Every session, keynote, and workshop slot — sorted by day so you can plan your path through the conference.
1-1s are ubiquitous in the software engineering industry, and great leaders cherish these discussions.
What makes 1-1s so valuable?
1-1s are just like any other meeting - they are used to exchange data - be it tactical project updates, personal updates, or perspectives on how a project is going. There is also implicit data exchanged, signals that are interwoven with each word that is spoken. These are our emotions.
Emotions can be felt and observed but can be difficult to interpret and process. Our brains are in overdrive when communicating with other humans as we take in these implicit signals along with the literal words being spoken. During 1-1s, this can intensify as our focus is entirely on the other person; What signals are they sending? How will I respond? What isn’t being said here?
Emotional intelligence is the ability to identify, understand, and manage our emotions to communicate more effectively with others. In this interactive discussion, we will explore how to leverage the four emotional intelligence skills to facilitate more productive and enjoyable 1-1s.
In the ever-evolving landscape of software engineering, the success of a team is not solely determined by the mastery of coding languages or the ability to develop cutting-edge solutions. It also hinges on the presence of an often underestimated yet essential element: psychological safety.
Psychological safety, as coined by Harvard Business School professor Amy Edmondson, refers to an environment where team members feel comfortable taking risks, sharing ideas, and making mistakes without fear of ridicule or retribution. In the context of software engineering, fostering such an environment can significantly impact team dynamics, productivity, and innovation.
This talk explores the various dimensions of psychological safety within dev teams, emphasizing its role in:
Drawing on real-world examples and practical strategies, attendees will leave with a deeper understanding of the pivotal role psychological safety plays in software development and the tools to transform their teams into resilient, innovative, and cohesive units.
Imposter Syndrome, a pervasive phenomenon affecting individuals across various industries, holds a particularly potent grip within the realm of software engineering. It is characterized by persistent self-doubt and a belief that one's accomplishments are mere flukes, is alarmingly common in the technical engineering community.
This 60 minute talk delves into the profound impact of Imposter Syndrome on software engineering teams, exploring its origins, manifestations, and strategies for fostering healthier, more productive work environment.
We are knowledge workers and ultimately, we must own our growth and learning. Personal Knowledge Management is a process of collecting information that one uses to gather, classify, store, search, retrieve and share knowledge in their daily activities and the way in which these processes support work activities.
Despite taking notes, bookmarking web content, and highlighting passages in books; often we struggle to recall or rediscover these many insights we pick up daily in our work and life. This session introduces a tool and some process recommendations to never again lose discoveries and knowledge resources.
Michael shares the tools and workflow he (and many on the NFJS tour) use to write, organize and share your thoughts, keep your todo list, and build your own digital garden. These approaches naturally connects what you know the same way your brain does, and makes it easier to make everything you learn actionable and always at your fingertips.
You'll learn the basics, tips and tricks, and recommendations of these tools and practices; and leave armed to deploy these right away as you continue learning at the conference!
Software projects can be difficult to manage. Managing teams of developers can be even difficult. We've created countless processes, methodologies, and practices but the underlying problems remain the same.
This session is full of practical tips and tricks to deal with the reallife situations any tech leader regularly encounters. Put these techniques into practice and create an enviable culture and an outstanding development team. At the same time, you'll avoid common management mistakes and pitfalls.
You were promoted for your expertise. And that’s exactly what’s holding you back.
Many technical leaders struggle to shift from “doing the work” to “leading the work.” Letting go is hard. Worse? It’s not enough.
This session reveals why stepping back doesn’t work—and what it really means to step up as a leader.
Key Takeaways:
Great leadership doesn’t abandon expertise—it evolves it.
Influence is the currency of leadership—but most leaders only spend what they’ve been given.
This session helps technical leaders break out of default power (positional, cultural, prestige) and tap into personal power—built on presence, clarity, and credibility.
Whether you’re managing up, across, or leading without formal authority, this talk gives you the tools to lead with more impact.
We’ll Explore:
The best leaders don’t use power to control. They use it to connect.
Everyone’s talking about AI’s potential. Few are asking the harder question: What exactly is it multiplying?
This session explores how Generative AI is accelerating everything—good and bad—and the hidden risks for leaders who aren’t paying attention. Drawing from the AI Leadership Lab and decades of riding tech waves (software, mobile, cloud, agile…), Pete will challenge you to rethink your AI strategy—from productivity to power, design to decision-making.
You’ll walk away with:
If AI is fuel, leadership is the steering wheel.
