Every session, keynote, and workshop slot — sorted by day so you can plan your path through the conference.
Most teams track numbers—but few measure what truly matters. In this insightful and practical session, Ken Sipe breaks down how to align organizational goals with measurable outcomes using Objectives and Key Results (OKRs) and Key Performance Indicators (KPIs) that actually drive success.
Ken will cut through the buzzwords and frameworks to show how engineering teams, product leaders, and executives can build a measurement culture that’s both data-driven and purpose-aligned. You’ll learn how to define metrics that motivate, avoid vanity indicators, and establish traceability from daily work to strategic outcomes.
Key takeaways include:
How to craft meaningful OKRs that align technical and business goals
The difference between activity, output, and outcome metrics—and why it matters
Techniques for cascading objectives across teams without creating chaos
How to use metrics as a feedback system, not a weapon
Real-world examples of OKRs and KPIs that improved clarity, accountability, and results
Whether you’re scaling an engineering organization or trying to bring more focus to your current team, this session will help you turn measurement into momentum—and ensure that success isn’t just tracked, but achieved.
Most teams treat incidents as technical failures. Great teams treat them as coordination failures under stress. This session gives engineering leaders a practical incident command system they can apply immediately: roles, communication cadence, decision logging, escalation paths, and postmortems that create learning instead of fear.
When incidents hit, technology matters — but leadership determines outcomes. This session walks through an operating model for incident response that scales across teams and time zones without chaos.
We cover clear roles (incident commander, comms lead, operations lead, and scribe), fast status loops, and decision frameworks that lower risk under pressure. You’ll see practical templates for timeline capture, stakeholder communication, and recovery prioritization.
We also cover the most ignored part: after-action learning. You’ll leave with a blameless postmortem structure that improves systems, process, and team behavior instead of assigning guilt.
Includes realistic scenarios, facilitation techniques for cross-functional pressure moments, and a leadership checklist you can use in your next production incident.
Outcomes:
No panic theater. Just practical leadership patterns that work when production is on fire and Slack has gone feral.
In the fast-paced world of software delivery, we often mistake “management” for “leadership.” Management is about complexity, stability, and the coordination of resources; leadership is about change, alignment, and the inspiration of people. For many tech leaders, the instinct is to manage the code, the deadlines, and the tickets—but great systems aren't built by managed workers; they are built by led innovators.
In this session, Ken Sipe explores the critical shift from a command-and-control mindset to a high-trust leadership model. We will dive into the “Anti-Patterns of Management” that stifle creativity and slow down velocity, and replace them with actionable leadership strategies designed specifically for technical teams.
Building an AI model is the easy part—making it work reliably in production is where the real engineering begins. In this fast-paced, experience-driven session, Ken explores the architecture, patterns, and practices behind operationalizing AI at scale. Drawing from real-world lessons and enterprise implementations, Ken will demystify the complex intersection of machine learning, DevOps, and data engineering, showing how modern organizations bring AI from the lab into mission-critical systems.
Attendees will learn how to:
Design production-ready AI pipelines that are testable, observable, and maintainable
Integrate model deployment, monitoring, and feedback loops using MLOps best practices
Avoid common pitfalls in scaling, governance, and model drift management
Leverage automation to reduce friction between data science and engineering teams
Whether you’re a software architect, developer, or engineering leader, this session will give you a clear roadmap for turning AI innovation into operational excellence—with the same pragmatic, architecture-first perspective that Ken is known for.
What happens when a self-taught programmer with a background in anthropology ends up leading engineering teams?
Robert Harris traces his path from BASIC on a Commodore 64, through a decade in archaeology and the social sciences, to running software teams - and the lessons that came with becoming a manager by accident and a leader on purpose. The hardest problems he ran into weren't technical. They were human. So he went back to his training as an anthropologist to solve them.
This 60-minute session approaches engineering culture the way an anthropologist approaches any human culture: by looking at the beliefs people share, the behaviors that bind them together, and the artifacts they create along the way.
Robert walks through real examples from teams he has led to show how culture emerges in practice - from unconventional job titles and team language, to rituals around technical debt and broken builds, to retrospectives, shared experiences, personalized rubber ducks, onboarding artifacts, and the art a team creates about itself.
Along the way, he'll show why healthy culture can't simply be declared in a mission statement. The strongest cultures emerge from the people already there. Leaders can shape them, reinforce them, and give them room to grow - but they can't manufacture them from a template.
Attendees will leave with:
Whether you're a reluctant manager, a seasoned leader, or someone who has stepped on a rake in production, you'll leave ready to put on your anthropologist's hat and build the kind of engineering culture you'd actually want to be a member of.
