The Engineering Leadership Podcast

In this episode, Pratima Arora, Chief Product and Technology Officer @ Smartsheet, dives into what it means to be a modern builder as product, design, and engineering roles converge into today’s post-AI world. She and Jerry discuss why the modern builder model is disrupting traditional engineering processes / responsibilities as individuals embrace a breadth of skills while maintaining individual expertise. They cover how to encourage “cross-pollination” of roles, maintaining product quality while improving iteration speed, facilitating bottom-up contributions, creating context / knowledge graphs to inform agents, examples of good product builders, and what this means for hiring.

ABOUT PRATIMA ARORA

Pratima Arora is the Chief Product and Technology Officer at Smartsheet. In this position, she is responsible for the company’s product management, product marketing, user experience, pricing and packaging, and digital and product partnerships.

An accomplished technology executive, Pratima has more than 20 years of experience as a product and technology leader with a passion for building innovative tools that solve real problems.

She has held senior product leadership roles at Atlassian and Salesforce, working on some of the companies’ highest-revenue products. Most recently, she was Chief Product and Technology Officer at Chainalysis, where she led the global R&D organization for one of the world’s top blockchain data platforms.

She holds a B.S. in Physics, an M.S. in Computer Science, and an MBA from UC Berkeley’s Haas School of Business.

The CAFE(S) framework is a research-backed definition of context quality for AI agents.

DX collaborated with researchers at Capital One, Google, and UVic to give teams a shared standard for reviewing agent context by breaking it into five properties: clarity, actionability, fidelity, efficiency, and security.

Your agent is only as good as its context and the CAFE(S) framework establishes a shared language around context to help you better understand how & why agents go wrong.

Check it out here!

SHOW NOTES:

• Introducing Pratima & her role @ Smartsheet (1:21)
• Pratima’s insights on the CPTO role / the modern builder (3:11)
• How the modern builder idea is disrupting traditional processes (4:52)
• Maintaining product quality while improving building speed (6:48)
• Understanding boundaries / designated roles as builder role expands (9:19)
• Reward your teams & develop a mindset of cross-pollinating roles (11:32)
• Benefits of a flexible modern builder role within teams (14:02)
• The relationship between modern builders & skill development (17:28)
• Strategies for facilitating bottom-up contributions across roles (19:44)
• Defining the chief AI officer’s responsibilities / team roles (21:30)
• What internal launches / adoption techniques look like @ Snapsheet (24:29)
• Creating & maintaining the knowledge graph that informs agents (26:05)
• The role of experts / specialities within the modern builder framework (29:28)
• What the modern builder role means for the org chart (32:17)
• Examples of modern builder archetypes (34:06)
• Skills that make a good product builder (35:07)
• Hiring insights when it comes to bringing in new modern builder talent (36:08)

This episode wouldn’t have been possible without the help of our incredible production team:

Jerry Li - 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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Sagnik Nandy (CTO & EVP of Engineering @ Docusign) joins Jerry to discuss keys to success when it comes to peer-led AI transformation. Sagnik shares how they approached AI adoption internally @ Docusign with the use of both champions & multipliers, understanding trade offs associated with AI adoption, determining which tasks to assign to agents, frameworks for measuring the ROI of agentic tools, and how it helps bring value to your customers. He also discusses how to measure the customer productivity index (CPI) and what it takes to mitigate customer issues when scaling AI internally.

ABOUT SAGNIK NANDY

Sagnik Nandy is the Chief Technology Officer and Executive Vice President of Engineering at Docusign responsible for engineering, cloud operations, and technology strategy that enables customers globally to run their organizations on Docusign.

Most recently, Sagnik served as the President and Chief Development Officer for Workforce Identity at Okta where led engineering development and operations, product management, and design and user research. Earlier, he joined Okta as their CTO, overseeing the engineering and business technology arms of the company.

Prior to Okta, Sagnik served as the Vice President of Engineering at Google where he oversaw several critical components of Google’s core advertising business, the backbone of the company’s growth and revenue. During his 15 years at Google, Sagnik also helped build Google’s Measurement and Analytics offerings and took several products from inception to becoming market leaders.

Sagnik has a bachelor’s degree from the BITS, Pilani (Birla Institute of Technology and Science Pilani) and a Ph.D. in computer science and engineering from UC San Diego.

The CAFE(S) framework is a research-backed definition of context quality for AI agents.