Technical leaders are problem-solvers by design. But not everything is a problem that can be solved. Some challenges—like speed vs. quality, alignment vs. autonomy, planning vs. adapting—aren’t meant to be solved. They’re tensions that can only be managed. And treating them like problems only creates new ones.
This session unpacks the most common leadership tensions in tech and how to navigate them with more clarity and less frustration.
You’ll explore:
No perfect answers. Just better choices.
Some aim for leadership positions, team lead, manager, director, VP, and so on whereas others slide into that position due to the opportunities that arise. Many grow into those positions from a strong technical background as opposed to formal training to be a manager. Join Venkat and learn how you can be a more effective technical manager?
We will look at some characteristics that can help us to better meet the needs of the organizations and help the team perform at its peak, to deliver good results.
It has been said that everything rises and falls on leadership and that there are no bad teams, only bad leaders. As you serve your team as their manager and leader, one of the most critical decisions for you to make is what kind of leader you will be.
In this session, we will focus on one of the keys to good leadership; how you manage yourself. From cultivating healthy personal routines to developing a culture of feedback, during this session we will explore some best practices in self-leadership that will help you bring your very best to the team you serve.
Self managed teams are a nice concept and has values to certain extent. However, a team that lacks having technical leadership can drift along as time goes on and especially when a number of hard decisions have to be made.
In this presentation we will discuss the role of technical leaders, their responsibilities, and how they can be effective in leading a bunch of highly skilled, opinionated technical people.
As leaders we want our teams to pursue great ideas and change directions to realize the goals. However, often we find it hard to implement changes. At times there seems to be resistance or at least reluctance to change. Why can't the team see the benefits of where we're headed and move fast to realize the goals?
Let's step back to look at the challenges of effecting change and how we can lead teams towards successful transition.
Are you drowning in data, but it's not helping you decide what to do? Maybe you wonder how to make better decisions faster.
Flow metrics are your evidence of what occurs at every level in the organization. Even better, unlike relative estimation or any other predictive form of estimation, you can use flow metrics and Monte Carlo simulation for much better prediction.
Learn how to start with flow metrics. Then take that learning to ask questions to create a more effective organization at all levels.
Before the pandemic, “everyone” said, “Agile approaches don't work for distributed teams!” Then came the pandemic and everyone figured it out—more or less.
However, now, many teams work in ways they call “hybrid.” Those are the most challenging forms for any distributed team: the satellite team or the cluster team. When those teams assume that they can work as if they were all collocated, the teams tend to lose their agility.
Instead, teams can use the eight principles for successful distributed agile teams and optimize for those principles, instead of location. The eight principles are:
● Establish acceptable hours of overlap.
● Create transparency at all levels.
● Create a culture of continuous improvement with experiments.
● Practice pervasive communication at all levels.
● Create a project rhythm.
● Assume good intention.
● Create a culture of resilience.
● Default to collaborative work.
In this presentation, Johanna will address just four of the principles—the ones that focus on and enable collaboration—to help you create the best environment for your distributed agile team.
Regardless of your place in the organization, you often need to convince others to spend money or time on a necessary effort. Sometimes, those proposals succeed. But too often, they don’t—and the organization suffers.
Instead, you can learn the secrets of successful consulting proposals. Those secrets include:
Don’t waste your time trying to calculate an incalculable number, such as ROI. Instead, become an internal consultant to help convince your management to fund the tools, training, or work, you need to succeed.
Ever wonder how to transform your engineering organization’s strategy but feel overwhelmed by abstract concepts and myriad ideas? In this talk, we'll navigate through practical implementations, starting simply and scaling according to team demands.
As your discipline matures, the dynamics shift. We'll move towards more structured strategies, emphasizing accountability and ensuring that an expanding team remains aligned with the organization’s goals. Transitioning from basic processes to a complex system introduces a range of challenges and opportunities. We'll address maintaining a clear direction, cultivating leadership within, and facilitating seamless collaboration across multiple teams.
This talk is designed for leaders and managers positioned to shape engineering strategy, as well as those curious about what lies ahead. You'll gain a suite of strategies to sustain your team’s growth effectively and keep your department innovative and agile, regardless of size. Whether you're at the beginning of expansion or seeking new methods to refine your approach, this session offers insights and practical tips to support your team’s success through every growth stage.