“How are you helping unite and bond your teams? What creative team buildings have you tried, both virtually or inperson, to connect the team on both a personal and professional level?”
Join this fun discussion on 12+ creative teambuilding ideas you can give a try to help take your team's connection to the next level! We’ll introduce ideas such as Values Exercises, Wellness Contests, Collaborative Team Development, SkillsBased Volunteerism, and unique games such as ‘Are You Smarter Than a 5th Grader’ that our teams have loved!
This two part executive briefing helps leaders, managers, and decision-makers understand the real technologies behind today’s AI movement — in clear, practical terms.
Rather than avoiding key terms, the session translates them: LLMs, RAG, Copilots, Agents, and the Model Context Protocol (MCP) — showing how each fits into the way organizations build and use AI.
Participants gain an intuitive understanding of how AI systems think, retrieve, and act — and how those capabilities are already showing up in tools across the enterprise.
Through relatable analogies, visuals, and examples, attendees will learn how to talk confidently with technical teams, evaluate AI initiatives, and lead with insight and accountability.
The presentation blends conceptual clarity, leadership relevance, and visual storytelling. It’s designed for executives and non-technical professionals who need to grasp how AI fits into their organization’s strategy, operations, and governance.
1.How Modern AI Really Works
Understand how Large Language Models (LLMs) learn patterns from data and generate responses. See why they don’t “know” — they predict — and why context and validation are essential for business use.
2.Retrieval-Augmented Generation (RAG): Making AI Current
Learn how RAG extends an AI’s capabilities by connecting it to trusted enterprise data sources. Understand how this approach keeps responses accurate, relevant, and policy-compliant.
3.Copilots and AI Assistants
Explore how copilots combine AI reasoning, enterprise context, and workflow integration to support human work. See how GitHub Copilot, Microsoft 365 Copilot, and internal copilots assist teams without replacing them.
4.Agents and AI Autonomy
Examine how AI agents can plan, call tools, and make structured decisions using the “Thought → Action → Observation” loop. Understand how this differs from static chatbots — and how to govern it.
5.MCP (Model Context Protocol): Standardizing AI Connections
Discover how MCP enables AI systems to safely discover and use tools, APIs, and data through a shared protocol — simplifying integration and improving control across departments.
6.Security, Guardrails, and Governance
Discuss the emerging field of AI security: preventing prompt injection, protecting data, and enforcing responsible use. Learn how leadership shapes trust and compliance in AI-enabled operations.
7.The Leadership Playbook for AI Adoption
Gain a framework for evaluating AI initiatives.
This two part executive briefing helps leaders, managers, and decision-makers understand the real technologies behind today’s AI movement — in clear, practical terms.
Rather than avoiding key terms, the session translates them: LLMs, RAG, Copilots, Agents, and the Model Context Protocol (MCP) — showing how each fits into the way organizations build and use AI.
Participants gain an intuitive understanding of how AI systems think, retrieve, and act — and how those capabilities are already showing up in tools across the enterprise.
Through relatable analogies, visuals, and examples, attendees will learn how to talk confidently with technical teams, evaluate AI initiatives, and lead with insight and accountability.
The presentation blends conceptual clarity, leadership relevance, and visual storytelling. It’s designed for executives and non-technical professionals who need to grasp how AI fits into their organization’s strategy, operations, and governance.
1.How Modern AI Really Works
Understand how Large Language Models (LLMs) learn patterns from data and generate responses. See why they don’t “know” — they predict — and why context and validation are essential for business use.
2.Retrieval-Augmented Generation (RAG): Making AI Current
Learn how RAG extends an AI’s capabilities by connecting it to trusted enterprise data sources. Understand how this approach keeps responses accurate, relevant, and policy-compliant.
3.Copilots and AI Assistants
Explore how copilots combine AI reasoning, enterprise context, and workflow integration to support human work. See how GitHub Copilot, Microsoft 365 Copilot, and internal copilots assist teams without replacing them.
4.Agents and AI Autonomy
Examine how AI agents can plan, call tools, and make structured decisions using the “Thought → Action → Observation” loop. Understand how this differs from static chatbots — and how to govern it.
5.MCP (Model Context Protocol): Standardizing AI Connections
Discover how MCP enables AI systems to safely discover and use tools, APIs, and data through a shared protocol — simplifying integration and improving control across departments.
6.Security, Guardrails, and Governance
Discuss the emerging field of AI security: preventing prompt injection, protecting data, and enforcing responsible use. Learn how leadership shapes trust and compliance in AI-enabled operations.
