adopting AI responsibility within engineering teams (35:53) Rapid fire questions (37:12)   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Explore how climate leadership measures should be a routine part of decision-making with Emeritus Professor Mark Howden and Aurecon’s Dr Ben McGarry. Together they discuss the role engineers play in shaping a low-carbon and resilient future; and why starting with values, incorporating systems thinking, and highlighting long-term benefits all matter when engaging stakeholders and delivering meaningful change. This episode of Engineering Reimagined was recorded live at the 2025 CAETS conference. See omnystudio.com/listener for privacy information.

Live from the Vercel recording studio, Lindsey Simon (VP Engineering @ Vercel) joins us to deconstruct the evolution of management craft and career growth strategies! We dissect the practice of live all-hands demos as a tool for context, accountability and inspiration. Plus, Lindsey's "vote with your wallet" framework for career strategy, how Lindsey's open source project inspired him to apply to Vercel, and why the most effective VPs are building hobby projects to maintain AI competency and empathy for non-technical users.   ABOUT LINDSEY SIMON Lindsey Simon is VP of Engineering at Vercel. Making the Web better has been his lifelong career ambition. Prior to Vercel, Lindsey spent seven years at Google, where he helped launch App Engine as an original core team member, and worked as a tech lead on the Google Translate and Web Performance teams. Lindsey has lived in San Francisco for the past 15 years, and his creative hobbies (beyond coding) include writing music and hunting for wild mushrooms.   This episode is brought to you by xMatters! xMatters automates the entire incident lifecycle with their purpose-built AI powered workflow, giving your team the context they need to stop disruptions before they start and minimize resolution times. Head over to xmatters.com to learn more!   SHOW NOTES: The evolution of Vercel's all hands to demo days: using live show-and-tell to maintain context and inspire the team (2:4p) Accountability for what's real: Why live visual demos help engineering teams with real-time workflow adjustments (4:36) Strategies for creating a successful live visual demo without over-rehearsing (6:20) Lindsey's career inflection point: Navigating the transition from a large ecosystem at Salesforce to a mission-driven startup (10:08) Career advice: Vote with your wallet and go somewhere with pre-existing PMF that feeds your ambition (12:33) The "Janitor" Mindset: Why prioritizing the company's mission over a specific job title can lead to unique opportunities (14:36) How Lindsey's open source hobby project led to a code-first interaction with @ Vercel (19:17) Vercel's "Dig Deep" value: Breaking down the company culture and the importance of technical support for developers (21:26) Standing out in the interview process: Why managers must bring a strong "Point of View" on what a company should do differently (23:51). The Swiss Army Knife Manager: Why today's leaders must also be salespeople, PMs, and customer support engineers (24:46). The death of pure "people management": Re-centering on the IC craft and why managers must maintain AI competency (26:12). Adopting better IC skills: Building hobby projects for non-technical users to maintain empathy for the user experience (28:33) Management principles that remain true today (32:54) Combatting imposter syndrome: Building trust by being vulnerable and learning alongside your team (36:45). Interviewing trends: Assessing how candidates operate with and without AI tools (38:05). The return of "In Real Life" work: Why the Bay Area culture is refocusing on "sweating the details" in person (39:15) Rapid fire questions (41:33)   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Career progression is rarely a straight line. More often, it only makes sense in hindsight. Chris Chiu (VP of Engineering, Agentforce @ Salesforce) joins us to deconstruct how to navigate these non-linear career paths! We talk about identifying the mismatch in your current role, building a personal "career thesis," how to engineer a productive exploration phase and leverage your relationships / VC networks to understand the market. Plus, how to apply the "Running Framework" to ensure success in your next role and why technical depth is no longer optional for modern engineering leaders.   ABOUT CHRIS CHIU Chris Chiu is a VP of Engineering at Salesforce, where he helps build Agentforce, a platform for building enterprise AI agents. Prior to Salesforce, Chris was Head of Engineering at Moonhub, building AI recruiting agents. He has experience building and scaling product engineering teams that consistently deliver great products through rapid growth and change. Earlier in his career, he led engineering teams across companies ranging from early-stage startups to late-stage growth companies, including Figma, Flexport, and OpenGov.   This episode is brought to you by xMatters! xMatters automates the entire incident lifecycle with their purpose-built AI powered workflow, giving your team the context they need to stop disruptions before they start and minimize resolution times. Head over to xmatters.com to learn more!   SHOW NOTES: How Chris navigated the transition from Figma to Moonhub (3:47) Energy alignment: identifying the mismatch between your role and your drives (6:27) Sidesteps aren't inefficiencies: Why it's okay to not have a specific and/or linear career plan (8:26) Building a career “thesis” by balancing passions with industry shifts (11:18) The exploration phase: Strategies for a productive four-month “sabbatical” (14:07) Leveraging your network and venture capital relationships to understand the market (16:45) The utility of “status”: When the “logo” matters & when it's overrated (19:18) The "Running" Framework: Why you shouldn't increase career "speed" and "distance" simultaneously (21:33) How Chris applied these ideas to his move from Figma to Moonhub (24:33) Avoiding "career injury": Why stretching too thin hinders your flow state (27:07) Developing technical depth and leadership in the AI space (29:15) Learning through imitation: Finding and emulating leaders five years ahead of you (31:20) Chris's observations on the evolution of technical leadership (34:14) The shift from “peacetime” to “wartime” (37:58) The "Leaky Abstraction" litmus test: Why leaders must stay in the technical details (39:40) Now: Chris' transition to Agentforce and the future of AI at Salesforce (41:38) Rapid fire questions: Growth mindsets and holding identity loosely (43:59)   LINKS AND RESOURCES: 99% Invisible: The design and architecture podcast Sulman has followed for over a decade. The Invisible Cow Tunnels of Chicago: A specific episode of 99% Invisible mentioned by Patrick.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send a textWhat happens to engineering systems when fear shapes the conditions under which people work, or are allowed to work?In this episode of ENGINEERING CH∆NGE®, I examine how fear-driven decisions inside organizational systems can reshape their capacity to produce research, education, and societal outcomes, and not for the better.Drawing from lived experience and patterns emerging across institutions, this conversation explores how organizational systems lose capacity, expertise, and knowledge when silence replaces truth and optics replace accuracy. This episode invites listeners to reflect on the often invisible organizational inputs that shape engineering outcomes and what leaders must be willing to see if our systems are to serve society effectively.In this episode:How fear reshapes organizational decision-makingWhat happens when systems lose people, knowledge, and capacityWhy engineering outcomes depend on organizational conditionsA “System Check” reflection for leaders responsible for engineering and research outcomesIf this conversation resonates with you, follow ENGINEERING CH∆NGE® and leave a five-star review to help more engineers and leaders join the conversation.Visit the ENGINEERING CH∆NGE® podcast website to learn more and to request a free copy of my new brief, Engineering for Society.Support the showENGINEERING CHΔNGE® is a registered trademark held by Dr. Yvette E. Pearson for producing and providing podcasts.

