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Merge pull request #15776 from DevOpsDaysNashville/main
[NSH-2026] Program and sponsor updates (#36)
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‎assets/events/2026-nashville/speakers/chris-lee.png‎

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‎content/events/2026-nashville/program.md‎

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Title = "Program"
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Type = "program"
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Description = "Program for devopsdays nashville 2026"
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Icons = "false"
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<div class = "row">
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<div class = "col">
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<hr />
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If Open Space is new to you, you may be interested in <a href="/pages/open-space-format">more details about Open Space</a>.
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<hr />
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<i>All times are in US Central Time</i>
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</div>
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</div>

‎content/events/2026-nashville/program/camilla-martins.md‎

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Talk_date = ""
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Title = "Bridging the Gap: Empowering AI Agents with Docker and MCP (Model Context Protocol)"
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Type = "talk"
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Speakers = ["camilla-martins"]
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AI agents are limited by what they can 'achieve'. Discover how the Model Context Protocol (MCP) combined with Docker allows LLMs to securely interact with development environments, local tools, and infrastructure. Learn how Docker is becoming the standard runtime for providing context and real-time execution capabilities for the next generation of AI agents.

‎content/events/2026-nashville/program/chris-lee.md‎

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Talk_date = ""
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Title = "I Vibe Coded an App. Now What?"
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Type = "talk"
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Speakers = ["chris-lee"]
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You used AI (Cursor, vibe coding) to build an app. Then you hit the wall: Now what? It needs a URL, auth, CI, and a way to find bugs before users do. This talk presents a repeatable “day two” checklist for moving to production: hosting on Vercel, DNS, data with Airtable, authentication with Clerk, GitHub for PRs and review, and GitHub Actions for lint and test on every push. We use git hooks (Husky) so the same test suite runs locally before every push, and Cursor agents to find issues, running “find bugs,” “check for auth leaks,” or “review this diff” so the AI does the first pass before human review. The DevOps connection: AI got us to “working code” fast; the same tooling (Cursor + agents) and pipeline (GitHub + Actions + Vercel) get us to deployed, reviewed, and maintainable without throwing away the vibe. Principles in play: automation (CI, cron, agents, hooks), feedback loops (PRs, tests, agents), and security by default (Clerk, env vars, CRON_SECRET)
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Key Takeaways
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“I vibe coded an app” is only half the story. The other half is hosting, auth, DNS, CI, and review.
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We use Cursor agents for finding issues; GitHub + Actions for PRs and CI; Husky so the same tests run locally; Vercel for hosting, Clerk for auth, and Airtable for data.
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The same AI that helped build the app now helps operate it through continuous "review assistance."
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The test suite is the same everywhere: run by git hooks before push, run by GitHub Actions on every push/PR, and required before merge so deploys are safe.
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‎content/events/2026-nashville/program/elissa-shevinsky.md‎

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Title = "Stress-Testing AI Agents: Red Teaming to Reduce Operational Chaos"
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Type = "talk"
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Speakers = ["elissa-shevinsky"]
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AI agents are now part of our automation layer, calling tools, modifying systems, and influencing production workflows. Unlike traditional automation, their behavior can be unpredictable under pressure. This talk explores how we stress-test AI agents embedded in production systems using red teaming techniques to surface hidden failure modes and operational risks before they escalate into customer-facing incidents.
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‎content/events/2026-nashville/program/michael-anthony.md‎

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Title = "The AI Augmented Student"
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Type = "talk"
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Speakers = ["michael-anthony"]
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‎content/events/2026-nashville/program/mike-noe.md‎

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Talk_date = ""
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Title = "AI in Action! SDLC Agents using LangChain+LangSmith in an Azure Environment."
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Type = "talk"
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Speakers = ["mike-noe"]
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You've heard the hype, seen the videos, and read all the posts on social media. Now it's time to see AI in Action. Our own Mike Noe will guide us through an implementation on SDLC Agents using LangChain and LangSmith in an Azure Environment.
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The demo will showcase a multi-agent pipeline that utilizes Azure ServiceBus to manage interactions between agents.
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I use LangSmith for the tracing and observability aspect. Tracking calls, latency, and costs.
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The purpose is to show how we can build isolated agents that work together, much like real folks.

‎content/events/2026-nashville/program/reserved.md‎

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Title = "Coming Soon!"
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Type = "talk"
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Speakers = ["reserved"]
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‎content/events/2026-nashville/program/robert-hoffman.md‎

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Title = "Keynote Day One"
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Type = "talk"
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Speakers = ["robert-hoffman"]
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‎content/events/2026-nashville/program/scott-stroz.md‎

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Title = "Smart Scaling: Leveraging AutoPilot for Efficient MySQL Deployment "
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Type = "talk"
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Speakers = ["scott-stroz"]
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MySQL HeatWave AutoPilot brings machine learning directly into the heart of MySQL HeatWave AutoPilot introduces machine learning directly into the core of database operations, transforming how teams provision, load, tune, and scale MySQL environments. This session explores how AutoPilot’s intelligent automation covers auto provisioning, auto parallel loading, and auto data placement. These features eliminate guesswork, predict optimal configurations, and accelerate performance with minimal manual effort.
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We will examine real-world scenarios that show how AutoPilot adapts instantly to shifting workloads, boosts query execution, and maintains high availability while reducing operational overhead.

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