7.The Leadership Playbook for AI Adoption
Gain a framework for evaluating AI initiatives.
The scope keeps expanding. The team still needs direction. Leadership wants more output. And the AI landscape is moving faster than anyone can fully keep up with. For a lot of technical leaders, somewhere along the way the job quietly shifted from leading to just keeping up. Decisions get made from whatever state you happen to be in when the next thing lands — and it's been costing you focus, clarity, and probably sleep.
Most leadership training addresses what to do. Less often does it address the skill of staying clear-headed while you're doing it — under real pressure, in real time, with a team and boss looking to you for answers. This full-day workshop is built around that gap. You'll work through real pressure situations — the kind you actually face — and develop practical skills for staying grounded when they spike, so you can lead with steadiness instead of reaction. You'll learn as much from the honest conversations in the room as from the content itself.
You'll leave with skills you can use in those moments — the ones you already know need them. More of your best thinking available when it matters most. The kind of leader you already know you can be, more of the time. Getting more done with less of the grind that's been wearing you down
You've basically stopped writing significant amounts of code. AI does it — you check it, direct it, and sign off on it. The leverage is real and so is the uneasy feeling that comes with it. You're now responsible for output you didn't fully produce, at a volume you can't fully review, while leadership pushes for more speed. And nobody — not your org, not the industry — has figured out yet who's actually on the hook when something goes wrong.
Here's the honest truth: nobody has a clean answer yet — not your organization, not the industry, not the people writing the frameworks. So this session doesn't pretend to have one either. Instead, we'll pool what's actually working for people in the room, surface what's already helping teams stay more on top of it, and build something more useful than a handed-down answer. You'll also develop the skill to become calmer and more clearheaded when you're buried in pull requests and competing demands — and when something does go wrong. You'll leave with concrete approaches for navigating the gray zone and more practical ways to handle the pressure of leading when the rules are still being written.
Does your life feel like non stop motion with never a moment to chill, as if you're always reacting to shifting priorities? You’re not alone, and it’s time to bring your A-game beyond the code. In this groomed talk, you'll learn how to use similar concepts—roadmaps, backlogs, and more—from your professional life in analogous ways to bring order to your everyday life.
Discover how to transform chaos into clarity by prioritizing tasks like a pro, tackling personal goals with laser focus, and making “fire drills” far less frequent. You’ll also learn how to let go—yes, it’s a skill, not just a mindset—and drop some of the mental clutter that keeps you spinning. Through relatable examples, humor, no-nonsense strategies, and real-world letting go practices, you’ll walk away with tools to get your life dialed in, reduce stress, achieve what truly matters—and still have time for a beer with friends. No debugging required!
Being a tech leader means balancing vision, strategy, and innovation—yet too often, the administrative burden of the role becomes a persistent obstacle, especially for those who found themselves thrust into leadership accidentally or reluctantly. If you're a technical expert navigating the transition into leadership, it's easy to feel overwhelmed by information overload, endless meetings, follow-ups, and scattered responsibilities.
In this practical, immediately applicable full day workshop, Michael introduces the Digital Knowledge Management (DKM) Tech Leader Toolbox—a proven approach to taming the chaos and reclaiming your clarity, productivity, and sanity. Leveraging Tiago Forte's “Building a Second Brain” methodology combined with powerful tools like Logseq, you'll learn structured workflows to capture, organize, distill, and effortlessly retrieve critical information exactly when you need it.
You'll discover how to streamline meeting notes, simplify administrative tasks, track decisions and outcomes, hold your self and your team accountable, and build your personal leadership knowledge base. With these tools and techniques, you'll not only master the administrative aspects of your role but transform them into a powerful advantage. Join us and take control of your leadership journey today!
As a tech leader, how can you help your developers take ownership of security without slowing down innovation? Developers are incentivized to prove that systems work as expected—but how often do we ensure they don’t do what they shouldn’t?Security isn’t just a checklist; it’s a mindset. But can your team define what security truly means? How do you measure enough security? More importantly, how do you drive meaningful, incremental improvements in your organization’s security posture without overwhelming your developers?
This session will provide you with a practical, actionable framework to embed security into your development process. You’ll walk away with concrete strategies to help your teams proactively design security in—without sacrificing velocity.
There are certain tech trends people at least know about such as Moore's Law even if they don't really understand them. But there are other forces at play in and around our industry that are unknown or ignored by the ever diminishing tech journalism profession. They help explain and predict the pressures and influences we are seeing now or soon will.