In this episode, recorded live at the OpenAI studio, Sulman Choudhry (Head of ChatGPT @ OpenAI) pulls back the curtain on how they structure engineering teams! We talk about shifting from silos to fluid mission-driven teams, vertical vs. horizontal teams, maximizing cross-functional collaboration between research, engineering, product and design. Plus we cover “directly responsible individuals” for high accountability, managers as systems designers, scaling decision-making to prevent leadership from becoming bottlenecks, frameworks for mentoring junior engineers, why “problem framing” is the most critical skill, and how managers can stay close to problems and maintain technical intuition.   ABOUT SULMAN CHOUDHRY Sulman leads ChatGPT Engineering at OpenAI, driving the development and scaling of one of the world's most impactful AI products. He pushes the boundaries of innovation by turning cutting‑edge research into practical, accessible tools that transform how people interact with technology. Previously at Meta, Sulman founded and scaled Instagram Reels, IGTV, and Instagram Labs, and helped lead the early development of Instagram Stories. He also brought MetaAI to Instagram and Messenger, integrating generative AI into experiences used by billions. Earlier in his career, Sulman was on the founding team that built and launched UberEATS from the ground up, helping turn it into a global food delivery platform. With a track record of marrying technical vision, product strategy, and large‑scale execution, Sulman focuses on building products that meaningfully change how people live, work, and connect.   This episode is brought to you by xMatters! xMatters automates the entire incident lifecycle with their purpose-built AI powered workflow, giving your team the context they need to stop disruptions before they start and minimize resolution times. Head over to xmatters.com to learn more!   SHOW NOTES: The Shift to AI-Native Engineering: How AI is collapsing the "Inner Loop" and reshaping engineering team composition (2:48) Mission-Driven Teams: Moving from traditional functional silos to integrated, problem-centric units (4:45) Vertical vs. Horizontal Team Architecture: How OpenAI structures specialized horizontal teams (ex. Infrastructure, RTC/Voice) with product verticals (7:04) Fluid org charts & blurring functional roles: AI-Native teams require proactive mission alignment and coordination over rigid structure (8:48) The Lifecycle of Problem-Oriented Teams: What happens when a "strike team" solves the problem (10:02) Maximizing cross functional collaboration between engineering, research, product and design (11:52) The DRI Framework: Implementing the "Directly Responsible Individual" model for high-velocity accountability (13:32) Thriving in the "Chaos Factory": Addressing bottlenecks in highly dynamic, high-volume environments (16:02) Prioritization & "Letting 1,000 Flowers Bloom": How OpenAI decides which AI bets to double down on (19:13) Scaling Decision-Making: Preventing leadership from becoming the bottleneck as volume increases (21:19) Knowing when to call it quits on a bet and reallocate talent for maximum impact (23:29) The Manager as "Systems Designer": Shifting the EM role from people logistics to technical orchestration (24:49) The Barbell Talent Strategy: Optimizing for innovation by pairing "super seniors" with "super juniors" (28:10) Mentorship in the AI Age: How to coaching junior engineers when the "cost of code" is approaching zero (30:19) Technical Intuition for Leaders: Sulman's frameworks for staying "close to the metal" as a manager (33:17) Cultivating Judgment: Why "Problem Framing" is the most critical skill for the modern engineer (37:01) Rapid fire questions (38:59)   LINKS AND RESOURCES: 99% Invisible](https://99percentinvisible.org/): The design and architecture podcast Sulman has followed for over a decade. The Invisible Cow Tunnels of Chicago](https://99percentinvisible.org/episode/cow-tunnels/): A specific episode of 99% Invisible mentioned by Patrick.   This episode wouldn't have been possible without the help of our incredible production team: Patrick Gallagher - Producer & Co-Host Jerry Li - Co-Host Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/ Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/ Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What does it take to build AI-powered products at speed - and lead the teams doing it? This episode has the answers.We sit down with Dominik Plsek, Senior Engineering Manager at Productboard, for an honest and energizing conversation about engineering leadership, the rise of AI-first product development, and what it really means to build something you believe in.Dominik has been with Productboard for over six years, joining fresh out of his master's degree after an instant connection with the team. Since then, he's grown from engineer to leader, and today he oversees multiple teams driving some of the company's most strategic work, including the newly launched Spark, Productboard's AI-first product management experience.In this episode, you'll hear:How Dominik leads with empathy and empowers teams to take real ownershipA behind-the-scenes look at building and launching SparkWhy he believes first-principles thinking will define the next generation of great engineersHow Productboard is approaching AI adoption across its entire engineering organizationWhat kind of engineers and managers Dominik is looking to hire right nowWhether you're an engineer curious about growth and AI, a leader looking for a fresh perspective on team management, or someone exploring what it's like to work at Productboard, this is an episode worth your time.

In this episode of The Engineering Room, Dave Farley welcomes Dan Abel, a veteran technical leader with over 30 years of experience, to explore the nuances of engineering leadership and the evolution of high-performing teams.This episode is a masterclass in dismantling silos, reducing cognitive load through platform engineering, and aligning technical excellence with core business values.---------------Dan Abel LinkedIn: https://www.linkedin.com/in/daniel-abel/Equal Experts is a product software development consultancy with a network of over 1,000 experienced technology consultants globally. They increase the pace of innovation by using modern software engineering practices that embrace Continuous Delivery, Security, and Operability from the outset ➡️ https://bit.ly/3ASy8n0Only Patreon Supporters get to see the FULL VIDEO Episodes of The Engineering Room, sign up here: https://www.patreon.com/c/continuousdelivery

Join us this week for The Tech Leaders' Podcast, where Gareth sits down with Rob Morris, Co-CEO UK and Ireland at Siemens Mobility. Rob talks about his journey to the Railways via mining, power stations and London 2012, how Siemens are managing a £340M investment, and the challenges of maintaining and upgrading the oldest rail network in the world. On this episode Rob and Gareth discuss digitising the railways, how AI will be employed on trains, and how in another life Rob could have been an architect. Timestamps: Introduction and Good Leadership (2:11) From Delivery to Senior Management (7:58) Siemens and the Railways (12:00) Digitising the Rail Network, and Building the Elizabeth Line (18:30) Technology on the Railways (32:15) Advice for 21-year-old Rob (41:20) https://www.bedigitaluk.com/

