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How to measure developer experience (DevEx) in the AI era

As AI coding assistants dramatically inflate PR counts, commit frequency, and lines of code, the limitations of individual output metrics have never been more apparent. A developer can now produce significantly more lines per session, but higher volume doesn’t guarantee that the code is stable, maintainable, or successfully running in production. GitClear analyzed over 200 million lines of code and found that code churn nearly doubled following widespread AI adoption.

The Checkly Playwright Reporter: Live Demo, Rocky AI RCA & Production Monitoring

Your Playwright tests catch bugs. The hard part is figuring out what actually broke — and sharing that context with your team. This session shows exactly how the Checkly Playwright Reporter solves that: one shared home for all your test runs, AI-powered root cause analysis, and a direct path from failing test to production monitor. María de Antón, PM for Playwright features at Checkly, runs a live demo on a real app with real failures.

Zero to Dashboard with Grafana Assistant and the Infinity datasource plugin

Senior Developer Advocate Nicole van der Hoeven demonstrates how to go from zero to dashboard in a few minutes without using any queries, with the help of Grafana Assistant and the infinity datasource plugin for Grafana. Nicole is using the rawg.io video game database API to visualize games and get recommendations for what to play next!

Episode 11 - Human Choices in an AI Future (Part 1)

What if the biggest risk in the AI era isn't the technology, but waiting for someone else to tell you what to do with it? In this episode of The Intelligent Enterprise, host Tom Stoneman sits down with Karthik Ravindran, General Manager of Enterprise Data and AI at Microsoft, to unpack what it really takes to thrive alongside AI, not in spite of it.

The Five Pillars of AI Agent Accountability: A Diagnostic Framework for Engineering Leaders

You’re in a board meeting. The CISO is presenting on AI risk. The CFO asks a simple question: “When that finance agent we deployed last quarter accessed a customer payment record, can we tell who authorized it, what policy permitted it, and produce the full audit trail?” The CISO looks at the head of the platform. The head of the platform looks at security. Nobody answers. If you can picture that meeting happening at your company, you’re not alone.

Decoding design: How design and engineering thrive together in open source

Open source thrives on engineering-driven processes. Fast feedback loops, terminal tools, Git workflows: they’re the lifeblood of how we build software in the open. But for software to truly excel, we need to create user experiences that empower people to use them. I wanted to bring this conversation into the spotlight as part of Canonical’s Open Design initiatives. What better way than at FOSS Backstage 2026 Berlin?

A Runnable Reference Architecture for Industrial IoT on InfluxDB 3

Industrial teams keep telling us the same thing: the data is there, but the stack to act on it isn’t. PLCs, CNCs, SCADA systems, vibration sensors, and quality stations all generate high-frequency telemetry that gets stranded in proprietary historians or stitched together with point integrations nobody wants to own. By the time anyone looks at it, the moment to act has passed.

AI Won't Replace You. Someone Using It Will.

AI isn’t about replacing engineers. It’s about leverage. The teams that win will be the ones that: Triage incidents faster Correlate signals automatically Reduce manual investigation Automate repetitive operational work In observability, that means asking: AI won’t eliminate expertise, it amplifies it. The real risk isn’t AI taking your job. It’s competitors using AI to operate at a speed and efficiency you can’t match.

The New Agentic AI Job Roles IT Leaders Need

CIOs are under pressure from every direction. Budgets remain tight, geopolitical uncertainty is forcing organizations to rethink resilience, and workforce expectations continue to evolve. At the same time, AI is accelerating a broader shift across enterprise IT – changing not only how organizations operate, but also the skills and roles they will increasingly depend on. The question is not whether AI will reshape IT teams, but how quickly organizations can adapt to these new ways of working.

Anthropic Monitoring & Observability with OpenTelemetry and SigNoz

Learn how to implement end-to-end monitoring and observability for Anthropic (Claude) API-based applications using OpenTelemetry and SigNoz. In this video, we walk through instrumenting your Anthropic API calls, collecting traces, metrics, and logs, and visualizing everything in SigNoz to gain real-time visibility into performance, failures, and bottlenecks. You'll see how to move from basic logging to production-grade observability, so you can debug faster, optimize latency, and confidently run Claude-powered AI systems at scale.