In this talk, I will identify a variety of trends that are happening at various paces in intertwined ways at the technological, scientific, cultural, biological, and geopolitical levels and why Tech Leaders should know about them. Being aware of the visible and invisible forces that surround you can help you work with them, rather than against them. You will also be more likely to make good choices and thrive rather than being buffeted uncontrollably.
This one-day leaders program builds practical AI literacy for managers, project leaders, and business stakeholders who need to make informed decisions about AI—without diving into technical implementation. Participants learn the core concepts and current AI landscape in plain language, practice using AI to improve everyday leadership workflows (writing, planning, analysis, and decision support), and leave with concrete artifacts they can use to sponsor and scope real initiatives.
The day is structured around four 90-minute sessions that balance concise instruction with hands-on exercises. Leaders will develop a shared vocabulary (models, assistants, agents, RAG, inference), build an intuition for where AI is genuinely useful versus where it creates risk, and learn a few simple verification habits to improve output quality.
The second half of the day shifts from understanding to sponsorship: how to select AI use cases worth piloting, define success metrics, and right-size scope so teams can prove value quickly. The program closes with a lightweight governance and rollout playbook, helping leaders coordinate with technical teams and set expectations for what a reasonable pilot (and a responsible scale-up) looks like in their organization.
AI agents are not just tools for the IDE; they are the new operating system for high-stakes leadership. In this session, Ken Sipe moves beyond the hype of “AI-assisted coding” to demonstrate what it actually looks like to lead and scale with a personal AI agent. From executive briefings and organizational “pulse checks” to automated travel ops and stakeholder management, Ken provides a practical framework for tech leaders to reclaim 20% of their cognitive load.
Everyone talks about AI strategy for their products. Fewer leaders show what it looks like to actually lead with one.
Ken shares his real-world deployment of a personal executive agent that bridges the gap between high-level strategy and tactical execution. This isn't a session on prompt engineering—it is a masterclass in an Tech Leader Operating Model. You will see how an incrementally built system handles morning situational awareness, privacy-safe calendar synchronization, complex travel logistics, and the automation of professional brand building while you sleep.
The Four-Stage Framework for Leaders:
Build: Curating the “Executive Context” (What your agent knows about your roadmap and team).
Trust: The Autonomy Ramp (Moving from “Assistant” to “Agent”).
Delegate: Identifying high-leverage administrative and strategic hand-offs.
Compound: Building a memory system that scales your decision-making.
Live Demonstrations of Leadership Workflows:
The Executive Brief: Beyond email triage—priority surfacing across Slack, Jira, and GitHub to identify organizational bottlenecks.
Stakeholder & Speaking Pipeline: Automating CFP tracking and abstract generation for conferences, while maintaining a consistent thought-leadership presence.
Travel & Logistics Ops: Auto-detecting conference trips, fare watching, and seamless TripIt/Expensify integration for a zero-friction travel experience.
The Privacy Bridge: Managing a personal-to-work calendar sync that protects your private life while ensuring your team has accurate OOO visibility.
Secure Vault Retrieval: Sudo-style authenticated access to sensitive documents and IDs on the fly.
The Nightly Content Forge: How the agent drafts internal memos, blog posts, or project summaries while you are offline.
Strategic Governance:
We will also tackle the critical “Leader-to-Agent” trust design: how to define “Guardrails vs. Guidance,” managing sensitive corporate data, and building a context-rich memory system that makes the agent a genuine force-multiplier for your leadership style.
Outcomes:
A Leadership Mental Model: How to deploy an agent that complements your specific technical and managerial skill set.
High-ROI Automations: A curated list of “Quick Wins” for tech leaders to implement immediately.
Governance & Control: A realistic roadmap for safety, privacy, and control in autonomous systems.
From Intermittent to Continuous: Inspiration to transition from “using AI” to “operating through AI.”
AI agents are not just tools for the IDE; they are the new operating system for high-stakes leadership. In this session, Ken Sipe moves beyond the hype of “AI-assisted coding” to demonstrate what it actually looks like to lead and scale with a personal AI agent. From executive briefings and organizational “pulse checks” to automated travel ops and stakeholder management, Ken provides a practical framework for tech leaders to reclaim 20% of their cognitive load.
Everyone talks about AI strategy for their products. Fewer leaders show what it looks like to actually lead with one.
Ken shares his real-world deployment of a personal executive agent that bridges the gap between high-level strategy and tactical execution. This isn't a session on prompt engineering—it is a masterclass in an Tech Leader Operating Model. You will see how an incrementally built system handles morning situational awareness, privacy-safe calendar synchronization, complex travel logistics, and the automation of professional brand building while you sleep.
