Explore what’s happening at LeadDev London

As engineering leaders, we need to move beyond the perception that technology is a back-office function, a support function, or a cost centre - and understand that technology is a leading function. As engineering leaders, we need to actively seek to lead the businesses that we’re a part of - and this is especially critical as we look to ensure the effective, safe and ethical adoption of GenAI.

To do this effectively, it’s also important that engineering expands its horizon - taking ownership of the impact of the products we create and not just the code that we create them with. As engineering leaders, we need to gain cross-disciplinary knowledge in areas like marketing, data, operations and finance to successfully lead and resolve key business challenges and identify transformational opportunities.

Across disciplines and time zones, the team worked through a series of complex challenges to deliver a pipeline to let 23 machines fill a 16k video wall. Live events work to very short deadlines, where a whole project can come together in a matter of days before the band walks on stage. In this environment, software issues can and do emerge at the eleventh hour and have to be carefully triaged, tracked and resolved with confidence. 

As the scope of customer requirements shifted and came into focus, the project expanded from a team with a single engineer and grew rapidly over three months. Members were split across two continents, stamping out bugs in overlapping shifts and shuttling information back and forth between in-house testing and on-site testing. 

Discussing both the managerial and technical challenges, this talk will go through what worked, what didn’t, and what lessons were learned for the next show - which was only six months later!

After a decade of boom, a lot of companies have been running layoffs, and headlines were dominated by CEOs talking about a need for “fewer managers”, “more efficiency”, and “more AI.” Throughout this time, many engineering leaders have been really busy turning a lot of these decisions into reality, while trying to make sense of these large and rapid changes beyond just headlines and anecdotes. Many leaders have been wondering what the industry shifts mean for them, asking questions like:

• How exactly have organizations and the shape of the tech industry changed? How have priorities shifted? 
• What role does AI play in organizations, how are they using it and where are they investing in it? 
• How have leaders’ roles and responsibilities changed, and how do other technical and people leaders spend their time now?
• And what does all of this mean for getting into engineering leadership and growing your career? 

I’m a VP Engineering and coach to engineering leaders, and, like you, I’ve been trying to get these answers—and now I’m sharing them with you: “The Engineering Leadership Report 2024”, produced in partnership with LeadDev and based on insight of over 1,100 engineering leaders. Join me for this talk to hear answers to these and more questions about the future of engineering leadership.

You’ll walk away with a clearer understanding of the shape of a changed industry, and the nuances in those changes, as well as concrete ideas for what you can do to navigate it successfully. During the office hours afterwards, co-producer Scott Carey, Editor in Chief at LeadDev, and I will be happy to answer your questions.

What if we could change that narrative? What if we looked at tech debt as a vehicle for novel innovation, growth for your best engineers, and managing it became a competitive advantage? In this talk, I’ll discuss how we’re reframing technical debt at Netflix and what we’re investing in to help manage it better.

As many organisations and teams enjoy the trialled comforts of hierarchy, all the responsibility tends to fall on the shoulders of leads, leaving them drowning in meetings and all kinds of ‘been there, done that’ tasks. Meanwhile, talented juniors never catch a glimpse of these new opportunities. Eager for more responsibility and exposure, yet struggling to find it, they can feel similarly stuck in their own search for more 'cool' bits in the day-to-day. 

So if half of us are lulled into overload and the other half frantically looking for more ways to contribute then is it time for change? 

If you’re ready to shift your team dynamics then join me for this talk. You’ll leave with actionable strategies on how to lighten your workload whilst genuinely empowering your team members and helping them grow. Instil confidence, create a safe environment and elevate your leadership. Less burnout, more contentment and way more time for the cool stuff! From overload to oasis, in under 10mins. It’s a win-win 🚀

As an Engineering Manager, I am responsible for managing 12 engineers across two different teams in 4 different timezones (SF, London, Austin and New York). Over the past two years we have experimented (and continue to experiment) with various processes and ways of working to maximise our ability to work collaboratively, deliver incrementally and build team rapport; even when we can't be in the same room. 

This talk will be a retrospective of that journey. We will explore what worked, what didn't and what were trying next.