Kiren Sekar (CPO @ Samsara) joins us to deconstruct the "Innovation Engine" behind Samsara, and how this system drives real-world impact and ROI across their products. We explore Samsara's decade-long compound product strategy and the mechanics of accelerating feedback loops in an era where the primary bottlenecks shift from code generation to customer feedback and absorption of change. Kiren details how their data flywheel expands the aperture of what is possible to build and we dive into the system of customer-driven innovation: advisory boards, “spark sessions” to test hypotheses and gain unfiltered feedback. Plus we talk about the power of embedding engineers in frontline environments (from truckyards to construction sites) to cultivate “taste,” customer empathy and trigger non-linear ideas. ABOUT KIREN SEKARKiren Sekar is the Chief Product Officer at Samsara (NYSE: IOT), where he has helped lead the company from a hardware-hacking startup in a basement to a global leader in Connected Operations with over $1.5B in ARR. An early leader at Meraki (acquired by Cisco for $1.2B) and an Apple veteran with multiple patents, Kiren specializes in the rare intersection of hardware, massive-scale data, and AI. He is the architect of a platform that now processes trillions of data points for the industries that keep the world running—trucking, construction, and logistics. This episode is brought to you by Retool!What happens when your team can't keep up with internal tool requests? Teams start building their own, Shadow IT spreads across the org, and six months later you're untangling the mess…Retool gives teams a better way: governed, secure, and no cleanup required.Retool is the leading enterprise AppGen platform, powering how the world's most innovative companies build the tools that run their business. Over 10,000 organizations including Amazon, Stripe, Adobe, Brex, and Orangetheory Fitness use the platform to safely harness AI and their enterprise data to create governed, production-ready apps.Learn more at Retool.com/elc SHOW NOTES:Real-world ROI The Intersection of Bits and Atoms: How Samsara supported customers through a once-in-a-century snowstorm using real-time AI insights (3:59)The Practicality Filter: Why low-margin, high-utility businesses are the best "BS detectors" for product builders (9:25)Deconstructing the compound product strategy: 10 years of feedback loops, scaling empathy, and technical capabilities (10:53)Accelerating your innovation flywheel, customer and product feedback loops (14:39)The New Bottleneck: Why writing code is no longer the constraint, and how to optimize for customer absorption of change (19:58)The Data Flywheel: Leveraging trillions of proprietary data points to solve new problems and expand your innovation engine into new capabilities (23:36)Embedding engineers in customer problems: Why there is no substitute for engineers seeing the frontline environment firsthand (29:56)How customer empathy and "taste" amplify the benefits of AI coding agents (33:26)Building a system of customer-driven innovation: Utilizing Advisory Boards and "Spark Sessions" to turn 10,000+ customers into co-creators (37:40)Rapid fire questions (47:50)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Founders often delay leadership coaching until a major crisis hits, leading to significant costs in productivity, team churn, and poor decisions. In this episode, James Birchler (Technical Advisor & Executive Leadership Coach) argues that early coaching is a game-changer for a startup's success. We explore the hidden costs of waiting and the benefits of intentionally installing leadership and communication systems before you scale. James shares specific self-awareness mechanisms, like advisory groups and feedback loops, to help founders design their day and create accountability. You'll also learn practical strategies like the "5-Minute Alignment Loop" for spotting communication breakdowns & for reinforcing clarity. Plus insights on how to "install your leadership OS" so it can scale with your company. ABOUT JAMES BIRCHLERJames Birchler is an executive leadership coach and technical advisor who specializes in helping engineering leaders and founders develop greater self-awareness and build high-performing teams. He combines deep technical expertise with practical leadership development, making him particularly valuable for technical leaders scaling their organizations.As both a founder and engineering leader, James has more than 20 years of experience leading teams at companies ranging from early-stage startups to Amazon, where his current role is Technical Advisor to the VP of Amazon Delivery Routing and Planning. Most recently, he founded NICER, a premium natural personal care company, and Actuate Partners, his executive coaching and technical advisory practice. He also held VP of Engineering roles at companies including Caffeine (backed by Greylock and Andreessen Horowitz), SmugMug (where his team acquired Flickr), and IMVU.At IMVU, James implemented the Lean Startup methodologies alongside Eric Ries, author of The Lean Startup and creator of the methodology, literally the first company to apply these principles. His team helped pioneer the DevOps movement by building infrastructure to ship code to production 50 times per day and coining the term "continuous deployment." This experience in systematic experimentation and continuous improvement now informs his coaching approach through frameworks like CAMS (Coaching, Advising, Mentoring, Supporting) and the Think-Do-Learn Loop.James completed his executive coaching certification at UC Berkeley Haas School of Business Executive Coaching Institute. His coaching practice focuses on self-awareness, integrity, accountability, and fostering growth mindsets that support continuous learning and high performance. He writes the Continuous Growth newsletter and offers both individual executive coaching and peer learning circles for technical leaders.Through his advisory work with growth-stage startups in the US and Europe, James helps leaders navigate common scaling challenges including hiring and interviewing, implementing development methodologies, establishing operational cadences, and developing other leaders. His approach treats leadership development like product development—with systematic feedback loops, measurable outcomes, and continuous improvement.You can find James at jamesbirchler.com, LinkedIn, and Substack. This episode is brought to you by Retool!What happens when your team can't keep up with internal tool requests? Teams start building their own, Shadow IT spreads across the org, and six months later you're untangling the mess…Retool gives teams a better way: governed, secure, and no cleanup required.Retool is the leading enterprise AppGen platform, powering how the world's most innovative companies build the tools that run their business. Over 10,000 organizations including Amazon, Stripe, Adobe, Brex, and Orangetheory Fitness use the platform to safely harness AI and their enterprise data to create governed, production-ready apps.Learn more at Retool.com/elc SHOW NOTES:Why founders should seek coaching earlier rather than waiting for a crisis to occur (2:45)The high stakes of ignoring this critical advice & how this leads to communication & scaling problems (4:50)The importance of effective communication channels & leadership mechanisms before pressure increases (6:12)How investing a small amount in coaching early on can prevent hundreds of thousands of dollars in future costs (8:07)Frameworks for cultivating self-awareness / leadership blind spots (11:06)James's practice of "designing your day" around a desired identity, not just a list of tasks (12:30)Why designing your day is about intentionality (15:13)How this practice leads to better relationships & opportunities to reflect (17:44)Reflective listening & its impact on customer relationships (19:32)Strategies for improving self-awareness / uncovering blind spots (22:05)An example of how awareness can lead to better results  (26:03)Day-to-day rituals for improving self-awareness (28:14)Signals that your communication methods are effective & getting through (30:37)Reflect on & define the desired outcome you want to generate (33:26)The five-minute alignment loop for creating clarity & confirming ownership as a leader (35:21)Why creating clarity & finding alignment is key as a founder (37:02)How the same communication & leadership patterns recur as your org scales, from small startup to large enterprise (39:46)The increasing importance of human skills like emotional intelligence and reflective listening in an age of AI (42:03)Rapid fire questions (44:38)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us a textBob Hankins brings over 20 years of dedicated experience in the medical-device industry, spanning engineering leadership, product development, process improvement and strategic technical oversight. As Director of Engineering at TE Connectivity, he leads a global team of engineers and scientists focused on designing, developing and delivering innovative customer-centric medical device solutions—particularly complex machined, extruded and laser-cut components. In this role he ensures design for manufacturing and quality within ISO 13485-compliant systems, marrying deep technical understanding with regulatory-driven manufacturing discipline.Before his current role Bob led Research & Product Development Engineering at Nordson Medical and has held key leadership positions at several medical-device companies, including overseeing product development platforms, multi-site engineering operations, manufacturing automation and system launches. Throughout his career he has honed core competencies in manufacturing process improvement, continuous improvement (including Six Sigma/Lean methodologies), design for manufacturing/assembly, regulatory compliance (ISO 13485, ISO 14971, FDA), and product R&D for the health-care market.Bob's academic background includes a Bachelor of Science in Mechanical Engineering from the University of California, Irvine, and an Executive MBA from the Drucker School at Claremont Graduate University. This combination of technical and business education supports his ability to lead engineering organizations in bridging innovation with operational execution, customer development and quality.In this episode we'll dive into how Bob thinks about leading engineering teams in the regulated medical-device space, how he drives design and process improvements globally, how he balances innovation with manufacturing rigor, and what advice he has for engineers growing into leadership roles in healthcare technology. We'll also explore his views on what the next wave of medical-device manufacturing and design looks like—and how engineering leaders can foster a culture of excellence, empowerment and impact. LINKS:Guest LinkedIn: https://www.linkedin.com/in/rthankins/Guest website: https://www.te.com/en/home.html Aaron Moncur, hostThe Wave is  a place for engineers to actively learn, share ideas, and engage with people doing similar work. Learn more at thewave.engineer Subscribe to the show to get notified so you don't miss new episodes every Friday.The Being An Engineer podcast is brought to you by Pipeline Design & Engineering. Pipeline partners with medical & other device engineering teams who need turnkey equipment such as cycle test machines, custom test fixtures, automation equipment, assembly jigs, inspection stations and more. You can find us on the web at www.teampipeline.us Watch the show on YouTube: www.youtube.com/@TeamPipelineus

Developer productivity is often framed as a tooling initiative or a morale issue. At scale, it's a more complex socio-technical systems challenge that spans engineering foundations, leadership alignment, organizational structure, and culture.In this episode, Laura Tacho sits down with Uma Namasivayam, Senior Director, Engineering Productivity at Dropbox, to discuss how the company approaches developer experience across an organization of nearly 1,000 engineers. Uma explains why productivity must be treated as a business problem, how executive alignment enables sustained progress, and what it means to run developer experience like a product.The conversation also explores the intersection of AI and developer experience. Uma shares how Dropbox prepared its engineering systems to support AI adoption, why daily AI use depends more on habits than access, and how the company evaluates build-versus-buy decisions as AI tools struggle to scale in large environments.The episode concludes with a candid discussion of the open questions facing engineering leaders today: how to understand where AI-driven capacity actually goes, and how to connect improvements in developer experience to meaningful business outcomes in 2026.Where to find Uma Namasivayam:• LinkedIn: https://www.linkedin.com/in/unamasivayamWhere to find Laura Tacho: • LinkedIn: https://www.linkedin.com/in/lauratacho/• X: https://x.com/rhein_wein• Website: https://lauratacho.com/• Laura's course (Measuring Engineering Performance and AI Impact) https://lauratacho.com/developer-productivity-metrics-courseIn this episode, we cover:(00:00) Intro(00:45) Dropbox's engineering org(01:59) Why developer productivity is a business problem(04:08) The role of executive sponsorship in developer productivity(06:02) How DX's Core Four framework created a shared language(08:13) Treating developer experience as a product(11:30) How Dropbox prioritizes developer experience work(14:20) The challenge of tying developer experience to business outcomes(16:38) How AI and developer experience intersect at Dropbox(18:35) The prerequisites for AI adoption to accelerate work(20:26) How Dropbox encourages daily AI use(23:12) AI use beyond code completion(25:00) Managing AI tool demand at scale(27:56) Early results from Dropbox's AI efforts(30:05) Progress on developer experience at Dropbox(32:55) Advice for organizations investing in developer experience(34:25) Capacity tradeoffs for developer experience(35:59) The unanswered questions around AI and capacity in 2026Referenced:• DX Core 4 Productivity Framework• Dropbox.com