The Four-Stage Framework for Leaders:
Build: Curating the “Executive Context” (What your agent knows about your roadmap and team).
Trust: The Autonomy Ramp (Moving from “Assistant” to “Agent”).
Delegate: Identifying high-leverage administrative and strategic hand-offs.
Compound: Building a memory system that scales your decision-making.
Live Demonstrations of Leadership Workflows:
The Executive Brief: Beyond email triage—priority surfacing across Slack, Jira, and GitHub to identify organizational bottlenecks.
Stakeholder & Speaking Pipeline: Automating CFP tracking and abstract generation for conferences, while maintaining a consistent thought-leadership presence.
Travel & Logistics Ops: Auto-detecting conference trips, fare watching, and seamless TripIt/Expensify integration for a zero-friction travel experience.
The Privacy Bridge: Managing a personal-to-work calendar sync that protects your private life while ensuring your team has accurate OOO visibility.
Secure Vault Retrieval: Sudo-style authenticated access to sensitive documents and IDs on the fly.
The Nightly Content Forge: How the agent drafts internal memos, blog posts, or project summaries while you are offline.
Strategic Governance:
We will also tackle the critical “Leader-to-Agent” trust design: how to define “Guardrails vs. Guidance,” managing sensitive corporate data, and building a context-rich memory system that makes the agent a genuine force-multiplier for your leadership style.
Outcomes:
A Leadership Mental Model: How to deploy an agent that complements your specific technical and managerial skill set.
High-ROI Automations: A curated list of “Quick Wins” for tech leaders to implement immediately.
Governance & Control: A realistic roadmap for safety, privacy, and control in autonomous systems.
From Intermittent to Continuous: Inspiration to transition from “using AI” to “operating through AI.”
Teams can often get dysfunctional. Even for leaders with the best of intentions—without knowing what signs to look for, and how to avoid to avoid them, can create teams that over time start fail to be cohesive, and delivering on their expectations. Add to that the ever changing landscape of the enterprise, the revolving door of attrition—all of which add to making this a real challenge for any leader.
This session will dive into some of the signs of a dysfunctional team, and provide guidance on what a leader can do to not just build, but maintain a high functioning team.
AI is accelerating software development at an unprecedented pace, but many teams are discovering a frustrating reality: faster coding isn’t translating into faster delivery.
The reason is counterintuitive. When you accelerate one part of a system, you don’t improve the system… you stress it. More code becomes more review, more coordination, more cognitive load, and ultimately, less flow.
This talk connects that modern failure mode to a foundational systems insight from The Goal: local optimization usually degrades overall performance. From there, Michael Carducci shows how to apply the Theory of Constraints to modern software delivery.
Using concrete examples, you’ll see how practices like XP, DevOps, Domain-Driven Design, and Team Topologies act as targeted interventions on specific bottlenecks—and how misapplying them can make things worse.
You’ll leave with a practical mental model for identifying constraints in your system, reasoning about trade-offs, and designing for flow in an AI-accelerated world.
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.
If everyone agrees with you, you’re probably not innovating, you’re just conforming faster. History’s breakthroughs rarely came from consensus; they came from heretics, hackers, and the hopelessly curious. In this talk, Michael Carducci takes aim at the myth of collective wisdom and explores why the crowd is almost always optimized for the past. Through stories of misfits who changed the world—from computing pioneers to magicians who reinvented wonder; Carducci reveals the hidden patterns of real innovation: discomfort, doubt, and persistence in the face of polite disbelief.
You’ll learn how to recognize the subtle forces that suppress new ideas, how to trust your intuition when it runs counter to consensus, and how to cultivate the curiosity and courage that real innovation demands. This is a talk for the misfits, the tinkerers, and the quietly visionary… because progress has always started at the edges.
Gartner just declared the semantic layer a non-negotiable foundation for AI. Most of the industry responded with a blank stare.
This presentation is the answer to that blank stare.
Your AI has a dirty secret: there is no mechanism in its architecture for truth. Only probability. Every response is a hallucination — most just happen to overlap with the facts. The philosophers figured out why 2,500 years ago, and they also gave us the solution. Plato defined knowledge as justified true belief. RAG is our architecture for justification. But there's a problem — your structured data is wholly inaccessible to it, because your JSON is full of magic strings that mean nothing outside the system that generated them.
This presentation shows you how to fix that. Not with a new framework, a bigger model, or an enterprise triple store. With a discipline — the discipline of making meaning explicit. Be introduced to a standards stack that has been quietly solving this problem for 30 years. Your AI is already fluent in it. Half the web already speaks it. Google built an empire on it.
