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Michael Rishi Forrester

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 thirty years of operational experience across Red Hat, ThoughtWorks, AWS, and KodeKloud, and I bring both sides into every talk. My work centers on Agentic Covenants, a governance model for autonomous systems built on one premise: guardrails enforced by the AI tool are bypassable, guardrails enforced by infrastructure are not.

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

Governing MCP for a Workforce the Size of a City Deploying the Model Context Protocol across a workforce of roughly 750,000 people, and what governing that actually requires. Keynote at MCP Dev Summit Toronto, Tuesday 6 October 2026. The keynote page carries the abstract, the slot and registration. The keynote's own site is mcp.michaelrishiforrester.com.

CNCF Bingo: Play, Learn, Win!!!!!! Twelve minutes in the Cloud Native Theater built on CNCF Bingo, a bingo card of CNCF projects described by what they actually do. KubeCon + CloudNativeCon North America, Salt Lake City, Tuesday 10 November 2026.

BurritoBot Said Let's Dance, the Platform Said No With Whitney Lee. Platform security and guardrails for a customer-facing agent, starting from the developer who asked a burrito chain's chatbot to reverse a linked list before ordering. KubeCon + CloudNativeCon North America, Salt Lake City, Thursday 12 November 2026.

Deploying Agents at Scale: What Enterprise Adoption Actually Looks Like What enterprise agent deployment looks like once it leaves the demo: the adoption curve, the governance boundary, and the failures that only appear at scale. Invited talk at Agentic Engineering Days Zurich, Friday 20 November 2026.

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. Given at devopsdays Atlanta 2026.

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. Given at LLMday Austin, May 2026.

The 90-Minute IDP: AI Ate My Implementation A live build of an Internal Developer Platform with an AI coding agent driving, scored component by component against real platform engineering criteria. Part demo, part assessment of where AI speeds platform work up and where it falls apart. Given as a 90-minute workshop at KCD Texas, Austin, Friday 15 May 2026. The write-up is here.

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

The full record, delivered and forthcoming, is kept in the speaking tracker, a document that is updated in place so its link never changes.

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.

You can also reach me on LinkedIn or Bluesky.

Workshops

A workshop room at DevOpsDays Portland 2026, attendees on laptops, Michael at the screen running the Unleash an Agent exercise with Whitney Lee at right

Upcoming

Appearances

53 indexed, grouped by role.

Writing (27)

Speaking (16)

Hosting (7)

Podcasts & Interviews (2)

Promotion (1)

For organizers

What a program chair or a producer usually asks for, in one place: a headshot, a bio at the length the program needs, and where a booking goes.

Headshots

Name and title

Michael Rishi Forrester, AI Workforce Transformation Lead, Accenture LearnVantage

Short bio

Michael Rishi Forrester is the AI Workforce Transformation Lead at Accenture LearnVantage, where he works on Claude and generative AI adoption with governments and forward deployed engineers. With nearly 30 years in technical leadership, workforce transformation, and artificial intelligence, his work centers on enterprise AI governance and adoption and on closing the gap between what executives expect from AI and what AI can actually deliver.

Standard bio

Michael Rishi Forrester is a generative AI strategist with nearly 30 years in technical leadership, workforce transformation, and artificial intelligence. He is the AI Workforce Transformation Lead at Accenture LearnVantage, where he works on Claude and generative AI adoption with governments and forward deployed engineers. He has trained more than a million engineers through every major platform shift, wrote Agentic DevOps with Claude Code (Packt, 2026), and authored the Agentic Covenants, a framework for AI agent safety. He speaks regularly at AI Engineer World's Fair, Linux Foundation AI Con, and MCP Con. His work centers on Claude and its ecosystem, specifically Claude Code, enterprise AI governance and adoption, and closing the gap between what executives expect from AI and what AI can actually deliver. His view is that the biggest blocker to AI adoption is people and process, not which model you use, but he will still wax poetic about Context Rot and other technical concepts if you let him.

Booking

Session catalog and requests through Sessionize. Anything else by email at michaelrishiforrester@gmail.com.

Hear about the next talk

New talks, recordings and workshops, by email, a few times a year.