Speaking
Speaking
I talk about what happens when AI meets production infrastructure. Most AI strategists don’t know how production systems work. Most infrastructure engineers haven’t reckoned with how AI changes their job. I sit at that intersection, with 25+ years of operational experience across Red Hat, ThoughtWorks, AWS, and KodeKloud, and I bring both sides into every talk.
I speak at conferences ranging from KubeCon and CNCF events to devopsdays, SREday, and enterprise leadership summits. Available for keynotes, breakout sessions, panels, and workshops.
Active Talks
The Day Claude Code Deleted My Cluster: A Cautionary Tale About AI Guardrails What happens when an AI coding agent gets root access to a Kubernetes cluster with no safety net? I ran the experiment so you don’t have to. This talk walks through the real incident, the eight infrastructure-level guardrails that would have stopped it, and why the AI tool’s built-in safety features are not enough.
Your MLOps Pipeline Is Your Agentic AI Guardrail AI agents are moving from chat windows into CI/CD pipelines and infrastructure automation. The same MLOps patterns you already use for model deployment (staged rollouts, monitoring, rollback) are the guardrails that keep agentic AI from doing damage in production.
The 90-Minute IDP: AI Ate My Implementation A live-build session where we stand up an Internal Developer Platform using AI-assisted tooling, then score what’s left against real platform engineering criteria. Part demo, part honest assessment of where AI accelerates platform work and where it falls apart.
The Platform Engineer’s Guide to AI Safety AI safety isn’t a new discipline. It’s tiered security controls, policy-as-code, and defense in depth wearing a new hat. This talk maps Anthropic’s Responsible Scaling Policy and Constitutional AI directly onto Kubernetes admission controllers, OPA/Kyverno policies, and the infrastructure patterns platform engineers already use.
AI Replaced Coding. It Didn’t Replace Engineering. The implementation layer is dissolving. AI can write code. It cannot define requirements, evaluate tradeoffs, or own outcomes. This talk covers what engineering work actually looks like when the typing part gets automated, and why the engineers who adapt will be more valuable, not less.
The AI-Driven Development Life Cycle (AI-DLC) AWS published a methodology that reimagines how engineering teams build software with AI as the primary driver of execution. I break down what AI-DLC actually is, how it differs from the ML Development Lifecycle tested in AWS certifications, and what the early adoption data from Wipro, Hitachi, and Panasonic tells us about where this is headed.
Workshops and Bootcamps
Claude Code Bootcamps
I run hands-on Claude Code bootcamps for teams ranging from individual contributors to enterprise platform organizations. Current workshop offerings include:
Engineering Workflows for Claude Code — How to build CLAUDE.md files, hook configurations, and permission boundaries that make Claude Code productive without making it dangerous. Covers the difference between a prompt and a workflow, and why most teams get this wrong.
Kubernetes and Terraform with Claude Code — Building Kubernetes manifests and Terraform configurations using Claude Code as the execution layer. Covers how to structure projects so Claude Code produces reviewable, deployable infrastructure instead of plausible-looking garbage.
Wrapping the Probabilistic in the Deterministic — The core safety pattern for Claude Code in production. Deterministic checks (linting, scanning, validation) run first. Claude Code handles the parts that require comprehension. Deterministic checks run again on the output. How to build this pipeline and why skipping it costs you more than the time you saved.
Claude Code in Government and Enterprise Settings — Deploying Claude Code under compliance constraints. Covers data residency, audit logging, FedRAMP considerations, acceptable use policies, and how to structure Claude Code usage so your security team signs off instead of shutting it down.
Claude Code with Amazon Bedrock — Integrating Claude Code into AWS environments using Bedrock as the model backend. Covers API configuration, guardrails integration, cost management, and when Bedrock is the right choice versus direct API access.
Additional Workshop Topics
AI-Driven Development Life Cycle (AI-DLC) Workshop — Hands-on implementation of AWS’s AI-DLC methodology. Teams work through the Inception, Construction, and Operations phases on a real project, using AI coding agents as the primary driver while maintaining human decision authority at every checkpoint.
AI Guardrails for Platform Engineers — Building infrastructure-level safety controls for AI workloads in Kubernetes. Covers admission controllers, network policies, agent sandboxing, and the eight guardrails framework.
Workshops range from half-day to full-day, tailored to team size and experience level. If you’re interested in combining a talk with a workshop, reach out.
Podcasts
AI Inevitable — Exploring how artificial intelligence is reshaping engineering, organizations, and the people doing the work. Conversations with practitioners, founders, and the people building and operating AI systems in production.
The Performant Professionals — Long-running conversations on career growth, engineering leadership, and what it means to operate at a high level in technology.
2026 Speaking Calendar
- KubeCon EU Amsterdam (March 2026) — Multiple sessions including KubeAuto AI Day
- devopsdays Atlanta (April 21-22, 2026)
- ASU+GSV Summit, San Diego (April 12-15, 2026)
- SREday Austin (May 11, 2026)
- LLMday Austin (May 12, 2026)
- KCD Texas (May 15, 2026)
Past Speaking
KubeCon, KCD events, Cloud Native community webinars, and enterprise training engagements across AWS, Coursera, O’Reilly, and YouTube. Over 1 million engineers trained across platforms.
Book Me
Browse my full session catalog and submit a speaking request through Sessionize.