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Surprise! Everyone at Your Company Suddenly Became a Developer (Kind Of)
Jason Meltzer
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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.
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.
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.
Are you blindly trusting your AI agents?
Organizations are pushing AI agents into production faster than they can properly secure, optimize, and govern them. Currently, most organizations have AI agents in some form of production use. Despite this rapid adoption, a glaring paradox has emerged: engineers report high confidence in their agent controls but the actual mechanisms in place lag significantly behind.
Join us for an exclusive look at Harness's upcoming research on AI adoption and controls. We recently surveyed 700 engineering leaders to reveal what is really happening behind the scenes of enterprise agentic AI adoption.
In this session, you will get the first look at key findings, including:
- The confidence gap: Why most engineers feel confident in production releases of agents despite few automated quality gates.
- The reality of incidents: How incidents are increasing as agents play a larger role.
- The path forward: We will discuss what leading organizations are prioritizing to safely scale agents.
# Webinar
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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.
Many organizations are exploring how AI can improve incident response, but turning a promising pilot into a reliable production workflow requires more than technology alone. Engineering leaders must identify the right use cases, integrate AI into existing processes, build trust with on call teams, and demonstrate measurable operational value.
Sponsored by Everbridge xMatters, this webinar will feature Sean Rousseau, Director of Product Management, who will explore how organizations can move beyond experimentation and apply AI to real incident response workflows without introducing unnecessary complexity or risk.
Discussion topics will include:
- Choosing the incident response use cases where AI can deliver the greatest value
- Moving from isolated pilots to reliable, repeatable production workflows
- Building trust and encouraging adoption among on call teams
- Measuring impact through response time, alert fatigue, responder workload, and operational efficiency
- Determining when to scale, adjust, or stop an AI initiative
# Roundtable
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In this episode, Pooja Brown (Founder @ 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.
Many engineering teams know their incident management processes need to evolve—but replacing everything at once isn’t realistic. In this session, we’ll explore practical ways to modernize your incident response without disrupting the tools and workflows your teams rely on today.
Join us as we discuss the warning signs that your current process is limiting growth, how to balance standardization with flexibility, and the first improvements successful engineering organizations make as they scale from startup operations to enterprise-grade resilience.
Discussion topics:
- Signs your incident process is holding you back
- Standardization vs. Flexibility
- Scaling from startup processes to enterprise operations
- What successful engineering orgs modernize first
# Roundtable
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