In our latest ELC episode, we are addressing some of the biggest challenges facing engineers today: identifying your scaling thesis, putting that thesis into practice, and addressing implementation challenges. Jaikumar Ganesh, Head of Engineering @ Anyscale, shares insights from his experience working at top tech companies like Android and Uber, and how to apply those lessons within your own orgs. We also cover strategies for identifying what to build, using data effectively when it comes to understanding AI agents, and keeping your intent (and customer success) top of mind. Additionally, Jaikumar discusses his experience as a GM and why all orgs should adopt cross-functional skillsets as part of their company culture. ABOUT JAIKUMAR GANESHJaikumar Ganesh is an accomplished technology leader and the Head of Engineering at Anyscale. With a deep background in engineering and customer-facing roles, Jaikumar has a proven track record of building and scaling engineering organizations. He is passionate about pushing the boundaries of product and engineering innovation while ensuring customer needs are met, and is committed to building empowering organizations rooted in trust, respect, and growth. Jaikumar is excited about working with companies to harness the power of AI and distributed computing to achieve their goals. He previously co-started and co-led Uber's AI group—the central ML group at Uber—and was also on the early team at Android @ Google. This episode is brought to you by Retool!What happens when your team can't keep up with internal tool requests? Teams start building their own, Shadow IT spreads across the org, and six months later you're untangling the mess…Retool gives teams a better way: governed, secure, and no cleanup required.Retool is the leading enterprise AppGen platform, powering how the world's most innovative companies build the tools that run their business. Over 10,000 organizations including Amazon, Stripe, Adobe, Brex, and Orangetheory Fitness use the platform to safely harness AI and their enterprise data to create governed, production-ready apps.Learn more at Retool.com/elc SHOW NOTES:Reflecting on scaling patterns across the 2000s, 2010s, and the AI era (03:27)Why "copy-pasting" scaling strategies from other companies leads to failure (5:56)How to define a scaling thesis by mapping revenue projections to infrastructure strategy (7:52)Infrastructure shifts: From Android's OS abstractions to Uber's on-prem data centers (9:56)The "Build vs. Buy" dilemma in the age of AI agents and third-party solutions (12:09)Why "Knowing What to Build" is the new long pole in engineering productivity (20:17)Developing "Product Thinking" within engineering and infrastructure teams (23:10)The emergence of Context Graphs and "Source of Truth" platforms for AI agents (24:46)How to avoid data & context graphs becoming bottlenecks (27:05)Lessons from GM leadership: Bridging the gap between engineering, product, and sales (29:06)The "6-20" Initiative: Uniting cross-functional teams around specific customer wins (32:45)Training engineers to empathize with customer pain and translate technical wins into the language of sales (33:48)Utilizing cross-departmental daily standups and leaderboards to drive aggressive "block and tackle" execution (36:18)Tracing execution failures back to early decision-making and judgment gaps (38:42)Rapid fire questions (45:28) This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Lee Zen, CTO of Yahoo, joins Tobias to unpack what it takes to modernize one of the internet's most iconic consumer portfolios—Mail, Finance, Sports, News, and Search—while operating with real legacy constraints at massive scale. We talk about Yahoo's evolution from its public days to private equity ownership, how modernization actually happens (cloud, platform bets, experimentation), and why shipping velocity becomes the most honest forcing function when you're rebuilding the engine mid-flight. Finally, we go deep on AI: where it meaningfully improves consumer experiences (mail catch-up, news takeaways, fantasy insights), how teams should avoid “AI labels” without user value, and what it means when AI becomes a tool—and increasingly a coworker.