Organizations increasingly see their aging technology and data architecture as a liability, at odds with their desired outcomes of engaging customer experiences, fast delivery speed and operational efficiency. So, how are organizations modernizing their legacy architecture and transforming it into a competitive advantage? What role is strategic Domain-Driven Design (DDD) playing in this transformation and how can it help organizations like yours?
In this talk, Ryan shares why architecture modernization is critical for today’s organizations and then shows real-life before / after designs from organizations using DDD to modernize their applications, data warehouses and cloud infrastructure. Ryan highlights the key DDD concepts used in modernization and explains how to get started a Domain-Driven Discovery approach. This talk is for all tech leaders interested in seeing real-life examples of how to modernize architecture using DDD and turn a liability into a competitive advantage.
Have you encountered particularly stubborn problems at work? You think you “fixed” or “solved” it, but the problem rears its ugly head again. Worse, maybe you have no idea how to solve it. That’s when you know you’re dealing with a complex adaptive system. Too often, those kinds of systems reinforce themselves to continue to get these results. The problem seems unfixable or unsolvable.
However, you can add more critical thinking skills to your toolbox. Those skills can help you clarify the underlying issues and help you solve them.
This workshop is about seeing the kinds of issues that allow or prevent change, starting with what you know and do not (or cannot) know about the situation:
After I introduce these ideas, you will test your problem with Cynefin. Then, you'll break into teams to practice Force Field Analysis. After a half-hour of practice, we will debrief and discuss any remaining questions.
Bring at least one specific organizational problem so you can practice. (Make sure your problem is “big” enough for you to learn from.)
Transitioning from an individual contributor to a technical leader requires more than just technical expertise—it demands a new set of leadership skills, strategic thinking, and the ability to empower a team. This half day interactive workshop is designed to help new and aspiring technical leaders build a strong foundation in technical leadership.
We’ll start with the basics: What do Engineering Managers actually do? From there, we’ll explore the principles of purposeful leadership, time management, and prioritization to help leaders stay focused on what truly matters. Participants will learn how to empower their teams, build a strong team vision, and navigate career conversations, coaching, and effective 1:1s to support their team’s growth.
The workshop will also cover strategic leadership and relationship-building, providing insights into how to balance technical execution with long-term planning and cross-functional collaboration. Through interactive exercises, real-world scenarios, and group discussions, attendees will leave with practical frameworks and tools they can immediately apply to their teams.
Whether you’re stepping into leadership for the first time or looking to refine your approach, this workshop will give you the skills and confidence to lead effectively in a fast-paced technical environment.
Download (and print if preferred) attached handout doc located in Slides folder.
Join Pat Cullen for an insightful session where he shares a decade of lessons from the front lines of engineering leadership. In “Mistakes Made, Lessons Learned,” Pat delves into the pivotal moments and epiphanies that shaped his leadership style and team dynamics. Learn from his experiences with team challenges and how strategic communication and empathy turned potential setbacks into progress. Pat addresses common pitfalls, such as the shiny object syndrome, with practical strategies to maintain focus and drive consistent results. Through stories of time boxing, you'll gain actionable strategies to manage your projects more effectively.
This talk invites current and aspiring leaders to reflect, adapt, and thrive in the ever-evolving tech landscape. Gain valuable perspectives that will invigorate your leadership approach and enhance your ability to lead successful teams.
Everyone knows security is important. Very few organizations have a robust and comprehensive sense of whose responsibility it is, however. The consequence is that they have ducttapped systems and a Policy of Hope that there will be no issues. (Spoiler: there will be)
We will review the various roles that most organizations need to fill and probably are currently not doing so. We will also focus on how the roles overlap and what should and can be expected from each of them.
Come gain insight on how an organization can start with what you have and move in the direction of strengthened security postures with tangible and practical guidance. You will find both direction and means of measurement to make sure you neither over nor undershoot what is is required.
Somewhere between the positions of “AI is going to change everything” and “AI is currently an overhyped means of propping up silicon valley unicorn valuations” lives a useful reality: AI research is producing tools that can be exploited safely, meaningfully, and responsibly. They can save you money, speed up delivery, and create
new opportunities that might not otherwise exist. The trick is understanding what they can do well and what is a big, red flag.
In this talk I will lay out a framework for considering a range of technologies that fall under the umbrella of AI and highlight the costs, benefits, and risks to help you make better choices about what to pursue and what to avoid.
As AI accelerates the pace of coding, organizations will have a hard time keeping up; acceleration isn't useful if it's driving our projects straight into a brick wall of technical debt. This presentation explores the consequences of AI-assisted coding, weighing its potential to improve productivity against the risks of deteriorating code quality.
