Incident Command for Engineering Leaders

Thursday, 9:30 AM EST

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:

• Reduce time-to-understand and time-to-recover
• Communicate clearly with executives and customers
• Build operational maturity without blame culture
• Replace panic theater with dependable response habits

No panic theater. Just practical leadership patterns that work when production is on fire and Slack has gone feral.

Operationalizing AI: From Prototype to Production

Thursday, 11:00 AM EST

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.

The Operating Limits of Microservices

Thursday, 4:00 PM EST

Reliable systems are not accidents. They are designed with explicit operating limits. This session translates lessons from high-risk domains into practical engineering guardrails for microservices: latency budgets, timeout strategy, retry discipline, concurrency limits, and blast-radius controls.

In high-consequence systems, teams define and respect operating limits. Software teams should do the same.

This session introduces an operating-limits model for modern microservices and platform environments. We’ll map common failure patterns (retry storms, cascading timeouts, queue overload, dependency fan-out) to concrete design and operational constraints that prevent small issues from becoming full incidents.

You’ll learn practical techniques for timeout layering, bulkheads, error budgets, load shedding, progressive degradation, and observability signals that reveal approaching limits before customers feel impact.

We’ll also cover leadership practices: how to align teams around reliability contracts and how to enforce guardrails without turning architecture into bureaucracy.

Outcomes:

• Define service-level operating envelopes
• Reduce cascading failures in distributed systems
• Improve incident prevention with better guardrails
• Balance delivery speed with reliability discipline

Yes, we will talk about when your retries are lying to you. And no, adding one more queue is not always the answer.

Lead Don't Manage

Thursday, 5:30 PM EST

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.

Architecting Your AI-Powered Leadership Operating System

Friday, 11:00 AM EST

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.”

Architecting Your AI-Powered Leadership Operating System

Friday, 1:30 PM EST

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.”

How to Measure Success: Making OKRs and KPIs Actually Work

Friday, 3:00 PM EST

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.