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Debug AI agents wherever they run, from Slack bots to code review with Sentry's Agent Tracing

Agent Tracing shows the full execution path of an AI agent: the model call, every tool invocation and its arguments, token counts, cost, and the span where it broke. Same traces and spans you already use, with agent-specific attributes on top. Serge walks through three apps — a Next.js e-commerce agent using the AI SDK with a failing tool call, a Slack bot built with Eve that orders lunch, and a code review agent built with Flue over MCP.

Run an AI SRE Agent Entirely Inside AWS with Bedrock and S3: AURA

An on-call question returns the threshold and the escalation owner from your own runbooks, and the answer comes back without a call to anyone outside. AURA runs against Bedrock as its model provider, using Claude Sonnet 5 served by AWS in the same region. Authentication is the normal AWS credential chain: a profile on a laptop, an IAM role in EKS.

Backspaces, Retypes, and Idle Time: The Small Signals That Make a Draft Look Genuinely Written

A backspace that fixes a typo. A five-second pause before a hard sentence. A word typed, deleted, and replaced with a better one. A cursor that sits idle for two minutes while the writer stares at the screen. None of these moments feel significant while they are happening. They are the ordinary texture of writing, so automatic that most writers never notice them. But together, they are what separates a document that reads as genuinely drafted from one that reads as simply deposited.

The EU Is Starting to Put Labels on the Synthetic Internet

It's getting harder and harder to distinguish between content produced by people and content produced by machines on the internet. AI can now create convincing articles, images, audio and video that may not be immediately recognized as being AI-generated. Europe has decided that this uncertainty cannot be left to users to deal with on their own. The EU AI Act introduces new transparency obligations, which are beginning to establish a more structured framework for identifying synthetic content.

What is going wrong with AI coding? Live Laugh Logs ep. 4

Welcome to Episode 4 of Live Laugh Logs, the podcast from the Coralogix Developer Relations team. This week, Chris Cooney joins Annie to share five key DevOps skills that have become even more important in the age of agentic code development, and gives you five key actions you can do today to start levelling up these skills. Subscribe to our channel for more insights into observability and AI.

Builder in the loop: what production agents were missing before AURA

Builder in the loop is a Mezmo interview series with the engineers, product leaders, and operators shaping AURA. Each installment looks past the product layer to explore the decisions, tradeoffs, and lessons involved in building agents for real production work. This installment features Mike Shearer, the engineer who built AURA and, until recently, its only developer. AI agents are easy to believe in when the task is small.

What an AI SRE agent actually finds when you point it at a broken Kubernetes cluster

‍ Most of the AI features that shipped into observability tools this year summarize alerts. You get a paragraph that restates the dashboard you were already looking at, and the agent never reads the cluster itself, because giving it cluster access is a security conversation nobody wanted to start. This walkthrough starts it.

Better context, smarter testing: How to give your AI coding agent direct access to k6 docs

As testing workflows become more AI-assisted, fast access to accurate documentation matters more than ever. Whether you're writing a new load test, troubleshooting an issue, or having an AI agent generate a script for you, you need reliable guidance that keeps pace with the way you work. But most documentation still lives in a browser. Every time you or your agent needs to verify an API or look up a best practice, you're forced to leave your terminal or editor and interrupt your workflow.