Adam delivers a fact-based examination of the short and long-term implications of using AI assistants in software development. Drawing from extensive research analyzing over 100,000 AI-driven refactorings in real-world codebases, we scrutinize the claims made by contemporary AI tools, demonstrating that increased coding speed does not necessarily equate to true productivity. Additionally, we also look at the correctness of AI generated code, a concern for many organizations today due to the error-prone nature of current AI tools.
Finally, the talk offers strategies for succeeding with AI-assisted coding. This includes introducing a set of automated guardrails that act as feedback loops, ensuring your codebase remains maintainable even after adopting AI-assisted coding.
Key insights include:
Novel Quality Metrics: Introduction and application of innovative metrics designed to act as guardrails, ensuring that AI contributions maintain high standards of code quality.
Balancing Speed and Quality: Strategies to leverage AI for increased efficiency while avoiding the pitfalls of technical debt.
Real-World Data: Fact-based presentation from comprehensive research on real-world codebases.
Prioritizing technical debt is a hard problem as modern systems might have millions of lines of code and multiple development teams — no one has a holistic overview. In addition, there's always a trade-off between improving existing code versus adding new features so we need to use our time wisely.
What if we could mine the collective intelligence of all contributing programmers and start making decisions based on information from how the organization actually works with the code?
In this workshop, you'll learn how easily obtained version-control data lets you uncover the behavior and patterns of the development organization. This language-neutral approach lets you prioritize the parts of your system that benefit the most from improvements so that you can balance short- and long-term goals guided by data.
In this session, you’ll learn:
To prioritize technical debt in large-scale systems
Balance the trade-off between improving existing code versus adding new features
Visualize long time trends in technical debt
Take a data-driven approach to technical debt.
During this workshop, you get access to CodeScene – a behavioral code analysis tool that automates the analyses – which we use for the practical exercises. We’ll do the exercises on real world codebases in Java, C#, JavaScript and more to discover real issues.
Participants are also encouraged to take this opportunity to analyze their own codebase to get actionable take-away information.
Code quality fails to gain traction at the business level, leading software companies to prioritize new features over maintaining a healthy codebase. This trade-off results in technical debt that consumes up to 40% of developers' time, causing stress, frustration, and costly delays in product delivery. Despite its importance, it's hard to build a business case for code quality: how do we quantify and communicate the benefits to non-technical stakeholders? Or even inside our own engineering team?
In this mini-keynote, Adam presents groundbreaking industry benchmarks and innovative metrics that, for the first time, enable organizations to compare their performance with top industry players. By leveraging statistical models, he demonstrates how you can predict the business gains of technical improvements in terms of increased development velocity and bug reduction. With these actionable recommendations, your organization can ship software faster and gain a competitive edge.
In today’s environment, the rapidly accelerating pace of artificial intelligence (AI) development has left many tech leaders feeling overwhelmed by both the potential benefits and the lurking risks. As the media often fuels misconceptions and sensationalism, navigating the real-world impact of AI on business strategy becomes challenging. You’re likely balancing two key priorities: seizing the opportunity to boost productivity and reduce costs, while ensuring your company avoids the kinds of embarrassing missteps that could end up splashed across the headlines.
Fortunately, you don’t need to be swayed by hype or fear. This full-day workshop will provide practical insights into the current state of AI, helping you make informed, strategic decisions about when and how to engage with these powerful technologies.
A Brief History of AI
Understanding AI’s evolution helps to put current developments in context, making it easier to discern hype from genuine innovation. We’ll cover how AI has developed over time and what key milestones have shaped the technologies we see today.
Generative AI
Generative AI has the potential to transform industries with its ability to create new content, from text and images to software code. We’ll explore how companies are leveraging generative models to boost creativity and efficiency, as well as the potential risks around intellectual property and ethical concerns.
Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG)
Learn about the latest developments in LLMs like GPT and how they are reshaping everything from customer support to internal knowledge management. We’ll also discuss Retrieval-Augmented Generation (RAG), a technique that combines the power of LLMs with specialized data retrieval systems to provide more accurate and relevant results.
Multi-Modal Systems
As AI systems evolve to process and generate content across multiple formats (text, images, audio, and video), we will look at how multi-modal AI is pushing the boundaries of what's possible and the opportunities and challenges it presents.