DX collaborated with researchers at Capital One, Google, and UVic to give teams a shared standard for reviewing agent context by breaking it into five properties: clarity, actionability, fidelity, efficiency, and security.

Your agent is only as good as its context and the CAFE(S) framework establishes a shared language around context to help you better understand how & why agents go wrong.

Check it out here!

SHOW NOTES:

• Introducing Sagnik & his role @ Docusign (1:28)
• Strategies for approaching AI transformation internally (2:52)
• How to create early goals & iterate quickly (4:50)
• Using DocuWiki as a source of truth for agents (9:10)
• How multipliers can address architecture-related decision making (11:12)
• Understanding the role of multipliers & organizational accountability (12:43)
• Trade offs eng leaders have to make when scaling AI adoption (14:05)
• Illustrating the standard AI workflow / where human decision making steps in (16:22)
• Frameworks for measuring the customer value of agents (20:13)
• Steps for mitigating risks of customer-facing issues when scaling AI internally (26:13)
• Tackling cost considerations when it comes to AI adoption (30:35)
• Best practices for maintaining your AI usage / methodology across a large org (35:06)
• How to AI effectively as a CTO (37:25)
• Rapid fire questions (38:39)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Amit Gupta, Partner @ SNR Ventures, joins Jerry to discuss his unique eng leadership journey and how that led him to his second career as an investor / coach. We cover some of the lessons learned throughout his time working as VP of various startups and how those experiences shaped his desire to start his own consulting business. Amit defines what a coaching tree is and his philosophy when it comes to mentorship, picking the right projects, and determining what a team needs to work effectively together. Throughout the conversation, we revisit why effective engineering coaching also includes mentorship around company building. Lastly, Amit discusses why eng leaders make good investors and how investing was a natural continuation off of engineering for him.

ABOUT AMIT GUPTA

Amit Gupta has held leadership roles at multiple high-growth companies from early-stage through the public markets, including Qualcomm, INQ Mobile, Lookout, and Benchling. He combines concentrated, early stage investing with a passion for helping technical founders with company building. In some cases that materializes into a role helping in the trenches and in others a more passive, help as needed voice. Amit has helped countless companies directly and as an advisor to Y Combinator Continuity.

The CAFE(S) framework is a research-backed definition of context quality for AI agents.

DX collaborated with researchers at Capital One, Google, and UVic to give teams a shared standard for reviewing agent context by breaking it into five properties: clarity, actionability, fidelity, efficiency, and security.

Your agent is only as good as its context and the CAFE(S) framework establishes a shared language around context to help you better understand how & why agents go wrong.

Check it out here!

SHOW NOTES:

• Amit’s transition from Qualcomm (1:05)
• Talent acquisitions challenges faced when starting a company (4:58)
• Lessons learned from Amit’s time @ Qualcomm (8:24)
• Strategies for building a support networks as an eng leader (9:41)
• An example of effective mentorship in Amit’s career (11:00)
• Defining work-life integration & how that influences Amit as a coach (12:55)
• Transitioning from a second startup / starting his own consulting business (14:05)
• Why the work at Benchling wasn’t as hard as the first couple startups (16:21)
• Amit’s favorite behavioral interview question (17:40)
• Shared traits of great teams who perform well together (18:56)
• Frameworks for determining good leaders vs. good managers (20:38)
• Ways to feed your high-aptitude leaders (23:18)
• An example of a rewarding coaching scenario (25:25)
• Amit’s perspective on investing as an extension of building (29:38)
• Strategies for determining which bets will be successful (32:16)
• Considerations for the eng leader to investor pipeline (34:43)
• Rapid fire questions (39:53)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Zohar Einy, CEO & Co-Founder @ Port, shares best practices for building a software factory, how software factories impact the organizational structure of your org, and scaling strategies. He and Jerry discuss why software factories can contribute to a significant ROI, tools for helping your teams navigate the transition from building a product for agents vs. people, and what scary (but healthy) decision-making looks like as an eng leader in a post-AI world. Zohar also shares some of his core beliefs when it comes to developing talent & hiring young engineers @ Port.

ABOUT ZOHAR EINY

Zohar Einy is the co-founder and CEO of Port, the agentic SDLC platform helping companies like GitHub, Visa, and PwC build and scale their AI Software Factories. Port has raised $158M, backed by General Atlantic, Accel, Bessemer Venture Partners, Team8, and TLV Partners.