How do you transform a collection of individual tools into a cohesive, AI-powered symphony? Vineeta Puranik (CPTO @ SmartBear) dissects the strategy behind evolving a product vision from point solutions to a unified multi-product ecosystem. We explore the critical architectural distinction between "AI bolt-on" and "AI native" strategies, frameworks for seamless M&A integration, and how to design for varying levels of customer AI readiness. Vineeta also discusses the shift to test “does it match intent”, using “jobs to be done” to drive solving entire workflows not just tool capabilities, and designing user experiences for both human personas and AI agents. ABOUT VINEETA PURANIKVineeta Puranik serves as Chief Product and Technology Officer (CPTO) at SmartBear, where she leads the company's global technology and product strategy to empower developers and enterprises worldwide. A seasoned technology executive with over two decades of experience, she combines strategic vision with hands-on leadership to drive innovation, growth, and operational excellence.At SmartBear, Vineeta oversees development, cloud engineers, AI, and architecture, and has been instrumental in scaling centers of excellence in India and Poland, launching the Developer Academy, and advancing the company's hub-based product strategy – Swagger suite for API capabilities, Test Hub, and Insight Hub. Recognized for her collaborative, people first leadership and commitment to inclusion, she was named a 2024 Women Worth Watching in STEM by Profiles in Diversity Journal. This episode is brought to you by Retool!What happens when your team can't keep up with internal tool requests? Teams start building their own, Shadow IT spreads across the org, and six months later you're untangling the mess…Retool gives teams a better way: governed, secure, and no cleanup required.Retool is the leading enterprise AppGen platform, powering how the world's most innovative companies build the tools that run their business. Over 10,000 organizations including Amazon, Stripe, Adobe, Brex, and Orangetheory Fitness use the platform to safely harness AI and their enterprise data to create governed, production-ready apps.Learn more at Retool.com/elc SHOW NOTES:SmartBear's evolution from individual tools to a connected ecosystem (3:34)The cultural shift toward vendor consolidation and avoiding context switching (5:39)Why "Jobs-to-be-Done" must drive the workflow, not just the tool capabilities (9:35)The shift in testing: Moving from "does it crash?" to "does it match intent?" in an AI world (14:26)The architectural difference between "AI Bolt-On" and "AI Native" products (20:44)The levels of autonomy: A framework for moving from manual control to autonomous testing (24:10)Designing for different customer personas: Addressing security, policy, and AI readiness (30:01)Rapid Fire Questions (32:50) LINKS AND RESOURCES Books MentionedOwn the Room: Discover Your Signature Voice to Master Your Leadership Presence by Amy Jen Su and Muriel Maignan Wilkins.The Leader You Want to Be: Five Essential Principles for Bringing Out Your Best Self--Every Day by Amy Jen Su.SmartBear Tools & ProductsSmartBear[**Reflect**](https://reflect.run/?utm_medium=referral&utm_source=smartbear.com&utm_campaign=prodnav&_gl=1*4gpwr4*_gcl_au*MTAzOTk0MjM2LjE3Njk0NjU4NTA.) – Mentioned as their "AI Native" product for autonomous testing.Zephyr Scale – Mentioned regarding the Atlassian ecosystem integration.[**QMetry**](https://www.qmetry.com/?_gl=1*1d5sv56*_gcl_au*MTAzOTk0MjM2LjE3Njk0NjU4NTA.) – Recently acquired test management product.[**Swagger**](https://swagger.io/product/?_gl=1*gtu348*_gcl_au*MTAzOTk0MjM2LjE3Njk0NjU4NTA.) – Mentioned as the suite for API design and compliance. This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Tyson Singer (Head of Tech & Platforms @ Spotify) joins us to unpack how Spotify is transforming its product development lifecycle across creation, experimentation and maintenance to shift from "localized speed" to "systematic speed." We explore why the industry's current obsession with the "Build It" phase of development is shortsighted, and how Spotify is aggressively deploying AI in the "Think It" (prototyping/strategy) and "Maintain It" (fleet management) phases. Tyson also details the internal tools driving this shift, including AiKA and Honk, and shares why the future of engineering relies on moving from I-shaped specialists to T-shaped generalists. ABOUT TYSON SINGERTyson Singer is the SVP of Technology & Platforms at Spotify, where he leads technology infrastructure, developer experience, cybersecurity, and finance IT. Tyson is the executive behind Spotify's internal developer portal, Backstage, and Spotify's experimentation system, Confidence, which are now both commercially available. He has a background as an engineer, architect, and product lead, and he holds a Master's in Computer Science from Stanford University. Tyson is also an avid outdoor adventurer. This episode is brought to you by Retool!What happens when your team can't keep up with internal tool requests? Teams start building their own, Shadow IT spreads across the org, and six months later you're untangling the mess…Retool gives teams a better way: governed, secure, and no cleanup required.Retool is the leading enterprise AppGen platform, powering how the world's most innovative companies build the tools that run their business. Over 10,000 organizations including Amazon, Stripe, Adobe, Brex, and Orangetheory Fitness use the platform to safely harness AI and their enterprise data to create governed, production-ready apps.Learn more at Retool.com/elc SHOW NOTES:Tyson's 9-year journey @ Spotify: From the "crucible" of hyper-growth to leading Tech & Platforms (3:46)The pivot from "localized speed" to "systematic speed" (7:27)Core principles of Spotify's Platform org: Partnering with customers & "Taking the pain away" (10:37)The "Think it, Build it, Ship it, Tweak it" lifecycle framework & why the industry obsession with "Build It" (coding agents) is missing the bigger picture (14:57)How Spotify is investing in the "Think It" phase: AI prototyping with deep business context (16:49)AiKA (AI Knowledge Assistant): Context engineering for humans and bots (18:47)"Honk": Spotify's internal framework for large-scale automated code changes (22:17)Addressing the decline of code quality and the bottleneck of human PR reviews (25:50)Probabilistic vs. Deterministic code reviews: A new approach to quality checks (29:43)Identifying bottlenecks to company value outside of R&D (Legal, Licensing, etc.) (32:12)Why systems change is fundamentally about people and identity shifts (35:57)Rapid fire questions (38:49) This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It started with a simple idea from James Tyack: “What if we hosted a hackathon at ELC Annual?” The result was a unique experiment where 14 senior engineering leaders stepped away from strategy to build and ship functioning apps in one weekend, unlocking new insights on AI-native workflows, "vibe coding," and the future of engineering. In this episode, we deconstruct the entire hackathon operational playbook, sharing lessons on everything from “best failure awards” and async collaboration structures to structuring ideation periods for maximum business alignment. Beyond the logistics, we explore how getting hands-on helped these leaders overcome imposter syndrome and why "rolling up your sleeves" is now a prerequisite for leading effective engineering teams. Plus, James shares how he plans to evolve the hackathon format at ELC and beyond. If you've been curious about leveraging hackathons to drive innovation, expose your team to new tools, or evolve how your org builds, this episode provides the blueprint for successful implementation. ABOUT JAMES TYACKJames is an engineering manager with a passion for people, technology, and learning. He's built and led distributed, diverse teams of engineers across locations and timezones for 10 years. James believes strongly in the value of diversity and championing a sense of belonging for everyone, from day 1. He's well versed in growth strategy, chaos engineering, major incident response, and blameless practice, and culture grounded by trust and psychological safety. He leads the Growth Acquisition team at Coursera where he's proud to be part of an organization that's transforming lives through learning. Previously, James enjoyed building and leading the Growth and Integrations engineering teams at PagerDuty. This episode is brought to you by Span!Span is the AI-native developer intelligence platform bringing clarity to engineering organizations with a holistic, human-centered approach to developer productivity.If you want a complete picture of your engineering impact and health, drive high performance, and make smarter business decisions…Go to Span.app to learn more! SHOW NOTES:The results of ELC's first-ever hackathon: 14 leaders shipping fully functional apps (2:21)The “Scrappy” beginning: Extending the invitation and early community engagement (4:50)The most surprising insights: Problem solving for “life outside of work” and micromanaging AI agents (5:42)Navigating the shifting boundaries between product, engineering, and management roles (8:43)James' personal journey: Building 5 apps in 5 hours to stay relevant and relatable (10:05)Deconstructing the Hackathon structure: The “Take-Home Assignment” approach (16:16)The Hall of Fame: Creating artifacts to recognize contribution (18:00)Iterating on the format: Pivots made for the next hackathon iteration at Coursera (18:47)The importance of a 2-week ideation period for alignment (20:59)A recap of the playbook: Seeding ideas, easy tooling, and safe deployment (22:15)The future of hackathons: Cross-functional participation beyond engineering (26:46)Rapid Fire Questions (28:15) This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This is a special episode, highlighting a session from ELC Annual 2025! Bill Coughran (Partner @ Sequoia Capital & former SVP of Engineering @ Google) and Bret Reckard (Talent Partner @ The General Partnership) deconstruct the evolving role of engineering leadership in an era dominated by AI hype. Bill is a legendary leader who joined Google right after the .com bubble and has seen every major industry shift since. Drawing on his experience scaling Google and advising world-class startups, Bill shares why the best leaders are "catastrophic thinkers," how to balance servant leadership with the need for decisive action, and why AI is forcing every leader to return to their technical roots. Plus they cover enduring companies and real value capture in the AI era, the nuances of organizational design, the "apprentice model" for mentorship and the dangers of over-layered hierarchies that stifle speed. Bill also provides a candid look at leadership transitions, offering a tactical guide for those moving from Big Tech to early-stage startups. ABOUT BILL COUGHRANBill Coughran works as a founders' coach and partner at Sequoia Capital to help build spectacular technology-centric companies. Previously, Bill was Senior Vice President of Engineering at Google with oversight of Chrome, YouTube, maps, google.com, underlying infrastructure systems, and security.ABOUT BRET RECKARDBret Reckard is Talent Partner at The General Partnership (TheGP), a hands-on venture firm working alongside ambitious founders in talent, engineering, go-to-market, and product. He leads TheGP's Talent vertical, matching foundational leaders, early engineers, and key specialists across the portfolio. Before this role, Bret spent over a decade at Sequoia Capital leading Talent and Network, where he helped hundreds of founders at companies like Stripe, Confluent, Retool and DoorDash build their early teams. This episode is brought to you by Span!Span is the AI-native developer intelligence platform bringing clarity to engineering organizations with a holistic, human-centered approach to developer productivity.If you want a complete picture of your engineering impact and health, drive high performance, and make smarter business decisions…Go to Span.app to learn more! SHOW NOTES:Introduction and Bill Coughran's background at Sequoia and Google (1:36)Hiring pitfalls and the biggest mistakes made as a leader (3:49)Managing crises: Acting as a dictator during the 2010 Google hack (5:25)Building for the AI world without chasing "shiny objects" (7:09)Developing context: How to learn AI without relying on LLM summaries (9:02)Identifying enduring companies and real value capture in the AI era (10:53)The debate on coding assistants and the future of junior engineering talent (13:23)Transitions: Making the leap from large organizations to early-stage startups (15:59)Staying curious and finding excitement in the next professional challenge (18:23) LINKS AND RESOURCESLink to the video for this sessionLink to all ELC Annual 2025 sessions This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Edward H. Muñoz rose from humble beginnings as a first-generation Mexican American in a South Texas border town to build a 33-year career at Celanese, where he played a key role in transforming the company into a global leader in engineering materials. After earning a chemistry degree from the University of Texas at Austin, he joined Celanese during its pivot from fibers to high-value engineering resins and helped establish its polyacetal product as a serious competitor to industry giants like DuPont and GE. His journey included navigating corporate takeovers, leading multinational teams, confronting cultural bias, and accepting personal sacrifices, particularly the strain his ambition placed on family life. A near-fatal car accident that killed a close friend became a defining turning point, propelling him into international leadership roles and reshaping both his career trajectory and personal life. In this episode of Marketer of the Day, Edward Muñoz reflects on his legacy through his memoir Challenges, Triumphs, and Heroes: Memoirs of My Celanese Odyssey, which honors the people behind corporate success while capturing the human cost of leadership. He discusses his work in Germany and Mexico, his commitment to inclusive leadership, and the lessons learned from balancing ambition, culture, and responsibility. Now living with Parkinson's disease, he remains active through photography, travel, and leadership within the arts community, helping an organization not only survive the pandemic but grow significantly. Key takeaways include the importance of resilience, values-driven leadership, preserving personal history, and leaving something meaningful behind for future generations. Quotes: “The hardest challenge was balancing ambition with family. You gain a career, but you pay a price, and you have to decide what you are willing to give up.” “I am an American. That moment taught me how perception works and how easily people define others before they listen.” “You are not going to be around forever, so you have to leave something behind that others can learn from.” “When I think I might get fired, I remember this: I was looking for a job when I got here.” Resources: Connect with Edward H. Muñoz on LinkedIn Discover Edward H. Muñoz's journey from first-generation roots to global leadership. Get Challenges, Triumphs, and Heroes: Memoirs of My Celanese Odyssey on Amazon.

In this episode of Disruption/Interruption, host KJ sits down with Chris Dolezalek, Executive Vice President of R&D at Hum Capital. Chris shares his journey from Silicon Valley’s most highly funded startup to leading innovation in venture capital. He discusses the flaws in traditional VC, the power of resilience, and how technology and human insight are reshaping funding for diverse founders. Listeners will hear hard-won lessons from the edge of chaos, stories of near-failure and rebirth, and practical advice for founders seeking capital in uncertain times. Four Key Takeaways: Resilience is Essential [29:46]Chris emphasizes the importance of getting up after setbacks, sharing the Japanese saying, “Get knocked down seven times, get up eight,” and how resilience is a key trait for founders. Venture Capital Needs Disruption [8:15]Traditional VC relies on personal networks and outdated data, often excluding minority and female founders. Hum Capital is using real-time financial data and AI to democratize access to funding. Human Insight Complements AI [19:35]While AI can flag promising companies, Chris explains the need for human judgment—what he calls “AI whispering”—to make the best investment decisions. Learned Resilience and Growth [36:05]Chris introduces the concept of “learned resilience”—not just bouncing back, but learning from setbacks to come back stronger and smarter. Quote of the Show (32:52):“The truth about software is the Milli Vanilli effect. You don’t have to be able to sing. You just have to look good.” – Chris Dolezalek Join our Anti-PR newsletter where we’re keeping a watchful and clever eye on PR trends, PR fails, and interesting news in tech so you don't have to. You're welcome. Want PR that actually matters? Get 30 minutes of expert advice in a fast-paced, zero-nonsense session from Karla Jo Helms, a veteran Crisis PR and Anti-PR Strategist who knows how to tell your story in the best possible light and get the exposure you need to disrupt your industry. Click here to book your call: https://info.jotopr.com/free-anti-pr-eval Ways to connect with Chris Dolezalek: LinkedIn: http://www.linkedin.com/in/chrisdolezalek Company Website: https://humcapital.com How to get more Disruption/Interruption: Amazon Music - https://music.amazon.com/podcasts/eccda84d-4d5b-4c52-ba54-7fd8af3cbe87/disruption-interruption Apple Podcast - https://podcasts.apple.com/us/podcast/disruption-interruption/id1581985755 Spotify - https://open.spotify.com/show/6yGSwcSp8J354awJkCmJlDSee omnystudio.com/listener for privacy information.