You'll leave with a concrete understanding of what the semantic layer actually is, why it matters, and—most importantly—how to empower teams to start building it this week with the APIs you already have.
Your data isn't worthless. AI just doesn't know what it means yet.
The Human Side of AI: Unlocking Opportunity in the New Bottlenecks of Software Development
Artificial Intelligence is transforming software development at unprecedented speed—reshaping roles, workflows, and organizational dynamics. Yet, with every acceleration comes a new constraint.
Kiran Rouzie (Head of Technology Strategy, North America & Global Head of Organizational Change & Transformation) and Rachel Laycock (CTO) of ThoughtWorks will discuss how AI introduces fresh bottlenecks that shift where value is created in the delivery lifecycle — and how these shifts unlock opportunities for business analysts, QA professionals, and other often-overlooked roles to rise in influence. More broadly, they will reflect on the human side of AI adoption: how diversity of thought, perspective, and lived experience must shape the integration of AI into the workforce.
Far from being a story of replacement, this conversation emphasizes the collective contribution of people in guiding, validating, and amplifying AI’s potential. Kiran and Rachel will highlight how voices from diverse and minority communities are essential in shaping trustworthy AI practices, and how organizations can foster inclusion while reimagining roles.
Attendees will walk away with a deeper understanding of:
Far from being a story of replacement, this conversation emphasizes the collective contribution of people in guiding, validating, and amplifying AIs potential. Kiran and Rachel will highlight how voices from diverse and minority communities are essential in shaping trustworthy AI practices, and how organizations can foster inclusion while reimagining roles.
Attendees will walk away with a deeper understanding of:
AI is no longer a side experiment. It is quickly becoming a standard part of enterprise IT, both in how systems get built and how teams get work done. For CIOs, CTOs, and team leads, the hard part is figuring out which AI efforts will actually pay off without creating unnecessary risk for the company.
In this session, you will get a practical way to pick the right first pilots, define success metrics that matter, and avoid the most common traps. Those traps include leaking sensitive data, producing unreliable results, having no clear owner, and running pilots that never deliver real ROI. We will talk about how AI tools fit into everyday team workflows, how to balance value and risk so you know where to start, and what guardrails to put in place from day one. That includes data boundaries, human oversight, auditability, evaluation, and safe fallback behavior.
This talk is grounded in my experience leading an internal AI adoption initiative at a major internet company, helping hundreds of technical and non-technical employees adopt AI effectively. I will also share practical leadership lessons and firsthand anecdotes from managing the effort.
You will leave with a simple checklist and an action plan you can use right away to launch a secure, measurable AI pilot that your team can ship and your organization can scale.
Technology professionals have a unique opportunity to use their skills to create meaningful impact—both inside their organizations and within their communities. This session will outline simple, actionable ways you and your teams can give back that result in a win:win for both the community and your culture and employee engagement/fulfillment.
We’ll discuss real-world ideas around how techies can give back internally, such as sharing knowledge through Lunch & Learns, mentoring peers, and organizing team philanthropic initiatives (spoiler: hosting group/s from programs like ‘Code the Dream’ or Best Buddies for an office field trip is a fan favorite!). We’ll also cover more ways to give back externally, including supporting STEM workforce development nonprofits, civic good hackathons, local Meetups, and contributing to tech-for-good initiatives or community events. We’ll learn about national organizations you can look into supporting who are helping upskill future tech generations, including Year Up United, Per Scholas, MSSA (Microsoft Software and Systems Academy), Wounded Warrior Project and more, and highlight specific volunteer needs these organizations have. Lastly, we’ll discuss a bit about the TechSoup nonprofit, and how TechSoup can support and provide cost savings for any nonprofit/s you might be involved in!
The toughest problems in engineering leadership have nothing to do with the technology, and everything to do with the humans building it. The technical skills that earn an engineer the promotion can be adapted to produce great leaders, but only with the right translation layer. Without it, leaders default to instincts that work on technical systems but fail on human ones.
This workshop installs that translation layer.
Over five modules delivered in a full-day workshop, participants learn to see the human system they're already inside, recognize what their daily inputs train into it, and read the signals it sends back. From there, they assemble a Leadership OS: the integrated stack that determines how a leader shows up under pressure, and the runtime practice that keeps the defaults from taking over. The day closes with applications - the OS running against real situations every engineering leader faces: difficult conversations, deadlocked teams, feedback gone wrong, terminations, and power gradients that turn against the team.