The idea for Port began during Zohar and co-founder Yonatan Boguslavski’s time as engineers in the IDF’s Unit 8200, where they built a platform to help developers move more quickly at scale. After recognizing the same challenge across the broader market, they founded Port in 2022.

The CAFE(S) framework is a research-backed definition of context quality for AI agents.

DX collaborated with researchers at Capital One, Google, and UVic to give teams a shared standard for reviewing agent context by breaking it into five properties: clarity, actionability, fidelity, efficiency, and security.

Your agent is only as good as its context and the CAFE(S) framework establishes a shared language around context to help you better understand how & why agents go wrong.

Check it out here!

SHOW NOTES:

• Introducing Zohar & his background / main focus (1:02)
• Defining what a software factory is & what that means for the industry (1:50)
• Parallels between a physical factory vs. a software factory (3:50)
• How the software factory model impacts organizational structure (5:27)
• What certification means in the context of software factories (8:46)
• Best practices for building a new software factory (10:48)
• Don’t make the ability to scale an afterthought (12:15)
• Navigating the balance between control & automation when building from scratch (13:17)
• How to know when a team / function merits its own software factory (14:37)
• Transitioning from a pre-AI to post-AI world as a large company (16:18)
• Inside Port’s rebuild using AI & navigating the team through the transition (18:00)
• The team’s reaction to building for agents vs. humans (20:25)
• Approaching decision-making with a healthy dose of trepidation (21:48)
• Characteristics that make for good hires today (22:51)
• Examples of product-related decisions that felt scary in the moment (25:03)
• Lessons learned while Port transitioned to building for agents (27:27)
• How to measure the ROI of software factories (29:05)
• Insights on how to best allocate resources across a mature company (31:10)
• Hiring hungry, young talent vs. hiring established talent (32:56)
• Rapid fire questions (35:30)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ali Dasdan, CTO @ Dropbox, joins the pod to share insights on the company’s large-scale AI adoption and research as a foundation of successful engineering leadership. First, Ali shares insights on why he continues publishing research despite his role as a CTO and how research / curiosity can drive better trust within your organization. He shares about how his research ultimately guided decision making regarding redrawing Dropbox’s entire architecture and the importance of creating a record of the company’s progression as the rearchitecture occurred. The bulk of the conversation centers around how Dropbox is adopting AI, including tools like Nova and Dash, within both EPD and non-EPD departments.

ABOUT ALI DASDAN

Ali Dasdan is a C-suite technology executive with 25+ years building, scaling, and leading global engineering, product, and technical-operations organizations of up to ~1,000 people across a dozen industries, in public companies, high-growth startups, and enterprises in Silicon Valley and London.

Today he is CTO of Dropbox, serving over 700 millions of users on an exabyte-scale platform with $2.5B+ revenue, where he also leads the AI strategy and AI enablement. Previously EVP and CTO of ZoomInfo and VP of Engineering at Atlassian (Confluence Cloud, Trello, Jira Work Management). As CTO (at Turn, Vida, Poynt, ZoomInfo, and Dropbox) he defines and owns company-wide technology strategy; in divisional roles (eBay, Atlassian, Tesco, Yahoo) he led engineering for revenue-critical parts of the business.

SHOW NOTES:

• Why Ali continues to publish research as a CTO (1:51)
• How research results can alter decision making as an eng leader (3:30)
• The connection between research & organizational trust (4:29)
• Redrawing the org’s architecture to learn more about it (6:00)
• What kinds of info help eng leaders better understand the business / technology (8:12)
• Building a record of the org’s progress & development (10:13)
• Where Dropbox is at in their AI adoption journey (11:58)
• AI @ Dropbox in EPD vs. non-EPD functions (13:36)
• Frameworks for implementing AI at the highest level (15:23)
• The engagement / ownership model @ Dropbox (16:58)
• Insights on Nova, Dropbox’s code review AI workflow (18:59)
• Incorporating human-driven feedback into the AI loop (21:12)
• What the immediate future looks like for automated developer tools (23:54)
• How AI has directly impacted productivity @ Dropbox (27:15)
• Addressing bottlenecks related to AI adoption (30:35)
• Using AI infrastructure to assist in non-EPD functions (32:33)
• Dash as a contextual AI platform (35:39)
• Ali’s experience with specialized models vs. foundation models (38:10)
• Rapid fire questions (39:48)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Jerry discusses key insights on delegating to agentic tools while maintaining high levels of engineering ownership with Ozzie Osman, co-founder @ Monarch. Ozzie shares what it looks to pursue two paths when it comes to AI: agentic-forward and human-orchestrated pipelines. They also cover the specific AI tools that are used in Monarch, including Devin and Voltron; assigning tasks to be AI-first vs. human-led; determining which pieces of customer feedback lead to new features; and common challenges when it comes to AI-generated code and what the human review process for it looks like.