Bias, Costs, and Environmental Impacts
No discussion of AI is complete without addressing its ethical dimensions. We'll talk about algorithmic bias, the hidden costs of AI development (including financial and resource use), and the growing concerns around AI's environmental footprint. Understanding these trade-offs is crucial for tech leaders who want to make sustainable, ethical choices.
AI Reality Check: Separating Hype from Practical Applications
Finally, we will take a step back and conduct an AI reality check. What are AI’s genuine capabilities versus what is being exaggerated in media or sales pitches? How do you sift through the noise to make strategic decisions that add true value to your business?
no requirements
Software keeps moving—and so must we. From end-of-life frameworks to sprawling polyglot stacks and never-ending CVEs, modernizing code at scale is one of the toughest, most necessary problems in engineering today. In this keynote, we’ll take a clear-eyed look at where we are—and what it really takes to move forward.
We’ll unpack the rise of agentic AI, and why the future isn’t just about bigger models but better data and tools. Generative AI may be great at writing new code, but modernizing existing code? That takes precision—and deterministic systems that know when not to guess.
We’ll also dig into the language engineering problem: how do you unify modernization with codebases written in Java, C#, Python, JavaScript, and more? Each language needs a custom model that captures types, formatting, and structure for meaningful, accurate change at scale.
Finally, we’ll confront the security tradeoffs facing modern teams: should you upgrade fast to stay on the latest most secure versions, or leverage back patches to stay secure on what you know? The answer isn't always forward motion—it’s smarter, safer modernization.
We're helping teams navigate all of this with confidence at Moderne, providing AI-driven, multi-language refactoring and modernization at scale. After all, modern software demands more than speed—it demands the ability to evolve, safely and continuously, no matter how complex the codebase or how fast the industry moves.
Join us as we kick off Code Remix Summit—your front-row seat to the future of code.
Statistically speaking, you are most probably an innovator. Innovators actively seek out new ideas, technologies, and mental models by reading books, interacting with a broader social circle, and attending conferences. While you may leave this conference with the seed of an idea that has the potential to transform your teams, products, and organization; the battle has only begun. While, as a potential changeagent, you are ideally positioned to conceive of the powerful new ideas, you may be powerless to drive the change that leads to adoption. Your success requires the innovation to diffuse outward and become adopted. This is the art of Innovation.
Fortunately there has been over a century of study on the topic of how innovations go from novel idea to mainstream adoption. The art of innovation is difficult, but tractable and this session illuminates the path. You will get to the heart of why some innovations succeed while others fail as well as how to tip the scales in your favor. You'll leave armed with the tools to become a powerful change agent in your career and life and, ultimately, become a more powerful and influential person.
In tech teams it's a constant firefight. We react. Then we react to the reaction… the cycle continues. In all this noise, in all this chaos, how do we move forward. How do we remain proactive?
A great leader must be an enabler for the team. At times this means insulating the team from the noise. At other times it means improving the environment for the team. At all times, however, it requires setting clear priorities and conditions for success.
This session is focused on the art of moving forward in even the noisiest environments.
Whether you want to effect culture change in your organization, lead the transition toward a new technology, or simply get more out of your team; you must first understand that having a “good idea” is simply the beginning. An idea must be communicated; a case must be made. Communicating that case well is as important, if not more so, than the strength of the idea itself.
You will learn 6 principles to make an optimal case and dramatically increase the odds that the other person will say “Yes” to your requests and suggestions, along with several strategies to build consensus within your teams. As a professional mentalist, Michael has been a student of psychology, human behavior and the principles of influence for nearly two decades. There are universal principles of influence that are necessary to both understand and leverage if you want to be more effective leader of change in your organization.
Generative AI can be a powerful force multiplier for developers, but it also comes with limitations. Developers are expected to co-create with AI, and check the generated output, or risk hallucinations running wild. This can aid development at a local machine, but what happens when you try to apply these tools on a massive scale?
For mass-scale code operations, AI needs to have agency, able to operate with some degree of autonomy. In this session, we’ll cover how you can combine retrieval and tool calling techniques, the richest code data source for Java called the Lossless Semantic Tree (LST), and OpenRewrite rules-based recipes to drive more efficient and accurate AI model output for refactoring and analyzing large codebases.
You’ll learn about how you can use AI embeddings as a powerful tool to visualize, analyze, and even do smarter sampling for your codebase. Plus, we’ll show you how to leverage GenAI to accelerate writing OpenRewrite deterministic recipes.
We’ll take an honest look back and a look ahead on our process, to show you how enterprises can now reliably leverage AI for code modernization at scale.