Well, in the Developer Success Lab – an empirical research lab studying the social science of developers and their wellbeing — we went on a journey in 2023 to understand something a little different about AI and software work: how developers are being impacted by changing expectations happening across the world of software development, and what leaders can do to help them. 

In this talk, I want to share the research story of our large-scale study into the social science of genAI adoption as we fought to bring a human-centered approach to pressing questions that engineering organizations are facing about the rapidly-changing possibilities of AI-assisted coding. 

In this talk, I’ll share our original empirical research findings from 3000+ software engineers and developers across 12+ industries engaged in the transition to generative AI-assisted software work. How are developers impacted by changing demands on their roles? Where might there be emerging equity & opportunity gaps in who has access to these new development capabilities? What are the risks to the quality of technical work, and the developer productivity, thriving, and motivation which drive that technical work? Along with rich data and important insights about the current state of genAI adoption, we learned that what developers are grappling with goes far deeper than flipping the switch on a new tool: by measuring key beliefs about where programming ability comes from and who is seen as "brilliant," we gathered empirical evidence about how to explain why teams thrive and others flail during this transition.

 Along the way, I’ll share the adventure of doing science on an innovative topic under high scrutiny – the choices we made as scientists about what to study and what to measure, including how using community-based methods to amplify diverse, underrepresented voices on tech gives us access to remarkable, incisive insights about how we use AI. Our research has found important risks and emerging equity gaps in how developers are experiencing the transition to AI, but also highlights the teams already creating resilience in this transition. 

Despite the uncertainty of technological transition, moments of change are also a transformational opportunity to examine our shared definitions of success, productivity, and knowledge work. Despite the upheaval of changing technical work, developers’ core skills of lifelong learning and collaboration are key strengths that engineering managers can leverage to sustain innovative teams.

Most of already know that diverse teams are more productive and build better tech products. But Neurodiversity is still relatively new to the conversation when talking about DEI in the workplace. Since the prevalence of Neurodivergence in tech is almost double that of the general population, technical leaders have a position of power and responsibility to consciously build neuroinclusive environments. 

In this talk, you'll learn about a DEI topic in a way that you've never seen before. Parul will be taking you on a trip down memory lane to learn about Neurodiversity in technical leadership through concepts from nostalgic video games such as Mario, Pacman and Tetris. She'll use case studies to demonstrate different scenarios faced by technical leaders and best practices to support and embrace neurodiversity in the workplace.

Through the technical stewardship provided for the CHT, Medic is committed to ensuring the tools stay updated with the newest technologies, techniques, innovations, and industry improvements to serve the community better. 

To bring transparency and enhance visibility and clarity on the technology choices, the technological strategy, and the available features and tools, the CHT leverages a framework called Technology Radar. 

A Technology Radar provides an easy-to-grasp visual representation of tools, languages, frameworks, platforms, and techniques, as well as features and functionalities available for use to build the CHT. Additionally, the Technology Radar provides a degree of adoption and guidelines on using (or not using) a particular technology with the CHT. 

Human-Centered Design (HCD) is important at Medic and building out technology radars is no exception. In this case that shows in the form of two radars, each designed specifically for the needs of the technologists using it. Those are a CHT Technology Radar for Implementers and a CHT Technology Radar for Contributors. Both versions leverage existing open-source tools by ThoughtWorks and AOE to implement the user interface; the difference is in the content and anticipated collaborators. Due to Medic’s commitment to open-source, all the content of the Technology Radars is public on GitHub and open to the community to provide comments and suggestions. 

The talk centres around the benefits of building such a tool, such as transparency, alignment and faster onboarding.

I’ve scrutinised burndown charts, velocity reports, and defect density metrics, searching for insights that will help us deliver more value to our customers in less time. But as a member of the development team, I’ve also experienced the frustration of being reduced to a set of numbers, and the pressure to meet arbitrary targets that don’t necessarily reflect the reality of our work. During this talk, we’ll examine how an over-reliance on metrics can be exploited by both developers and managers for status, power and $$$$. And for the less cynical, how a sensible approach to measuring things can make a team work better. 

These choices determine whether your organisation can use metrics to improve – or if they’re going to cause your engineering culture to take a nosedive. After coaching hundreds of engineering leaders, I’ve seen that the ones who got it right shared a few important traits: all metrics are tied to a decision, they involve their teams, and they always, always follow up. Aside from metrics, these leaders know that they need to equip their teams with the knowledge, tools, and autonomy they need to continuously improve.