ABOUT OZZIE OSMAN

Osman (Ozzie) Osman is co-founder of Monarch. He is the lead author of the Holloway Guide to Technical Recruiting and Hiring. He has built products and engineering teams at companies including Quora and Google. Ozzie has also started two companies that have been acquired, and advised dozens of other startups.

Sinch is the communications infrastructure the AI era runs on.

There's a layer of infrastructure behind every text, call, and login code your product sends, and it works exactly like plumbing: nobody thinks about it until it's the reason something broke.

Most providers route through 4-6 intermediaries; Sinch connects in 1-2 hops, direct carrier relationships across 600+ connections, handling 900 billion interactions a year across 60+ countries.

Routing, compliance, fraud prevention handled automatically rather than manually managed by the business sending the message!

Sinch is the reliability layer underneath AI-driven customer communications; the infrastructure that determines whether an AI agent's output actually reaches a real person as a delivered text, connected call, or verified interaction.

Check it out here!

SHOW NOTES:

• Introducing Ozzie & his role @ Monarch (2:37)
• Where Monarch is at in terms of technology transformation / user adoption (5:20)
• Insights on how Monarch is embracing AI with a security-forward mindset (7:21)
• What it looks like to pursue both agent- and human-orchestrated AI pipelines (11:00)
• Dissecting how an MCP shared infrastructure improves productivity (13:11)
• Inside the enablement team @ Monarch (15:25)
• Why Monarch uses Devin / prioritizing autonomy (16:33)
• How to fine-tune an agent to make it reusable (18:40)
• Strategies for determining what is an AI-centric vs. human-centric task (20:47)
• Understanding when & why Devin fails (24:49)
• Devin’s role in assisting the human-orchestrated processes (26:39)
• What a typical flow looks like throughout an SDLC (28:05)
• The importance of ownership in engineering when reviewing AI-generated code (29:31)
• Frameworks for prioritizing feature requests based on user feedback (35:15)
• Ozzie’s perspective on the role of engineering teams (40:03)
• Final thoughts on navigating AI-related anxieties (43:08)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jakub Oleksy, SVP of Software Engineering @ Github, joins the podcast to discuss how Github is addressing some of the biggest challenges facing the industry when it comes to infrastructure scaling, customer capacity, and using AI to add value to your org’s processes and eng leaders’ decision-making. He shares how scaling looked different at Github six years vs. today, how they navigated the migration to Azure, and what AI transformation looks like individually & at the team level. Jakub also discusses insights for eng leaders when it comes to investing in yourself & your people and making cross-functional decisions.

Sinch is the communications infrastructure the AI era runs on.

There's a layer of infrastructure behind every text, call, and login code your product sends, and it works exactly like plumbing: nobody thinks about it until it's the reason something broke.

Most providers route through 4-6 intermediaries; Sinch connects in 1-2 hops, direct carrier relationships across 600+ connections, handling 900 billion interactions a year across 60+ countries.

Routing, compliance, fraud prevention handled automatically rather than manually managed by the business sending the message!

Sinch is the reliability layer underneath AI-driven customer communications; the infrastructure that determines whether an AI agent's output actually reaches a real person as a delivered text, connected call, or verified interaction.

Check it out here!

SHOW NOTES:

