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”!

Rajeev 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.

• 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)

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/5

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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.

Daniel 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.

• 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)

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/

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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 and then translate that understanding back to us in human terms.

Jaime 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.

Rashi 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.

• Archetype AI’s mission: Building a foundation model for physical reality (0:24)
• The potential for discovery: Using AI to observe phenomena humans cannot perceive (1:36)
• Augmentation vs. Replacement: Giving humans "superpowers" rather than automating them away (2:48)
• The "Perfect Storm" for Physical AI: Transformers, self-supervised learning, and commodity sensors (4:04)
• Defining “Non-Human Intelligence” and removing the constraints of human labels (6:34)
• Why language is inherently lossy and insufficient for true physical understanding (8:28)
• Real-world application: How Physical AI aids safety decision-making in the solar industry (9:35)
• Use case: Improving pedestrian safety and traffic signaling in Bellevue (12:51)
• The biggest engineering leadership challenge: Embracing the “messiness” of real-world data (14:21)
• Q&A: Why we shouldn't teach AI physical laws, but let it discover them (16:50)
• Q&A: Validating models when there is a defined ground truth vs. subjective language (18:49)
• Q&A: Compute requirements and the future of active learning at the edge (20:05)

• Video version of Jaime and Rashi’s session at ELC Annual 2025

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.