Drawing on examples from teams of all stages and sizes, join me to see how you and your teams can responsibly use metrics to foster habits of continuous improvement.

This has resulted in a shift away from traditional software development towards Data Science. This talk gives an overview of Data Science and delves deep into the pipeline data scientists use - right from fetching the data, the Python tools and frameworks used to creating models, gaining insights and telling a story. The session is aimed towards aspiring data scientists - hobbyists and professionals alike. Data-curious folks interested in knowing what the field of Data Science entails are welcome to attend too. 

The government plan for rebuilding London after World War II called for this incredibly valuable land to be filled with office towers to help fill the City of London’s insatiable need for office space. What got built instead was a monument to urbanism and Brutalist architecture housing 2,000 residences, 3 schools, a church, and a performing arts complex.

There’s a lot we can learn about navigating the stakeholders and constraints we face every day from the people who made the Barbican a reality. Let’s dig into the fascinating story of this incredible set of buildings.

On the back of working in the tech industry developing great products in highly competitive markets, how can we make society better? Germán and Seraphine will share the story of skills and talent meeting diversity and social impact.

But if engineers don’t know how to develop in a structured way, they’re more likely to feel disengaged - viewing career conversations and reviews as tick box exercises. And equally as a manager, if you don’t have structured ways to evaluate development you’re more likely to fall victim to bad habits around progression - promoting focus on word of mouth or impression, which could place another barrier in front of engineers who underrepresented in tech. 

So how can you create a structured way for engineers to view, track, and take charge of their own development? And a way that gives you an equitable way of rating their progression? 

At ASOS, we run quarterly surveys with our engineers and we heard that they were struggling to know how to grow themselves - and so we knew we had to do something about it. In this talk, we’ll take you through how we built a comprehensive competency framework; starting from an initial MVP all the way to where we are today - a dedicated web app powered through markdown files in Github and a Blazor Server App. We'll delve into the evolution of frameworks and tools, all with one goal in mind: crafting an engaging and user-friendly platform to drive meaningful development and career conversations. And we’ll also take you through how we shared our matrix with folks outside of engineering - and how they ended up adopting it too. 

You’ll take away: 

• Strategies for navigating constructive career conversations, both for yourself and others 
• Effective frameworks and resources for constructing competency matrices 

• Understanding of which platform of delivery are most effective for career matrix 

   

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• Should we build solutions in-house or hire an external vendor? 
• What tools, programming languages, or frameworks should we invest in? 
• Or how do we choose between a costlier option that promises better outcomes over a more budget-friendly one. 

If you're feeling a bit lost or uncertain about how to tackle these decisions, you're definitely not alone. 

Making smart tech decisions — those that minimize costs while maximizing profits for our organization — can feel like trying to find your way through a labyrinth. There are various factors to weigh and often multiple routes that could lead to what you consider the best result. 

In this talk, we're going to explore a framework for evaluating the return on investment (ROI) of complex tech decisions, illustrated with real-world examples that highlight both the traps to avoid and the paths to success. I'll share methods for pinpointing key metrics that matter, and how to design experiments or proof-of-concepts to measure ROI. Finally we will discuss the importance of staying objective and adaptable throughout the process. 

You will leave this talk equipped to navigate the complexities of tech decision-making with confidence, ensuring your choices align with your strategic goals and deliver tangible value.

At Vercel, we're no longer running the traditional software 1.0 playbook.

In this talk, we'll discuss how Vercel transitioned to an AI-native company and how you too can operate highly effective, AI-native product engineering teams, from the tools used to the way to stay organised amid the rapidly changing pace of AI.
 

While discussions often revolve around cutting-edge technologies like genAI, ChatGPT, and deep learning, this talk shifts the spotlight to what truly matters for most companies—practical data analytics and real-world machine learning applications. 

Learn why enabling data-driven decision-making and automating tasks with machine learning are the keystones that can truly make a difference, particularly for companies transitioning from start-up to scale-up. We'll explore the essential steps in establishing and proving the product-market fit of a new, small data team in a scale-up environment, essentially a data start-up within your own company. 