• The current focus @ Github & what scaling looks like (1:21)
• Signals that previous scaling methods are no longer viable (3:00)
• Migrating to Azure / impact on the engineering org (5:55)
• Strategies for orchestrating massive, widespread change across the org (7:28)
• How to control the scope while scaling / rebuilding (10:16)
• Ownership dependencies & potential rollback with Github’s service migration process (11:50)
• Embrace excitement when it comes to prioritization, scaling, & problem solving (14:15)
• Addressing capacity & configuration challenges earlier on (16:49)
• Github’s “new norm” for processes / organization (18:23)
• How to address legitimate vs. illegitimate traffic (21:02)
• Keeping up with rapidly changing technology / AI advances (21:31)
• Github’s method for tackling the context layer of its AI toolage (27:14)
• Where Github is on the AI adoption curve (29:30)
• Navigating the transition from individual AI adoption to team-level transformation (31:36)
• An example of team-level AI adoption @ Github (33:39)
• Jakub’s advice to eng leaders on building infrastructure teams / investing in people (34:36)
• How platform leaders can improve their cross-functional change making ability (38:39)
• Reducing complexity for platform teams to improve ability to scale (40:42)
• An example of a successful transformative moment @ Github (42:34)
• Rapid fire questions (46:28)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Benny Chen, Co-Founder @ Fireworks AI, joins the show to discuss his founder journey and share valuable insights on navigating common founder / product dev challenges in today’s agent-first landscape. He and Jerry cover strategies for creating effective messaging, staying competitive in a crowded market space, hiring top-tier talent / what qualities to look for in high-performing engineers, navigating the cultural shift to managing agents, creating data flywheels & how this can help your customers, and more.

ABOUT BENNY CHEN

As co-founder and early product architect, Benny Chen shaped Fireworks AI’s infrastructure strategy, spearheading the design of scalable systems to support high-throughput AI model serving. Benny’s contributions established the technical foundation for Fireworks AI’s robust and cloud-native architecture, which underpins its ability to meet enterprise demands.

Formerly Meta’s Ads Infrastructure Lead, Benny optimized large-scale ad-serving pipelines and developed significant expertise in distributed systems and cloud infrastructure. He holds a B.S. in Computer Science from Stanford University, bringing both leadership and technical depth to the Fireworks AI management team.

Sinch is the communications infrastructure the AI era runs on.

There's a layer of infrastructure behind every text, call, and login code your product sends, and it works exactly like plumbing: nobody thinks about it until it's the reason something broke.

Most providers route through 4-6 intermediaries; Sinch connects in 1-2 hops, direct carrier relationships across 600+ connections, handling 900 billion interactions a year across 60+ countries.

Routing, compliance, fraud prevention handled automatically rather than manually managed by the business sending the message!

Sinch is the reliability layer underneath AI-driven customer communications; the infrastructure that determines whether an AI agent's output actually reaches a real person as a delivered text, connected call, or verified interaction.

Check it out here!

SHOW NOTES:

• Moving from an early idea to a rocket ship (1:13)
• Insights on developing / communicating your core message as an early founder (2:40)
• Role of open source & inference @ Fireworks AI (4:24)
• How Firework AI’s company messaging evolved over time (6:07)
• Popular customization features today (7:25)
• Strategies for staying competitive in a crowded market (9:11)
• Defining the customer data flywheel & how it helps users (11:25)
• Common types of data that companies can collect to train their AI models (13:53)
• The customer’s next steps after creating a data flywheel (15:53)
• Benny’s perspective on acquiring engineering talent as a founder (16:43)
• Common traits shared by high-performing engineers @ Fireworks (19:05)
• How AI has altered which traits founders prioritize when hiring (20:45)
• Navigating the shift from engineering work to managing agents (22:40)
• Frameworks to ensure agents are doing the right thing (25:23)
• Aligning your metrics with the outcome you’re trying to follow (27:37)
• What a typical day looks like for Benny as a founder (28:31)
• Advice for founders / eng leaders looking to embrace AI adoption (29:19)
• Rapid fire questions (31:15)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Pooja Brown (Founder @ http://inventry.ai/) shares her insights on balancing being a founder & technologist, especially within the mid-market manufacturing industry. We cover why founders need to lead with curiosity as they seek out customer problems to solve, strategies for solving complex problems related to supply chain, and strategies for selling your products. Pooja also dissects important fundraising tactics, how to identify areas that AI tooling can enhance within your business, reading customer signals, and bolstering your engineering skills by leveling up business capabilities.

ABOUT POOJA BROWN

Pooja Brown is a technology executive and founder focused on building AI-native platforms that power real-world operations across industries. She has led engineering at scale at companies like Stitch Fix and DocuSign, building systems that combine data, workflows, and machine learning to drive everything from personalization and supply chain to digital agreements used by hundreds of thousands of businesses.Her experience spans multiple verticals including retail, enterprise SaaS, education technology, and real estate, where she has consistently focused on embedding AI directly into core business systems rather than layering it on top.

