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Shipping trustworthy code with Chunk CLI

Apr 24, 2026 By Roger Winter In CircleCI

AI coding agents are fast. They generate functions, refactor modules, and wire up boilerplate faster than any human. What they don’t do by default is enforce the conventions a specific team has agreed on: the lint rules, the review patterns that senior engineers flag on every PR. A generated diff looks clean until someone runs CI or reads it carefully.

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Sentry + Claude Agents: Automatic Bug Fixes from Root Cause to PR

Apr 24, 2026 By Sentry In Sentry

Seer, Sentry's AI debugger, automatically analyzes your issues and finds the root cause. Now you can pass that analysis directly to a Claude agent - a managed agent session in the Claude Console at platform.claude.com. Once it's done, a link to the branch appears in Sentry so you can review and merge the PR. This video walks through how the integration works and how to set it up in under two minutes.

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The Claude Bill is Too Damn High #speedscale #claude #aiagents #aicoding #devops #llms

Apr 24, 2026 By Speedscale In Speedscale

Stop overpaying for AI reasoning by trading expensive GPU cycles for efficient, deterministic testing. This video explores how tools like linters and traffic replay can complement Claude, helping you fix bugs more accurately while cutting token usage by up to 50%. Visit: speedscale.com to learn more.

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Speedscale

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How Diffusion Transformer Models Power Hyper-Realistic AI Avatar Videos

Apr 24, 2026 By OpsMatters In OpsMatters

The AI avatar videos from a year ago still had a tell. The mouth movement was a little off, the facial expressions were a bit stiff. It was a quality that made it obvious that you were looking at a digital human and not a real one. The uncanny valley issue was not a small aesthetic problem, it was the only thing that stopped the practical adoption of anything other than novelty use cases.

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Run Local LLMs on Mac to Cut Claude Costs

Apr 23, 2026 By JT, Matthew LeRay, and Hugh Brien In Speedscale

Part of the motivation for this post is how cloud API economics are shifting: Anthropic is moving large enterprise customers toward per-token, usage-based billing (unbundled from flat seat fees), which makes “always call the API” a moving cost line for teams at scale. A hybrid or local layer is one way to keep spend bounded while you still use premium models where they matter.

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AI for Incident Response: Should You Build or Buy?

Apr 23, 2026 By Snir Amsalem In Komodor

SREs and platform teams are overwhelmed by the effort of manually troubleshooting ever-more complex cloud-native environments. This pain is driving a breakneck adoption of AI SRE solutions that promise to automate core reliability practices, from root cause analysis to capacity planning. For teams with strong engineering talent, creating a DIY AI SRE seems like a straightforward challenge.

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What Is AI Agent Observability? Why Cost Is The Signal You're Missing

Apr 23, 2026 By Keith MacKenzie In CloudZero

Your LLM observability stack probably handles individual model calls well enough. Latency, token counts, error rates, maybe even evaluation scores....

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CloudZero

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Introducing Ubuntu 26.04 LTS | Resolute Raccoon

Apr 23, 2026 By Canonical Ubuntu In Canonical

Ubuntu 26.04 LTS, codenamed, is now available to download. Resolute Raccoon builds on the resilience-focused improvements introduced in interim releases, with TPM-backed full-disk encryption, improved support for application permission prompting, Livepatch updates for Arm-based servers, and Rust-based utilities for enhanced memory safety. This release also brings native support for industry-leading AI/ML toolkits like NVIDIA CUDA and AMD ROCm, making Ubuntu 26.04 LTS the ideal platform for AI development and production workloads.

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AI agents are only as smart as the data you feed it

Apr 23, 2026 By Coralogix In Coralogix

AI is only as useful as the context you give it. An autonomous observability agent can unlock serious value from your telemetry, but only when the foundation is right: good telemetry, a strong data layer, and efficient access to the data. Annie Freeman and Lewis Isaac had a lot to say about this at AWS Summit London this week! hashtag#Observability hashtag#AI hashtag#AWSSummitLondon hashtag#DevOps hashtag#OpenTelemetry.

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Why Mandating AI Tools Backfires on Engineering Teams

Apr 23, 2026 By GitKraken In GitKraken

Responsible AI adoption for engineering teams starts with culture, not compliance. In this GitKon talk, Rizel Scarlett (Tech Lead of Open Source DevRel at Block) shares how Block helped thousands of engineers actually want to use AI tools, including Goose, Cursor, Claude Code, and more, without mandates, vibe coding disasters, or security gaps.

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