Operations | Monitoring | ITSM | DevOps | Cloud

Debugging multi-agent AI: When the failure is in the space between agents

I've been building a multi-agent research system. The idea is simple: give it a controversial technical topic like "Should we rewrite our Python backend in Rust?", and three agents work on it. An Advocate argues for it, a Skeptic argues against, and a Synthesizer reads both briefs blind and produces a balanced analysis. Each agent has its own model, its own tools, its own system prompt. It worked great in testing. Then I noticed the Synthesizer kept producing analyses that leaned heavily toward one side.

A Prototype's Worth 1,000 Minutes: How Claude Prototypes Accelerate The Product Planning Process

The relationship between product managers (PMs) and engineers is due for an upgrade. The division between these personas is responsible for a healthy, if laborious, collaboration when envisioning and building new products. A PM generates the vision; engineers translate it into an architectural approach, raising the technical questions that sharpen it along the way. This back-and-forth eventually produces tight alignment, a solid PRD, and functional code.

You're Running Agents. Your Tooling Is Still Catching Up.

Introducing GitKraken Desktop 12.0. At some point in the last year, the question shifted. It stopped being “should I use AI coding agents?” and became “how do I run more than one at a time without losing my mind?” If you’ve been there, you know what the management layer looks like. A terminal per agent. A worktree created by hand before each session.

Route OTel data from AI apps to ClickHouse and Datadog using Observability Pipelines

As organizations continue to heavily invest in AI and build more agentic workflows, their telemetry data volumes can surge quickly, and the associated costs can become unpredictable. To regain control of their data, many AI-forward teams are turning to high-throughput, low-latency pipelines to collect and route data to tools such as OpenTelemetry (OTel) and ClickHouse. But these self-hosted solutions come with drawbacks.

Auto-Generate Tests for Your Codebase with AI (CircleCI Chunk Tutorial)

AI coding tools help you ship features faster than ever, but test coverage often can't keep up. In this video, we show you how CircleCI's Chunk autonomous CI/CD agent finds untested code in your codebase, writes tests to cover it, and opens a pull request for your review. What you'll learn: Chunk works directly inside your CI/CD pipeline, giving it access to your build history, test results, and coverage reports. That means smarter tests, not just more tests.

Sentry Built AI Dashboards: Monitor Your AI Agents End-to-End

Building AI applications? There's a lot more to monitor beyond errors. With tracing enabled, Sentry's built-in AI Dashboards give you deep visibility into how your agents are actually performing. This video walks through three key dashboard views: You'll also see how to drill from a dashboard widget straight into the trace explorer to pinpoint the root cause of errors, how to duplicate and customize dashboards to fit your needs, and how to set up monitors with alert thresholds - like getting notified if your LLM calls exceed 20 seconds.

In the Age of AI, Taste Isn't About Aesthetics

AI can generate a UI in seconds. So what do designers actually bring to the table? Marcela, Principal Product Designer at Rootly and former Founding Designer at Ramp, has spent 20 years in design. Her answer: taste isn't about aesthetics or crafting pleasant interactions. It's about asking the uncomfortable questions, and choosing the right problem, not the easiest one.

What Parents Should Know About AI Essay Grader Tools

Artificial intelligence is showing up in more classrooms than ever before, and parents are right to have questions. One area that has grown quickly is AI-powered writing assessment. Schools and teachers are increasingly turning to automated tools to help manage the workload of grading student essays, and while this might sound like a behind-the-scenes administrative change, it directly affects how your child receives feedback on their writing. Understanding what these tools do, how they work, and what they cannot do will help you stay informed and involved in your child's education.

Why Gaming Studios Are Using AI Video Generators for Trailers and Promotional Clips

The gaming world thrives on anticipation. Before a player ever downloads a game, watches a stream, or reads a review, they experience one thing first, the trailer. It's the spark. The hook. The moment that determines whether someone clicks "wishlist" or scrolls past. But here's the reality: traditional trailer production is slow, expensive, and often rigid. In an industry where hype cycles move at lightning speed, that's a problem.