JavaMUG at Dallas/Plano AI Agent tools meetup w/ Meta, Netflix, Spotify, and Moderne
Erik Weibust
Agent Tools at Scale
Now that the industry has figured out code generation with AI, what about the other billions of lines of old code that large enterprise software organizations have that are blocking innovation and shipping software at scale? Enterprise teams face a ubiquitous problem with coding assistants: how to safely evolve massive codebases. Join us for this half-day, in-person event to learn how the leading large software organizations are leveraging agent tools to manage, modify, and maintain large code bases at scale with AI.
📍 JPMorgan Chase & Co., 8181 Communications Parkway, Building C, Plano, TX
📅 Thursday, August 20, 2026, 1:00–6:00 PM Central
🎟️ Free to attend, registration required.
Save your spot: https://lnkd.in/gD3QYpGq
Agenda
1-2pm Registration and Networking
2-3pm Talks 1-2
3-4pm Talks 3-4
4:15-4:45pm Panel
4:45pm-6pm Networking and Happy hour
Talk 1
Diff Risk Score: AI-driven risk-aware software development
By Rui Abreu, Research Software Engineer, Meta
Software development in the era of AI is fraught with risk, especially in rapidly evolving large enterprise software organizations. In this talk Rui and Nachi share the tools Meta has implemented to mitigate risk. Specifically, Meta has developed, deployed, and enforced Diff Risk Score (DRS) and other code health metrics to tackle production risk. Equipped with a model that predicts if a code change might cause a product customer disruption, Meta developers can build features and workflows to improve almost every aspect of writing and pushing code. Today, DRS powers many risk-aware features that optimize product quality, developer productivity, and computational capacity efficiency. Notably, DRS has helped us eliminate major code freezes, letting developers ship code when they historically could not with minimal impact to customer experience and the business.
Talk 2
Scaling code health with always on rewrites and AI
By Jonathan Dahl, Spotify
Managing thousands of components across millions of lines of code is a massive challenge. At Spotify, we moved from manual multi-month migrations to a fleet-first mindset, using tools like OpenRewrite and AI-powered background coding agents to run automated, daily code refactorings and infrastructure optimisations.
This talk covers how we scaled to over one million automated changes, our evolution from deterministic recipes to agentic loops, and how we use test automation and LLM judges to maintain quality.
Talk 3
Dev Tools or Agent Tools?
By Jonathan Schneider, CEO and co-founder, Moderne/OpenRewrite
As AI agents become the primary consumers of engineering tooling, optimizing tool-call speed, accuracy, and token efficiency is becoming a critical lever for software delivery. Small improvements can compound across fleets of coding agents and foundation models.
This talk examines practical techniques for tightening agent feedback loops, including trigram-based code search, lossless semantic tree access, chat transcript mining, and exposing multi-repository development activity to agents.
Talk 4
Netflix’s Journey to Confident Automated Changes
By Aubrey Chipman, Sr. Software Engineer at Netflix
How do you safely deploy automated changes across thousands of repositories in hours instead of weeks? This talk shares how Netflix transformed code and dependency updates into a fully automated, zero-touch process through scalable dependency management, automated source control changes, and end-to-end observability. We’ll also explore how validation data, feedback loops, and impact analysis help build developer trust in automation, enabling rapid platform-driven changes while maintaining quality and reliability at scale, along with lessons for organizations looking to accelerate automated change management with confidence.
Rooz Mohazzabi
Vice President of Strategic Accounts
Moderne, Inc
E: Ro...@Moderne.io
M: 6502480070
Erik Weibust
This one has been tested and works:
https://moderne.ai/events/agent-tools-at-scale-plano