Send us a textIn this conversation, Sarah Clatterbuck, a seasoned engineering leader with over 30 years of experience in tech, shares her journey at major companies such as Google, LinkedIn, and Yahoo. She discusses her recent decision to take a break from her career, her thoughts on leadership, the importance of authenticity, and the cultural differences she experienced after moving to Zurich. Sarah also reflects on the impact of COVID-19 on team dynamics and the challenges of executive leadership.Chapters00:00 Introduction to Sarah Clatterbuck01:13 Navigating Career Transitions05:03 The 30-Year Career Arc08:36 Transitioning into Engineering12:21 Growth at LinkedIn16:33 Challenges of Executive Leadership19:25 Leaning Out: A New Perspective21:11 Moving to Zurich: A New Chapter24:31 Cultural Differences in Leadership25:22 Building Culture During COVID28:59 Authenticity in Leadership32:20 Leaving the Google Bubble

This is a special episode, highlighting a session from ELC Annual 2025! OpenAI evolved from a pure research lab into the fastest-growing product in history, scaling from 100 million to 700 million weekly users in record time. In this episode, we deconstruct the organizational design choices and cultural bets that enabled this unprecedented velocity. We explore what it means to hire "extreme generalists," how AI-native interns are redefining productivity, and the real-time trade-offs made during the world's largest product launches. Featuring Sulman Choudhry (Head of ChatGPT Engineering) and Samir Ahmed (Technical Lead), moderated by Lawrence Bruhmeller (Eng Management @ Sigma). ABOUT SULMAN CHOUDHRYSulman leads ChatGPT Engineering at OpenAI, driving the development and scaling of one of the world's most impactful AI products. He pushes the boundaries of innovation by turning cutting‑edge research into practical, accessible tools that transform how people interact with technology. Previously at Meta, Sulman founded and scaled Instagram Reels, IGTV, and Instagram Labs, and helped lead the early development of Instagram Stories.He also brought MetaAI to Instagram and Messenger, integrating generative AI into experiences used by billions. Earlier in his career, Sulman was on the founding team that built and launched UberEATS from the ground up, helping turn it into a global food delivery platform. With a track record of marrying technical vision, product strategy, and large‑scale execution, Sulman focuses on building products that meaningfully change how people live, work, and connect.ABOUT SAMIR AHMEDSamir is the Technical Lead for ChatGPT at OpenAI, where he currently leads the Personalization and Memory efforts to scale adaptive, useful, and human-centered product experiences to over 700 million users. He works broadly across the OpenAI stack—including mobile, web, services, systems, inference, and product research infrastructure.Previously, Samir spent nine years at Snap, working across Ads, AR, Content, and Growth. He led some of the company's most critical technical initiatives, including founding and scaling the machine learning platform that powered nearly all Ads, Content, and AR workloads, handling tens of billions of requests and trillions of inferences daily.ABOUT LAWRENCE BRUHMELLERLawrence Bruhmuller has over 20 years of experience in engineering management, much of it as an overall head of engineering. Previous roles include CTO/VPE roles at Great Expectations, Pave, Optimizely, and WeWork. He is currently leading the core query compiler and serving teams at Sigma Computing, the industry leading business analytics company.Lawrence is passionate about the intersection of engineering management and the growth stage of startups. He has written extensively on engineering leadership (https://lbruhmuller.medium.com/), including how to best evolve and mature engineering organizations before, during and after these growth phases. He enjoys advising and mentoring other engineering leaders in his spare time.Lawrence holds a Bachelors and Masters in Mathematics and Engineering from Harvey Mudd College. He lives in Oakland, California, with his wife and their three daughters. This episode is brought to you by Span!Span is the AI-native developer intelligence platform bringing clarity to engineering organizations with a holistic, human-centered approach to developer productivity.If you want a complete picture of your engineering impact and health, drive high performance, and make smarter business decisions…Go to Span.app to learn more! SHOW NOTES:From research lab to record-breaking product: Navigating the fastest growth in history (4:03)Unpredictable scaling: Handling growth spurts of one million users every hour (5:20)Cross-stack collaboration: How Android, systems, and GPU engineers solve crises together (7:06)The magic of trade-offs: Aligning the team on outcomes like service uptime vs. broad availability (7:57)Why throwing models "over the wall" failed and how OpenAI structures virtual teams (11:17)Lessons from OpenAI's first intern class: Why AI-native new grads are crushing expectations (13:41)Non-hierarchical culture: Using the "Member of Technical Staff" title to blur the lines of expertise (15:37)AI-native engineering: When massive code generation starts breaking traditional CI/CD systems (16:21)Asynchronous workflows: Using coding agents to reduce two-hour investigations to 15 minutes (17:35)The mindset shift: How rapid model improvements changed how leaders audit and trust code (19:00)Predicting success: "Vibes-based" decision making and iterative low-key research previews (20:43)Hiring for high variance: Why unconventional backgrounds lead to high-potential engineering hires (22:09) LINKS AND RESOURCESLink to the video for this sessionLink to all ELC Annual 2025 sessions This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Brian Balfour (Founder & CEO @ Reforge) deconstructs the two core, interconnected challenges leaders face in the AI age: deciding what to build and evolving the Engineering, Product, Design workflow to deliver it. We cover why you should avoid “the local maxima trap” and siphon off "skunkworks" teams to take high-risk, AI-native bets. Brian provides the blueprint for the "Great Distribution Shift," detailing how to reshape your product from the ground up to avoid being left behind as platforms close, and how to emerge as a winner in the new AI landscape. Plus, learn how to rethink what to build, avoid commoditization, compress product discovery from weeks to hours, scale feature variations & prototypes, evolve products to solve harder classes of problems and shift specialist roles from "inboxes" to system builders. ABOUT BRIAN BALFOURBrian Balfour is the Founder & CEO of Reforge, which provides expert training and tools for AI-native product teams. Previously, he served as VP of Growth at HubSpot, spearheading launches like HubSpot CRM and building the growth team that propelled the company's next chapter. This episode is brought to you by Span!Span is the AI-native developer intelligence platform bringing clarity to engineering organizations with a holistic, human-centered approach to developer productivity.If you want a complete picture of your engineering impact and health, drive high performance, and make smarter business decisions…Go to Span.app to learn more! SHOW NOTES:Brian's reaction to the 5:1 gap between AI coding usage and actual product quality challenges (1:57)Why your system only goes as fast as the slowest part, and how hyper-optimizing engineering moves bottlenecks elsewhere (4:53)The "Local Maxima" trap: Why turning designers and PMs into mediocre developers is a waste of opportunity cost (6:04)Siphoning off "Skunkworks" Teams for AI-Native Innovation (7:53)Moving from exploring two solution paths to ten by simulating "product reps" through AI prototyping (13:24)Reforge's AI-native suite (Build + Research): Scaling prototypes, feature variations and compressing product discovery & validation from weeks to hours (15:43)Case Study: How Captions evolved to solve harder classes of problems, using a creator-tool wedge to fund custom AI emotion-models for the media studio market (19:54)Case Study: How Shopify reframed support agents as multimodal "Business Advisors" to provide outsized value (22:24)Navigating the great distribution shift: Understanding the lifecycle from open platforms to closed ecosystems (25:10)The lifecycle of distribution shifts: Navigating the "Open Phase" growth to "Closed Phase" monetization w/ examples from Facebook, Google, and Apple (29:30)OpenAI, memory & context as moat, and why you need to reshape your product from the ground up to win in this distribution shift (31:16)Strategic de-risking for EPD leaders: Building proprietary moats through memory, context, and specialized workflows (32:51)Optimizing EPD workflows and structures: Separate high-risk "skunkworks" from core product optimization, lean cross-functional teams for faster iteration / decisions, and avoiding too many specialized roles (35:25)Dissolving the "Octagon of Specialists": Shifting researchers and PMMs from "inboxes" to builders of self-serve systems (36:57)The five types of product work and why there is no "one-size-fits-all" system for EPD (41:25)Rapid fire questions (43:25)LINKS AND RESOURCESAbout Reforge: Expert training & AI-powered tools for product teamsReforge Build: The prototyping tool discussed for exploring multiple feature variations without designer constraints.Reforge Research: The AI-interviewer tool used to compress user discovery and validation from weeks to hours.Reforge Insights: The platform that aggregates qualitative customer feedback into a self-serve system for EPD teams.Brian Balfour's Research & FrameworksBrianBalfour.com: Brian's personal blog featuring deep dives into growth and product strategy.The Next Great Distribution Shift: The foundational article explaining the lifecycle of open vs. closed platforms.The Four Fits Framework: A refresher on the system of Product-Market Fit, Product-Channel Fit, Channel-Model Fit, and Model-Market Fit.Reforge Strategic Deep DivesAI Disruption Risk Assessment: A guide for engineering leaders to determine if their product is at risk of being commoditized.Product-Market Fit (PMF) Collapse: How to identify and avoid the risk of your core product losing relevance in the AI era.MentionsInvest Like the Best podcastThis episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of Wine After Work, Bryce Batts sits down with Anthony Fasano, founder of Engineering Management Institute, to talk about what leadership really looks like inside engineering and AEC firms today. Anthony has spent years helping engineers grow beyond technical excellence into confident, people-first leaders — and in this conversation, we unpack what firms get wrong about leadership development, why burnout is so common in AEC, and how engineers can build careers that feel both successful and sustainable. In this episode, we cover: Why technical skill alone isn't enough to advance in engineering leadership The biggest leadership blind spots holding AEC firms back How engineers can develop communication, confidence, and influence without losing credibility What career growth really looks like in today's AEC landscape How firms can retain talent by investing in leadership development earlier Whether you're an engineer navigating your next career move or a leader trying to build stronger teams, this episode offers practical insight and perspective you won't want to miss.   https://engineeringmanagementinstitute.org   https://www.linkedin.com/in/anthonyjfasano/  