Pooja is currently the founder and CEO of http://Inventry.ai, where she is building autonomous AI agents that help mid-market manufacturers run procurement and supply chain operations more effectively. Across her career, she has focused on turning complex operational data into systems that don’t just generate insights, but actually drive decisions and execution.

Sinch is the communications infrastructure the AI era runs on.

There's a layer of infrastructure behind every text, call, and login code your product sends, and it works exactly like plumbing: nobody thinks about it until it's the reason something broke.

Most providers route through 4-6 intermediaries; Sinch connects in 1-2 hops, direct carrier relationships across 600+ connections, handling 900 billion interactions a year across 60+ countries.

Routing, compliance, fraud prevention handled automatically rather than manually managed by the business sending the message!

Sinch is the reliability layer underneath AI-driven customer communications; the infrastructure that determines whether an AI agent's output actually reaches a real person as a delivered text, connected call, or verified interaction.

Check it out here!

SHOW NOTES:

• What shaped Pooja’s entrepreneurship journey & background (3:20)
• Looking for the right problem & leading with curiosity (6:47)
• Insights on solving problems related to supply chain (10:42)
• Building systems for chaos / complexity (12:46)
• Adopting a beginner’s mindset when solving complex problems (15:40)
• Dissecting fundraising strategies & decision making (19:28)
• Emerging business patterns that eng leaders need to capitalize on (26:32)
• Understanding how customers make decisions on what products to adopt (29:09)
• Selling strategies for the mid-market manufacturing industry (37:08)
• Integrating AI tools to augment current business capabilities (41:03)
• Engineering skills that enhance sales processes (44:43)
• Communication frameworks when working with customers (47:21)
• Rapid fire questions (50:06)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Sergiy Nesterenko (CEO @ Quilter) joins the pod to share how he turned a personal technical challenge into his own company, even before the market caught up. He shares his unique journey from SpaceX to Quilter and addresses common eng leader / founder challenges, including taking critical feedback to solve tough technical problems, knowing when your most important role is educating the market / customers, and choosing the right customers. Sergiy and Jerry also dissect insights into principles around building circuit boards, and common misconceptions around hiring top-tier talent, finding investors, and procuring customers as an early-stage company.

ABOUTSERGIY NESTERENKO

Sergiy Nesterenko is the Founder and CEO of Quilter, the first physics-driven AI platform that fully automates PCB layout design. Under his leadership, Quilter has pioneered autonomous board design – creating the missing automation layer for hardware and compressing weeks-long layout cycles into hours. Backed by Index, Benchmark, Coatue, and Tony Fadell, Quilter is redefining what's possible in hardware development. Previously, Sergiy spent five years at SpaceX as a Senior Radiation Effects Engineer, building electronics for the Falcon 9 and Falcon Heavy.

SHOW NOTES:

• Introducing Sergiy Nesterenko & the inspiration behind Quilter (1:43)
• Why now is the right time to tackle this technical challenge (3:37)
• The technology landscape during Quilter’s early days (6:05)
• Sergiy’s fundraising journey & key takeaways (8:26)
• The importance of adopting an evolutionary mindset (10:52)
• Early problems that Quilter aimed to solve (13:08)
• Navigating the balance between technical problems & consumer readiness (15:59)
• How negative feedback can lead to solving a key problem (18:34)
• Knowing which feedback to incorporate into product iterations (20:08)
• Lessons learned from choosing the wrong customers (27:33)
• First principles approach to circuit board building (29:31)
• Signals that it’s the right time to tackle a hard technical challenge (34:04)
• Advantages to solving really hard problems & tackling entrepreneurship (36:32)
• Common misconceptions surrounding early phase companies (38:17)
• Sergiy’s experience working with Eric @ Benchmark (39:46)
• Why investors like founders who spend time in the “idea maze” (42:19)
• Strategies for convincing high-profile talent to join your org early on (43:22)
• Rapid fire questions (45:10)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Tomas Reimers, Co-Founder & CPO @ Graphite, reveals his journey to becoming a founder and some of the major moments from Graphite’s product development story. He dissects frameworks for determining when it’s time to quit your full-time job to pursue becoming a founder and analyzing the costs vs. benefits of that decision. We cover how to decide what customer problems to solve, understanding how software development trends impact what you’re building, and product market fit and selling considerations. Lastly, Tomas shares valuable strategies when it comes to selling to developers.

