ELC Annual 2023

When building digital products and enhancing user experiences through AI, gathering user feedback is crucial. However, traditional methods such as surveys often aren’t enough to generate explicit feedback. In this session, Amplitude's Shadi Rostami and Dusty Pierce will explore the important role that user behavior tools play in effectively capturing user feedback and improving AI models. The audience will walk away with an understanding of the challenges associated with gathering user feedback, how user behavior data can better inform our AI models, and how organizational shifts can also be an effective tool in orienting a company around CX. In this fireside conversation, Shadi and Dusty can also share practical insights and strategies for integrating user behavior tools into the development process.

Generative AI is the "it" productivity tool of the moment, but we're still at the very early stages of incorporating it into everyday workflows. In this session, Shailesh Kumar, SVP of Engineering at ClickUp, and Kelly Ehret, Latitude, will contemplate how engineering teams can take advantage of the "Era of AI" and use it to optimize and accelerate their work. Specifically, Shailesh can share his own experience as an engineering lead at ClickUp, offering anecdotes and advice on how generative AI has helped his team work more collaboratively across departments. He will also share his perspective on encouraging more AI adoption across teams and how to measure success. Listeners will walk away from this session with a tactical understanding of how to motivate engineers to use AI in their day-to-day to achieve meaningful productivity gains.

Scaling beyond early market fit presents unique challenges - Where’s the highest leverage? How do you build things that scale & avoid getting stuck with 1000+ MVPs? How do you manage increasing orders of complexity in your teams and product? Where are the greatest opportunities for real vs. perceived velocity? In this session, Marck Robinson, VP of Engineering @ Brex, will unpack strategies for sustaining velocity and efficiency, offering a roadmap to fuel your organization's journey to enterprise scale. Marck shares actionable insights from his experiences operating at massive scale at places like Microsoft Azure, New Relic, and now, Brex.

The GenAI WAVE will dramatically alter organizational structures, your customers, the market, your team's roles and needs, and yours. Waiting to “see how it plays out” is simply not an option for leaders and companies that want to survive it. Why not lead it? Join Andrew Lau (not ChatGPT) as he discusses the evolving roles of engineering as the toolsets change, the changing demands of the engineering function as the industry leverages GenAI, case study on how CoPilot truly impacts an engineering team's productivity, the shifts in leadership requirements and skill sets from hiring to the boardroom, how to use experimentation and empirical data to learn what works for your org and what doesn’t, and why it’s more important than ever to highlight and protect innovation. Transformative technology will continue to change the world, but supporting it with empirical data is essential. And even more importantly, this is all happening right now; if you aren’t paying attention, you must.

Generative AI is changing the way we work and will disrupt most industries. This means that technology leaders need to be prepared for change and develop new skills and competencies in order to lead their organizations through (and beyond) this disruption. In this session, I will discuss what the likely changes are, what new requirements leaders will have, and how you can start developing the competencies you need to lead in this next generation of technology leaders.

The generative AI moment is turning traditional software development on its head, and coding as we know it today may look as obsolete as punch cards in a few short years. This session is an invitation to wild speculation: what will the work of software engineering and software project management look like in 10 or 20 years? This panel brings together seasoned technology practitioners who’ve weathered past paradigm shifts in the industry. They’ll explore other questions like: How, and how long, will humans be in the coding / testing / debugging loop? What will be the core skills for building technology (and managing technologists? What should a college freshman study next year if they aspire to be a software engineer? Will there ever be a new programming language again?

As the technical workforce becomes more diverse, managers and leaders are challenged to integrate junior engineers of different backgrounds and varying levels of technical knowledge and practical experience. It is important for engineering leaders to understand how to integrate and cultivate talent from such groups to build more cohesive and better-performing teams. Reprogramming higher education to create the most diverse generation of engineers, CTOs, and founders, CodePath partners with leading companies such as Amazon, Bloomberg, Capital One, Meta, Salesforce, and more, to expand their talent pipelines with industry-ready and diverse tech talent. Leaning on the expertise and experience of our engineering leadership partners, this fireside chat will provide engineering managers and team leads with the knowledge and real-world examples necessary to build internal cultures that allow junior engineers to hit the ground running and translate technical knowledge into practical experience. Attendees will walk away with actionable strategies and examples to help team leads build, retain, and cultivate diverse, early career talent to maximize team productivity.

In this session, you’ll learn how to save 95% of your time on test automation by leveraging breakthroughs in Generative AI and move 90%-100% of the work to the product management organization. We’ll cover how to improve SDLC to allow you to move up to 30% faster with up to 90% less bugs in production, and how Generative AI can be helpful to eliminate 98% of the effort on maintaining end-to-end tests.