Rajeev Rajan (CTO @ Atlassian) shares the leadership playbook he used to transform Atlassian's engineering culture, and how that cultural foundation directly powered the build and launch of Rovo (Atlassian's new AI powered app). We cover how they reduced ship time from 120 days to zero, why “developer joy” is the metric that matters, and how to create a community of developer productivity champions to scale DevEx transformation. Rajeev also breaks down his principles for systematizing autonomy and empowerment, including frameworks for giving direct reports more ownership. Plus, a look at the future of Atlassian's “Systems of Work”! ABOUT RAJEEV RAJANRajeev Rajan is the Chief Technology Officer (CTO) at Atlassian. Rajeev joined the company in May 2022 and is responsible for Atlassian Engineering, IT, Security and Trust, and the Engineering Operations teams. His focus areas include the company's continued transformation to Cloud, Developer Platform, and Product lines. Additionally, he is passionate about continuing to develop Atlassian's world-class engineering organization and making it a top choice for aspiring engineering talent worldwide.A long-time resident of Washington state, Rajeev previously acted as the Vice President and Head of Engineering for Facebook and Head of Office for Meta in the Pacific Northwest Region. Prior to Meta, Rajeev spent more than two decades with Microsoft, first joining as an intern in 1994. During his time there, he worked on many products, culminating in Office 365 where he built and led the team responsible for all of the Cloud Infrastructure for Office 365.Rajeev is married with two children and a spunky yellow lab named Rayna. He is very involved in and passionate about a number of efforts that uplift the local community, ranging from the arts to STEM programs. SHOW NOTES:The "Listening Tour": Grounding leadership in reality and identifying friction points (3:52)The Confluence Editor story: Reducing ship time from 120 days to 0 (6:26)Moving beyond productivity: Why "Developer Joy" is the metric that matters (8:45)Creating a community of Developer Productivity Champions and the power of a Productivity Summit (13:44)Elevating productivity to a company-level OKR and measuring qualitative sentiment (17:12)Leadership framework: Deciding when to "manage through people" vs. "manage through process" (19:05)How to give more direct ownership / responsibility to a DRI (23:03)Alignment conversations about prioritizing developer joy & productivity (24:22)Challenges faced during Atlassian's developer joy transformation journey (26:23)How the "Developer Joy" foundation enabled building Rovo in just 6 months (30:02)The "System of Work": Expanding Jira's utility beyond engineering to finance, marketing, and legal (33:22)Rapid Fire Questions (40:48) This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/5 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The common narrative suggests AI will make engineering leadership obsolete, but history - and the Industrial Revolution - suggests the opposite is true. Engineering executive Manoj Mohan joins the show live from ELC to argue that as code generation costs drop, the demand for high-level judgment and strategic oversight will only skyrocket. He breaks down why leaders must stop starting with models and start with customer pain points, utilizing his "3GF" framework to manage the risksLinearB: Measure the impact of GitHub Copilot and CursorFollow the show:Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelLeave us a ReviewFollow the hosts:Follow AndrewFollow BenFollow DanFollow today's guest(s):Connect with Manoj: LinkedIn | SubstackOFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

Eric Bowman (CTO @ King.com, previously CTO at TomTom and VP Engineering at Zalando) returns to the alphalist podcast to unpack what “agentic engineering” really means in practice—and how to introduce it to teams without turning it into a mandate. We talk about the uncomfortable trade-offs behind “YOLO mode” tooling, why adoption should feel voluntary even when you set explicit goals (like “five AI-assisted commits” as a company-level key result), and why the real opportunity isn't just faster coding—it's building a learning system that relentlessly reduces time-to-learning and time-to-value. The conversation spans practical rollout patterns, DORA/value-stream thinking, Toyota's Andon-cord mindset applied to software, multi-agent decision support with MCP, and why the CTO role may keep converging with product as AI pushes organizations to optimize for iteration speed over output volume.

Ever wondered how an engineer's mindset can transform complex challenges into innovative solutions? In this conversation with Josh Tarbutton, PhD, PE, founder of Bravo Team, Cam and Otis explore the intersection of engineering excellence and entrepreneurial spirit."Engineering is about solving problems," Josh explains, drawing from his extensive experience as a military veteran, professor, and now leader of a premier engineering firm. From discussing the importance of custom machine design and automation to sharing insights about the Hero's Journey in professional development, this episode offers a deep dive into the world of advanced R&D.What makes this conversation particularly valuable is Josh's unique perspective on leadership and innovation. "The best solutions often come from understanding the narrative," he shares, emphasizing the role of storytelling in engineering and business. Whether you're an aspiring engineer, a business leader facing technical challenges, or simply curious about the future of automation, Josh's insights provide a roadmap for navigating complex problems with creativity and precision.More About Josh:Joshua Tarbutton, PhD, PE is an engineer, entrepreneur, and U.S. Army veteran, leading Bravo Team, a premier engineering firm specializing in custom machine design, automation, and advanced R&D. With a BSME from Georgia Tech and an MS andPhD in Mechanical Engineering from Clemson University, he spent nearly a decade as a professor, earning tenure at UNC Charlotte, publishing 53 research papers and securing millions in research funding. His eight years of military service instilled a disciplined, problem-solving mindset that drives his leadership. He is an Entrepreneur Organization member, where he has served as an Accelerator Coach and board member. Founded in 2018, Bravo Team partners with Fortune 500 companies, OEMs, and industrial manufacturers to solve complex engineering challenges. The firm excels in machine design, automation, PCB development, and software engineering, providing custom-built solutions where off-the-shelf options fall short. Joshua is dedicated to advancing engineering excellence, transformative automation, scalable innovation for industry leaders, and helping people find their narrative in the Hero's Journey.#10xyourteam #LeadershipDevelopment #EngineeringMindset #ProblemSolving #InnovationCulture #EntrepreneurialLeadership #VeteranLeaders #AutomationSolutions #AdvancedEngineering #RAndDInnovation #BusinessGrowthStrategiesChapter Times and Titles:From Military Service to Engineering Leadership [00:00 - 10:00]Introduction to Josh Tarbutton and Bravo TeamThe journey from Army veteran to engineering entrepreneurHow military discipline shapes problem-solvingCustom Solutions for Complex Challenges [10:01 - 20:00]The importance of custom machine design and automationWhy off-the-shelf solutions often fall shortPartnering with Fortune 500 companies for innovationThe Hero's Journey in Engineering [20:01 - 30:00]Understanding the narrative in problem-solvingHow storytelling enhances engineering solutionsThe role of the Hero's Journey in professional growthAdvancing Engineering Excellence [30:01 - 40:00]Josh's experience as a professor and researcherThe impact of publishing and securing research fundingBuilding a culture of innovation at Bravo TeamLeadership and Innovation in Practice [40:01 - 50:00]Balancing technical expertise with entrepreneurial visionLessons from serving as an Accelerator CoachEncouraging scalable innovation in industry leadersConnecting with Bravo Team [50:01 - End]How to learn more about Bravo Team's servicesFinal thoughts on engineering and entrepreneurshipContact information and resources for further explorationJosh Tarbuttonhttps://www.link