The content draws on twenty-five years of engineering leadership from a former anthropologist, gained across startups, consultancies, and global organizations, told through first-person stories of failure modes and recoveries. Frameworks come from psychology, anthropology, systems theory, and philosophy - translated into vocabulary engineers can use.
Participants leave with diagnostic questions, pre-loaded responses, and a working operating system for leading humans the way they already lead systems: with awareness, intention, and design.
Many codebases already struggle with technical debt that makes development expensive, frustrating, and risky. When coding agents enter the development loop, existing technical debt becomes an AI-adoption constraint. Poor-quality code causes more defects and turns even state-of-the-art AI agents into legacy code generators.
In this keynote, Adam Tornhill shows why code health cannot be treated as a mere engineering concern: it determines how much of the promised AI productivity gains organizations can capture. Backed by large-scale empirical studies on AI coding and developer productivity, we separate what works from what doesn't in real-world systems. Building on these findings, we distill practical techniques for scaling agentic coding while preventing a quality crash.
Not too long ago, each new feature in our products came with a reasonable assumption: there was a human programmer in the loop. Writing the code was how engineers learned their systems, and how organizations built knowledge of how those systems worked.
Agentic coding breaks that feedback loop. Without understanding, we risk generating tomorrow's legacy systems at agentic speed.
Drawing on cognitive psychology and hands-on experience leading AI-first teams, Adam Tornhill explores what this shift means for technical leaders.
You’ll learn:
When pushing agent throughput backfires, and how to set a sustainable pace.
Where to invest in automated verification versus what to leave for humans.
Practices that keep teams learning their systems when they no longer write the code.
When the pressure is on, your team stops listening and starts watching. What they see is your operating system under load. Human hardware runs emotion before logic finishes loading, so under stress even smart, decent leaders fall back on factory defaults: ego, fear, fight, flight, freeze. Add AI-accelerated output that moves faster than anyone can fully audit, and you get asked for answers you don't have yet, at the moment your defaults are loudest. Some days that's exhilarating. Other days you wonder whether you're still the right person to ask.
In this two part, co-taught session, Robert Harris and Hunter Milligan pair a systems view of leadership with practical skills for the moment itself. Through stories of leaders under increasing load, from a well-meant intervention that backfired to a boss who lost it in front of the team, you'll learn a simple loop for choosing your response (signal, default, interrupt, principle, response) and the core leadership principles worth deciding before you need them. Then you'll practice: a breathing reset that settles your body, a way to stop spinning on a problem you can't solve yet, and a method for getting through the dread of a hard conversation. You'll work real scenarios with the people around you and leave with something steadier than certainty: one honest sentence for when the answer isn't there yet, and the ability to stay clear, consistent, and credible while it arrives.
When the pressure is on, your team stops listening and starts watching. What they see is your operating system under load. Human hardware runs emotion before logic finishes loading, so under stress even smart, decent leaders fall back on factory defaults: ego, fear, fight, flight, freeze. Add AI-accelerated output that moves faster than anyone can fully audit, and you get asked for answers you don't have yet, at the moment your defaults are loudest. Some days that's exhilarating. Other days you wonder whether you're still the right person to ask.
In this two part, co-taught session, Robert Harris and Hunter Milligan pair a systems view of leadership with practical skills for the moment itself. Through stories of leaders under increasing load, from a well-meant intervention that backfired to a boss who lost it in front of the team, you'll learn a simple loop for choosing your response (signal, default, interrupt, principle, response) and the core leadership principles worth deciding before you need them. Then you'll practice: a breathing reset that settles your body, a way to stop spinning on a problem you can't solve yet, and a method for getting through the dread of a hard conversation. You'll work real scenarios with the people around you and leave with something steadier than certainty: one honest sentence for when the answer isn't there yet, and the ability to stay clear, consistent, and credible while it arrives.
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.
Enterprise Architecture (EA) has long been misunderstood as a bottleneck to innovation, often labeled the “department of no.” But in today’s fast-paced world of Agile, DevOps, Cloud, and AI, does EA still have a role to play—or is it a relic of the past?
This session will highlight the need for Enterprise Architecture in the modern enterprise. It will show how EA can help provide line-of-sight from business to IT assets and management. Leaders will learn how to build out a future-proof version of EA that thrives in the modern landscape.
Remote and hybrid teams don’t lose culture when they lose the office. They lose many of the accidental mechanisms that helped culture form: hallway encounters, informal learning, weak ties, shared jokes, spontaneous collaboration, and everyday social connection.
But none of those mechanisms actually require a building.
