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Building Agent-Friendly CLIs - What we learned at Checkly

Building Agent-Friendly CLIs: Why Your AI Agent Already Loves the Checkly CLI Stefan explains why products, docs, and CLIs must be AI-ready as coding agents rapidly become primary users of the Checkly CLI. He outlines key CLI features for agent workflows: Stefan demos how an agent initializes project-tailored Checkly setup from scratch without any human intervention and also shows how agents can entirely automate the incident life cylce from resolution to status page communication.

Your "clean code" is costing the company millions #speedscale #darkcode #coding #aiagents #claude

If it passes the tests, it’s not my problem. If you’re still manually checking every line of code in 2026, you’re just wasting company time. Let the AI cook and go touch some grass. Check out: speedscale.com.

AI vs. Hype: Redefining Engineering Excellence with Ron Miller

In this episode of "ShipTalk: Engineering Excellence," host Thomas Dockstader sits down with Ron Miller, editor at Fast Forward, to discuss the real-world impact of AI on software development. They dive deep into the maturity of AI-driven code, the rise of the "citizen developer," and why traditional writing and communication skills are becoming the new must-have for modern engineers.

Beyond the Prompt: AI Agent Design Patterns and the New Governance Gap

If you are treating Large Language Models (LLMs) like simple question-and-answer machines, you are leaving their most transformative potential on the table. The industry has officially shifted from zero-shot prompting to structured AI agent design patterns and agentic workflows where AI iteratively reasons, uses external tools, and collaborates to solve complex engineering problems.

Grave improvements: Native crash postmortems via Android tombstones

Native crashes on Android have always been harder to debug than they should be. The platform has its own crash reporter (debuggerd) that captures the crashing thread, every other running thread, register state, and memory maps into a file called a tombstone. Tombstones have been a part of Android for a long time; in fact, they’ve been there in one form or another since Android's first commit.

What Is an AI SRE? And Why Do They Need Live Runtime Evidence?

AI SREs are autonomous systems that handle incident triage, root cause analysis, and remediation by correlating logs, metrics, traces, and code signals. However, as they rely on pre-configured telemetry, the critical execution details of a specific failure, such as variable state and code paths, can often be missed. As a result, they either force users into manual redeploy loops or make inferences from partial data, diagnosing issues using probability rather than proof.