In this episode, Daniel Lereya (Chief Product and Technology Officer @ Monday.com) shares how they are evolving their engineering roles from developers to builders & system designers, where the lines between product, engineering, and design are intentionally blurred, and developers manage AI Agents as team members, tackling an ever-expanding list of projects. We explore the shift from "developer" to "system designer" and why managing AI agents requires the same skills as managing people. Plus, a case study where the Monday.com team leveraged AI agents to decompose a monolith, autonomously manage the project board and assign strategic / high-risk tasks to humans. ABOUT DANIEL LEREYADaniel Lereya has served as Chief Product and Technology Officer at monday.com since 2023. In this role, he focuses on advancing monday.com's multi-product vision and operational efficiencies while driving execution to support company growth. Previously, he was Vice President of R&D and Product, leading global teams in shaping and executing the company's product strategy through innovation and technology. Before joining monday.com, Daniel held leadership and engineering roles at IBM and SAP. SHOW NOTES:The three core principles of monday.com's culture: Ownership, Transparency, and Speed of Execution (3:59)How AI acts as an accelerant to implement these cultural principles at scale (8:36)Why the “Developer” role is evolving into a “Strategic Builder” and “System Designer” (13:47)Breaking silos: How the “Builder” role blurs the lines between product, engineering, and design (17:13)Real-world example: A designer using AI to submit code and fix UI issues independently (19:09)Case Study: The “Agent Factory” & how a weekend prototype by one leader shifted the product roadmap (21:25)Operationalizing transparency: Using internal tools (“Big Brain”) to align every builder on daily business impact (25:58)The “Kickoff Meeting” framework: A strict protocol for falling in love with the problem, not the solution (32:26)The new management paradigm with AI agents as team members (37:31)Rapid fire questions (42:09) This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This is a special episode, highlighting a session from ELC Annual 2025! The true promise of AI isn't in replicating human intelligence. It's in developing entirely new forms of non-human intelligence that perceive and understand the world in fundamentally different ways. Jamie Lien (Co-Founder and Chief Scientist @ Archetype AI) and Rashi Agarwal (Head of AI Engineering @ GoodLeap) explore the emergence of "Physical AI" - machines that sense the world through modalities beyond human biology to form internal representations free from our biases. This means building machines that can directly sense the physical world through modalities beyond human biology, form their own internal representations and interpretations free from our biases, and then translate that understanding back to us in human terms. ABOUT JAIME LIENJaime Lien, Ph.D. is Co-Founder and Chief Scientist at Archetype AI, a pioneering startup advancing Physical AI, artificial intelligence that understands the real world through real-time sensor data fusion.With over a dacade of experience in radar-based sensing, signal processing, and hardware engineering, Jaime's career bridges cutting-edge research and consumer-ready innovation. Before Archetype, she led radar sensing development for Google ATAP's Project Soli and contributed wireless communication and localization expertise at NASA's Jet Propulsion Laboratory. ABOUT RASHI AGRAWALRashi Agrawal is Head of AI Engineering at GoodLeap, where she leads enterprise-wide AI initiatives that deliver real business impact. An accomplished speaker, she covers the latest in AI, including context engineering, evaluations, and multi-agent collaboration, while driving Applied AI innovation in the enterprise. Previously, she scaled engineering teams at Yahoo, advancing its multibillion-dollar advertising business. A passionate world traveler to 40+ countries, Rashi brings global perspective and energy to her leadership and storytelling. SHOW NOTES:Archetype AI's mission: Building a foundation model for physical reality (2:24)The potential for discovery: Using AI to observe phenomena humans cannot perceive (3:36)Augmentation vs. Replacement: Giving humans "superpowers" rather than automating them away (5:48)The "Perfect Storm" for Physical AI: Transformers, self-supervised learning, and commodity sensors (6:04)Defining “Non-Human Intelligence” and removing the constraints of human labels (8:34)Why language is inherently lossy and insufficient for true physical understanding (10:28)Real-world application: How Physical AI aids safety decision-making in the solar industry (12:35)Use case: Improving pedestrian safety and traffic signaling in Bellevue (14:51)The biggest engineering leadership challenge: Embracing the “messiness” of real-world data (16:21)Q&A: Why we shouldn't teach AI physical laws, but let it discover them (18:50)Q&A: Validating models when there is a defined ground truth vs. subjective language (20:49)Q&A: Compute requirements and the future of active learning at the edge (22:05) LINKS AND RESOURCESVideo version of Jaime and Rashi's session at ELC Annual 2025 This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

If you've ever shipped an AI feature that looked great in testing — only to watch it behave unpredictably in production — you're not alone.In this episode of IT Visionaries, host Chris Brandt talks with Lawrence Jones, Founding Engineer at incident.io, about the critical gap between AI that demos well and AI that works under pressure. Lawrence shares how his team designs tools that help engineers respond faster, learn from failure, and build systems that don't crumble when it counts. CHAPTERS / KEY MOMENTS00:00 - AI Chaos & The Mike Tyson Rule00:58 - Meet Lawrence Jones of Incident.io03:14 - From FinTech Outages to Incident Response06:22 - The Biggest Mistake in Incident Management09:08 - Training for Chaos: Game Day Simulations10:31 - Inside the AI SRE System13:01 - What SRE Really Means16:23 - From Prototype to Production AI20:27 - Keeping Up with AI's Rapid Evolution22:50 - Understanding Vector Databases & Embeddings28:34 - The Architecture Problem: Chaining Prompts at Scale36:11 - Measuring AI Performance & Reliability44:02 - The Future of SRE Meets AI52:10 - Lessons from Real Incidents56:42 - Final Thoughts: Building AI That Works -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, I talk with Dr. Feniosky Peña-Mora, Sc.D., P.E., F.ASCE, ASCE President and National Dean, School of Engineering and Sciences at Tecnológico de Monterrey, about civil engineering leadership and its future impact. We discuss how his upbringing in the Dominican Republic shaped his approach to leadership, the evolving demands of civil engineering education, […] The post How Civil Engineering Leadership Is Shaping the Future – Ep 300 appeared first on Engineering Management Institute.

I want to dive into the concept of Deliberate Practice, which sets the greatest apart in fields ranging from sports to writing to engineering. I'll explain why it's much more than just repetition or experience, and why applying it to your career can lead to rapid improvement. Most importantly, I will provide concrete ways you can apply deliberate practice to level up your engineering and leadership skills, especially in areas that are traditionally difficult to practice, such as communication and strategic decision-making.Differentiate Practice from Deliberate Practice: Understand that while repetition is part of practice, deliberate practice specifically involves engaging in a very narrow set of activities with the intentional goal of improvement, requiring very quick feedback for continuous incorporation.Identify Opportunities for Rapid Improvement: Learn why deliberate practice is much more effective at achieving rapid improvement than simply engaging in repetition.Apply DP to Leadership Skills: Discover how to incorporate deliberate practice into roles like engineering manager, tech lead, or IC (Individual Contributor) leader, where the activity of practice is often harder to pinpoint.Leverage Existing Work for Practice: I suggest a mindset shift where you begin looking at existing responsibilities, such as one-on-ones, as opportunities for practice. For example, you can focus on improving your clarity when providing constructive criticism and ask for specific feedback on that aspect.Generate Novel Value Through Practice: Explore how engaging in deliberate practice activities—like recording a video to communicate a technical concept or creating documentation—serves the primary goal of practice, while almost certainly creating unexpected value for your team (often net neutral or positive).Use Backwards Training for Strategy: Find out how to practice strategic decision-making and forecasting by using "backwards training". This involves reviewing past decisions or work scopes, creating your own rationale or estimate, and then calibrating it against the known reality.Simulate Difficult Conversations: Consider leveraging Large Language Models (LLMs) to engage in deliberate practice around language-heavy skills, such as modelling sensitive or difficult topics, or practicing receiving harsh feedback.