Drawing on anthropology, engineering leadership, and years of leading distributed teams, this session examines what thriving online communities already know about building culture without physical proximity - and how engineering leaders can intentionally design the digital spaces where trust, identity, learning, and community can grow.
In this session, a software engineering leader with formal training in psychology and anthropology challenges one of the most persistent assumptions about remote work: that meaningful culture requires physical proximity.
The needs behind that assumption are real. Teams need informal interaction, mentorship, shared identity, spontaneous collaboration, belonging, and access to information. But offices satisfy many of those needs accidentally - through hallways, overheard conversations, shared spaces, and proximity.
Remote and hybrid teams have to satisfy them by design.
Using seven common return-to-office arguments as a starting point, this session separates the human need from the physical mechanism traditionally used to meet it. From hallway conversations and brainstorming to onboarding, coordination, and belonging, attendees will explore how distributed teams can intentionally reproduce - and sometimes improve - the functions we once relied on the office to provide.
Then we'll borrow one of anthropology's oldest tools: cross-cultural comparison.
Open source communities and online gaming cultures have built strong distributed identities for decades, often among people who have never met in person. Their success reveals practical lessons about weak ties, shared language, rituals, symbols, informal spaces, and cultural artifacts.
Finally, we'll bring those lessons back to engineering teams through real examples from remote organizations Robert's led: digital watercoolers, team totems, custom dialects and emojis, collaborative art, onboarding artifacts, recognition rituals, and the deliberately designed spaces where culture can take root.
The core idea is simple:
The office gave us cultural infrastructure by accident. Remote teams have to build it on purpose.
Participants will leave with:
• A framework for separating the human needs of a team from the physical mechanisms traditionally used to meet them
• Practical ways to create low-friction digital spaces for spontaneous interaction and weak-tie formation
• Design principles for building shared identity through language, rituals, humor, art, and artifacts
• Concrete examples they can adapt to strengthen culture on remote and hybrid engineering teams
• A new diagnostic question: if the building disappeared tomorrow, what about your culture would still be there next month?
This session is grounded in anthropology, systems thinking, and more than two decades of engineering leadership, and is designed for leaders who want remote and hybrid teams to do more than function - they want them to feel like communities people genuinely want to belong to.
Most advice about difficult conversations starts too late. It assumes you already know which conversation you need to have.
But what if you're debugging the wrong problem?
Robert Harris draws on 25 years of engineering leadership — and an earlier career in psychology and anthropology — to examine the human systems underneath the conversations leaders avoid, mishandle, or never realize they need to have. Using real stories from his career, from a production outage to a board asking, “How many developers do we need to fire?“, he'll show why the conversation that looks obvious on the surface is often very different from the real one underneath.
Because before you can have the difficult conversation, you have to find it.
This 60-minute session borrows the engineer's own mental model: debugging.
Humans won't show you their internal state, call stack, or debug log, so engineering leaders have to work from the signals the system actually gives them. Robert introduces three forces operating underneath difficult conversations - power, risk, and reward - and three signals that appear when those forces get out of balance: silence, conflict avoidance, and withdrawal.
Then he puts the model to work.
Through real conversations from his career, attendees will debug what happens when a leader accidentally teaches a team to stay silent, when a promotion changes relationships with former peers, when a boss makes uncertainty dangerous during a production incident, and when a valued employee has already decided to leave - whether either person is ready to admit it yet.
Each conversation becomes a debugging session: inspect the inputs, read the hidden signals, identify the strongest forces, and test the assumptions behind the apparent problem. Sometimes the assertion passes. Often it fails. And sometimes the first difficult conversation you need to have is with yourself.
Attendees will leave with:
Whether the conversation is with your team, your boss, or yourself, the goal isn't to become fearless about conflict. It's to stop solving the wrong problem because you never found the real conversation.
AI has increased what your team can produce. Which means more output to review, more decisions to make, more places where everything runs through you. The leverage is real — and so is the growing pile of work that was supposed to be off your plate. Part of that is systems. But a bigger part is the pull to just do it yourself — because it's faster, because it's easier than explaining it, because if something goes wrong you want to have been the one who touched it last. That pull is costing you. Not just time — the kind of work you actually want to be doing, and the headspace to do it well.
This is a working session — you'll work through real delegation situations, yours or someone else's, and learn as much from the people in the room as from the content. You'll leave with the skills to hand off work with trust, clarity, and accountability — one concrete delegation you've been avoiding, with a plan to execute in upcoming week, and the foundation to keep building on it. Less bouncing back to your desk. More of your time on the work that only you can do. The kind of leader whose team actually runs without them in every conversation.