Quarkus at WeAreDevelopers NA 2026

[insectengine]

Event Description: WeAreDevelopers World Congress: developers, engineering leaders, and the people building production AI systems.

Date: September 23–25, 2026·
Location: San José, CA
Event Type: In-Person

https://www.wearedevelopers.com/world-congress-north-america

Sessions

Session: Reinventing Testing Practices in the AI Era
Speaker(s): Eric Deandrea
Date/Time: TBD
Abstract: AI-infused applications demand a rethinking of our testing practices. Developers face a new class of challenge as LLMs become standard integration points in modern applications: non-deterministic behavior that traditional testing approaches were never designed to handle. The current wave of distributed, orchestrated, agentic AI systems is evolving fast and, if we're being honest, it smells a lot like the early days of microservices.
In this session, we'll explore how your DevOps and testing practices must evolve when you wire AI into your applications. Not all AI failures look the same, and recognizing the difference is the first step toward building systems you can actually trust. We'll walk through practical testing and observability strategies, using open source tools that give you confidence in AI-infused applications at every layer of the stack.
You'll leave with a concrete mental model for reasoning about AI failures and one grounding question: What if AI was just an API call?

Session: From Static Rules to Reasoning Platforms: Scaling Intelligent Canary Delivery in 2026
Speaker(s): Daniel Oh
Date/Time: TBD
Abstract: As organizations scale their Kubernetes footprint, the "Day 2" reality of GitOps becomes clear: static thresholds are brittle. Standard Canary rollouts rely on fixed Prometheus queries (e.g., Error Rate < 1%), but these rules lack the context to distinguish between a minor transient blip and a systemic failure. For Platform Engineers, this results in "Alert Fatigue" and manual "promotion" gates that slow down the delivery pipeline.
In 2026, we are moving from Static Automation to Reasoning Platforms.
This session explores how to evolve your delivery infrastructure into an intelligent system that doesn't just follow rules, but reasons through data. We will demonstrate how to wrap ArgoCD Rollouts with an Agentic Reasoning Layer capable of cross-referencing metrics, logs, and distributed traces to make autonomous "Go/No-Go" decisions.
We will trigger a Canary deployment that passes basic health checks but introduces a "silent failure" (e.g., a cache hit-rate drop causing downstream latency). You will see the Reasoning Platform detect the anomaly, pause the rollout, "investigate" the root cause, and present a natural-language justification for the automated rollback.

Session: Agents That Actually Work: From AI Prototype to Production with IBM Bob
Speaker(s): Daniel Oh
Date/Time: TBD
Abstract: Building an AI agent is easy. Making several agents collaborate safely, predictably, and efficiently in a real application is the harder engineering challenge.

In this session, you will follow an incident management case study built with IBM Bob. A live demo will show specialized agents triaging an incident, assessing business impact, planning a resolution, invoking tools, and coordinating decisions through a supervisor. You will see how human approval protects critical actions and how distributed tracing makes agent behavior, tool calls, latency, and failures visible.

We will also demonstrates how IBM Bob uses a concise project context file to understand architecture, follow team conventions, generate consistent code, and avoid inventing APIs that do not exist. Along the way, we will examine where agent workflows commonly break, how to choose between sequential, parallel, and supervisor based coordination, and how to control context and token usage without sacrificing quality.

Key Learnings
 1. Design reliable workflows involving multiple specialized AI agents.
 2. Select sequential, parallel, or supervisor coordination for each use case.
 3. Apply human approval and tracing to make agent decisions safer and observable.
 4. Use IBM Bob with concise project context to produce consistent, governed code.

You will leave with reusable design patterns, practical governance tips, and a clear path for turning an agent prototype into a system that operations teams can understand, test, and trust.