This talk explains how to kickstart a data team, establish a robust data platform, and implement the first data analytics and machine learning use cases. With the new data team proving its value, it's crucial to avoid getting stuck when experiencing a surge in demand. Drawing parallels with the growth pains often experienced by expanding engineering teams, we'll use concepts from Team Topologies to navigate the challenges and scale your data initiatives effectively. 

Whether you're a data enthusiast, an engineering leader, or part of a growing start-up, this talk promises valuable insights and actionable strategies for creating your own success story with Data & ML.

Against the backdrop of a system that failed with heartbreaking real-world consequences, Hywel’s talk will examine the micro-decisions that lead to bad and dangerous software practices (e.g. remote access to production), and what you can do about them if you’re not the key decision maker. 

He will then explore how dev team culture can lead to the types of process that make complex systems fail, and what you can do to recognise the red flags and course-correct.

The reality of leading a large, complex team might surprise you. Stellar execution and in-depth knowledge won't cut it anymore – leading at scale is a whole different ballgame. 

Transitioning from managing a close-knit team to leading a larger, potentially distributed organization throws unexpected curveballs. Being an expert in your domain or building personal bonds won't magically make you an effective leader. So, how do you shift gears? 

Inna Weiner navigated this exact journey and lived to tell the tale. In this talk, she'll share the crucial insights gained from her leadership evolution, transforming your approach from team management to strategic leadership. Gain five practical tips you can implement immediately to empower others, craft a compelling vision, make tough decisions, and become a leader people genuinely want to follow.

But have you ever wondered why some of us handle change better than others? And how does this relate to software testing? Well, it's not the change itself that's the problem, but rather the uncertainty that comes with it. And who plays a crucial role in managing this uncertainty? Our software teams use testing as their primary tool. 

In this talk, I will take you through uncertainty and its impact on our lives by looking at case studies from the cotton mill workers of 19th Century Britain to the fall of Nokia as the world's No. 1 phone maker and how change connects them both. Then, I will explore how the uncertainty of change can sometimes cause us to ignore, deny, distort, or even try to stop it from happening instead of working with it. 

From there, I will show you how to work with uncertainty by getting curious and learning about our environments. However, this approach works well for well-understood things with expected outcomes, such as a combustion engine. But creating software is far from certain. 

The problem with software development is that we can only be partially sure that what we build will give us the desired outcomes. Moreover, we don't always know the best way to build it. To reduce this uncertainty, we use testing, but not always in the most effective way. We may use testing to feel that we are reducing uncertainty, but it does not necessarily do so. Yet, wonder, curiosity, and learning empower us to navigate the uncertain waters of software development.

Whether a simple refactoring, replacing an existing API, or redesigning a service or even an entire system, migration projects are an inevitable staple in an engineer’s diet. As Team Leads, migration projects present distinct challenges, most notably that existing users, who may be outside our immediate sphere of influence, must be migrated to the new solution. This can take time.

In this short talk, Lawrence will reflect on his experience leading teams through multi-year migration projects. He will discuss a general approach to this before shining a spotlight on the unique challenges that a prolonged migration project has on team dynamics. For example, how do we cope with fatigue and complacency? What can leaders do to motivate the team and help them maintain their focus? Finally, the speaker will examine some techniques to address these questions and how the resulting lessons can be applied more generally within the Team Lead role.

Join me for a thought-provoking and entertaining presentation where I'll take you on a journey through some of the biggest and most impactful bugs in software history, including the example of an interplanetary probe launched by NASA that was lost due to a software bug. This will not only show the importance of attention to detail but also highlight the significance of proper testing and quality assurance. 

We all know that no piece of software is free of bugs and errors, but by learning from the mistakes of others, we can minimize the risk of introducing similar bugs in our own work. This talk is designed to evoke a sense of schadenfreude, allowing us to smile when we hear what happened to others while also taking away valuable lessons to improve our own craftsmanship. 

This presentation will provide practical advice and insights to help you improve your skills and avoid becoming the next "All Star" bug. So, join me for an entertaining and educational session that will leave you with a better understanding of software development and the tools to take your skills to the next level.