ABOUT TOMAS REIMERS

Tomas Reimers is the CPO and co-founder of Graphite, the a16z and Anthropic-backed AI code review platform that Cursor acquired in December 2025. Previously, he was an engineer at Facebook. Passionate about advancing developer velocity, Tomas holds a BS in Computer Science from Harvard University.

SHOW NOTES:

• The origin story behind Graphite (1:05)
• Signs that it’s time to quit your job / found a company (4:03)
• How Tomas & his co-founders knew it was time to break up with their jobs (5:40)
• Understand what leaving your job will mean career-growth wise (7:33)
• Embracing regret minimization (9:28)
• Pros & cons of developing in blue ocean vs. red ocean areas as a founder (11:49)
• Strategies for determining what software to build / how is software dev evolving (14:00)
• Tomas’s framework for determining bets (15:50)
• Recommendations for selling as a founder (17:52)
• Identifying if sales isn’t working or if product market fit is off (20:35)
• Using customer insights to experiment & make a PMF pivot (23:05)
• Why developers don’t want to be sold to, they want to be taught (24:42)
• How to apply teaching vs. selling into early GTM strategy (27:20)
• Utilizing demonstrations to gain developer buy in & trust (29:24)
• What Tomas is looking forward to in Graphite’s future / software dev in general (32:04)
• Rapid fire questions (33:34)

LINKS AND RESOURCES

• The Mom Test - Rob Fitzpatrick’s quick, practical guide that will save you time, money, and heartbreak.
• Founding Sales - The Startup Sales Handbook - rhe distillation of Pete Kazanjy’s experience at his first software startup, TalentBin going from a founder with a product marketing and product management background to early sales guy, early sales manager, and eventual post-acquisition sales leader at Monster Worldwide in addition to his later experience founding Modern Sales, the nation’s largest sales operations, enablement, and leadership community.
• Thinking in Bets: Making Smarter Decisions When You Don't Have All the Facts - Annie Duke, a former World Series of Poker champion turned business consultant, draws on examples from business, sports, politics, and (of course) poker to share tools anyone can use to embrace uncertainty and make better decisions.

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Vivek Raghunathan, SVP of Engineering @ Snowflake, joins the Engineering Leadership Community Podcast to discuss all things AI – most importantly, how Snowflake is utilizing AI internally to iterate faster with smaller, focused teams. Vivek shares how AI and lower coding costs ultimately help Snowflake implement tighter feedback loops between customer & eng teams to speed up product development rollout and how Snowflake empowers their orgs to upskill when it comes to AI. Jerry & Vivek also break down what quality leadership looks like across the board and the role of AI in shaping today’s eng leaders.

ABOUT VIVEK RAGHUNATHAN

Vivek Raghunathan is Snowflake's SVP of Engineering. Before joining Snowflake, Vivek co-founded Neeva, one of the first AI-native search engines for consumers, which was acquired by Snowflake in 2023. Prior to that, he spent more than a decade at Google, where he led YouTube monetization and helped launch Google Now.

ABOUT SNOWFLAKE

Snowflake is the data and AI platform that many of the world's largest organizations rely on to power their most critical operations. Whether a bank is approving a loan, a retailer is optimizing its supply chain, or a hospital is bringing together patient data, Snowflake helps organizations unify data, apply AI, and make faster, more informed decisions. Today, over 13,900 companies rely on Snowflake to turn their data into business value, with enterprise-grade security, governance, and scale built-in.

SHOW NOTES:

• Where Snowflake is on their AI adoption journey (0:57)
• Using AI to help eng orgs meet maximum velocity (3:04)
• Defining traits of engineers who successfully leverage agentic tools (5:55)
• The benefit of cross collaborative skillsets for eng leaders (8:53)
• How AI is helping orgs test infrastructure rewrites effectively & less expensively (10:09)
• Discovering AI patterns @ Snowflake (11:44)
• Why Snowflake gives teams a week off to learn the necessary AI tools (16:37)
• Compressing the product dev cycle with the help of AI (18:28)
• Simplify eng teams / encourage fluidity of roles (19:49)
• Vivek’s perspective on leveraging AI to best support customer needs (22:45)
• Building control planes to support enterprises (24:30)
• Methods for consolidating data / making it accessible to the entire org (27:18)
• How AI shapes what a quality leader looks like (30:39)
• The role of empathy in leadership (33:49)
• Rapid fire questions (35:08)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Russ d’Sa (CEO & Co-founder @ LiveKit) joins the show to deconstruct the "Product Paradigm Shift" toward voice-driven interfaces and agent-centric UX . We dive into LiveKit’s high-stakes scaling lessons: from powering OpenAI and Character AI’s voice mode, how they navigated real time bottlenecks to hit the next level of scale, the architectural necessity of a multi-cloud strategy, and the foundations of a co-founder relationships that can effectively blend engineering & business strategy.

ABOUT RUSS D’SA

Russ is a startup vet who founded his first company in the 2007 YC batch and was the 2nd frontend engineer hired at Twitter, Russ d'Sa now leads voice AI unicorn LiveKit. They're the backbone of ChatGPT Voice Mode, Salesforce Agentforce, Grok, and roughly 30% of US 911 calls.

ABOUT LIVEKIT

LiveKit is an open source framework and cloud platform for building voice, video, and physical AI agents. It provides the tools you need to build agents that interact with users in realtime over audio, video, and data streams. Agents run on the LiveKit server, which supplies the low-latency infrastructure (including transport, routing, synchronization, and session management) built on a production-grade WebRTC stack. This architecture enables reliable and performant agent workloads.

SHOW NOTES:

• The product paradigm shift toward voice-driven apps and natural human-computer interfaces (2:44)
• Voice-apps in practice: How these trends impact the strategy of product building today (5:32)
• Early adopters: Why legacy industries like healthcare use voice AI (7:55)
• Reevaluating and building product experiences optimized for AI agents (12:52)
• How AI trends will impact roadmaps and Go To Market (18:16)
• The origin of LiveKit: Building real-time infra for the pandemic (21:07)
• The OpenAI moment: Powering the fastest-growing consumer app (23:48)
• Scaling with OpenAI: Navigating the challenges of balancing time-to-market with system design (25:39)
• The Character AI outage: Solving cross-continental state sync and hitting the next level of scale (29:00)
• The problem: When telemetry breaks first: Managing analytics and logging for millions of concurrent AI sessions (32:04)
• Architecting for resilience: Multi-cloud from day one and why treating infra as a utility matters (33:22)
• Co-founder dynamics: Blending engineering strategy with business outcomes (37:15)
• Rapid Fire Questions (40:51)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Patrick discusses what it means to build an empowered career & explore creative career portfolios with Jean Hsu (VP of Engineering @ Range) and Cate Huston (author of The Engineering Leader and fractional CTO @ Twill). Both share their unique engineering leadership journeys & how they built creative career paths through exploration & finding room for optionality. We dissect the identity crisis that eng leaders face – whether they are ICs or managers – and how to navigate the tension between individual & team productivity, especially taking into consideration AI. Lastly, Jean and Cate share insights on letting go of societal norms, unique ways to expand your work, taking on bets, and incorporating your values into your career.

ABOUT JEAN HSU

Jean is a builder, writer, coach, and fractional VPE at Circuit & Chisel. She was previously in leadership roles at Pulse, Medium, and Range, and also built out a leadership development company focused on engineers. She lives in Berkeley with her partner and three kids.

ABOUT CATE HUSTON

Cate is the author of The Engineering Leader, fractional CTO at Twill, and engineering leadership coach. She was previously in leadership roles at DuckDuckGo and Automattic, and an advisor at Glowforge. She has been all over the world, but now lives in Ireland.

Check out DRI Your Career today and use promo code “ELCPODCAST” for 15% off any of Cate and Jean’s three courses!

SHOW NOTES:

• What it means for creative career paths to become the norm (1:42)
• Navigating the tension between individual vs. team productivity (3:34)
• What an empowered career looked like in Jean’s leadership journey (5:00)
• Cate’s decision to craft her own career narrative (10:46)
• Redefining work-life balance (12:54)
• How to cultivate time to explore future projects & create room for optionality (15:59)
• Why it can be challenging to find the space / time to experiment (19:17)
• Let go of “societal shoulds” (23:37)
• Frameworks for building out your career portfolio (28:43)
• Unique ways to expand the type of work you can perform (30:23)
• Using AI tools to help orient your career & incorporate your values (34:35)
• Thinking about your career portfolio as bets (40:14)
• Final thoughts on what it means to build an empowered career (44:47)
• Rapid fire questions (46:13)

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

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); http://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.

http://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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

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.

http://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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

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.

http://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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

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.

http://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 https://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 http://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 http://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.

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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 http://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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

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 https://pcm.adswizz.com for information about our collection and use of personal data for advertising.