Not everyone is thinking about the future, not everyone wants to learn something new. People think goals are pointless and performative, and to be fair to them, they absolutely can be. 

So, how do you set goals with someone who doesn’t really want to? 

Well, the truth is, *most* people do have a sense of the direction they want to go in, deep down, somewhere. You as a manager just have to help them find it and drag it out them. 

It’s also important to acknowledge that goals are not for everyone: they can create undue stress and distraction, so what do you do with those types of people? 

There are tons of ways to set goals, there are countless blog posts and YouTube videos about it. Over the 4 years I’ve been managing, I’ve learnt a lot about how to help people find goals they are excited about. I’ve refined my own process, which focuses on the individual, aligns with the company and encourages true growth. 

During my talk I’m going to share my tried and tested method of setting goals, I will do a step by step walk through of my process, including: 

• Pulling ideas out of your reports
• Creating tangible, realistic goals that your reports are excited about and engaged in - How not to repeat the goal setting process every cycle (making it fast and agile) 

• How to set direction when goals aren’t a good fit - Align with broader team or company objectives 

   

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As AI reshapes the software engineering landscape and engineering teams embark on building their first AI-powered features, leadership and management also need to evolve in ways that ensure they can provide the right support to set teams up for success as they navigate this new frontier.

Drawing from my experience as Engineering Manager at incident.io, where I was part of a product team that built the company's first AI-powered features, this talk combines personal insights and broader leadership strategies. It aims to help your team navigate the challenges and opportunities presented by AI. It will highlight the need for leaders to adapt to these technologies and to anticipate unexpected outcomes as teams begin using them. This talk's objective is to provide engineering managers with the tools necessary to encourage innovation, manage new situations, and ensure the success of AI initiatives within their teams. 
 

You have to actively drive change by suppressing negative behaviours and transforming toxic managers into better leaders. It's not enough to silently do a good job; You must take an assertive approach to tackle difficult situations with peer managers and those above you to create a positive work environment. However, providing feedback to individuals, especially if it's your boss, can be challenging and may strain the working relationship. In this talk, Alex will give you practical mechanisms to identify and tackle difficult situations with confidence and poise. You'll leave the talk feeling inspired and empowered with the tools you need to react to difficult situations and make a real difference in your workplace. Join us in this talk and let's kick some dick behaviours to the curb!

We often find mentors: people who can give us helpful advice. But what can be even more valuable is finding “sponsors”, who help us find new opportunities and improve the visibility of our work. As sponsorship is especially important for members of minoritized communities in tech, Lara Hogan walks through tactics you can employ today to be a sponsor for those around you, too. 

But with so many variables that contribute to how successful a team is - how can you work out what to change to move the needle? And what should you be measuring in the first place?

Ready to go beyond theory and get practical? This workshop dives deep into DORA, showing you exactly how to apply data-driven insights in your real-world environment to identify bottlenecks, measure progress, and drive continuous improvement. From selecting key performance indicators to fostering a culture of learning, you'll walk away with actionable strategies to boost your team's velocity, reduce time to market, and achieve your goals.

However many developers are feeling fear and anxiety over the adoption of AI tools in their day-to-day development process. And as leaders, we’re expected to be able to guide our teams in how to adopt generative AI, while managing our anxieties and worries about our ability to successfully adapt to this change.

In this workshop, we’ll take a look at how you can help yourself and your teams to adopt AI-assisted tools and practices in a human-centred, evidence-based way. We’ll give you an assessment that will allow you to benchmark your AI adoption readiness and respond appropriately to it with strategies that allow you to effectively surface and address worries head-on. By the end of the session, you’ll walk away with a toolkit for understanding how to best guide your engineers and organization through this change.

We have to know how to prioritize, manage work to deadlines and perhaps the hardest - lead others. Our role means a shift from doing to guiding and supporting. We must know when to manage, mentor or coach. When we use these modalities well we build capacity in the team, increasing our ability to meet organisational goals. Along with it, people feel valued, we strengthen our culture and create a workplace where people want to come to work.

In this mini-workshop, we'll talk about the difference between each of these skills and how to know when to use them. You'll learn three key coaching skills and have the opportunity to practice deciding which modality to use. You'll walk away more confident in your ability to lead others.