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AI Agents Write Broken Code 49% of the Time #speedscale #AI #Coding #Tech #DevOps

Jul 1, 2026 By Speedscale In Speedscale
AI agents write broken code nearly 50% of the time. By adding a traffic-based deterministic evaluation, Speedscale boosted unsupervised bug-fixing quality from 51% to 77% in just 5 minutes. This helped slash token costs and eliminate rework without human intervention. Learn more: speedscale.com.
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speedscale

The Three Pillars Were Built for Humans

Jun 30, 2026 By Matthew LeRay In Speedscale
It was 2am and I was paying for the privilege. Something was on fire in production, and I’d done the modern thing: I pointed an AI agent at it. It ingested the dashboards. It read the logs. It walked the traces. Then it handed me back a beautifully formatted paragraph that said, in effect, “latency is elevated on the checkout path.” I knew that. The page told me that.
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speedscale

Which Bugs AI Agents Fix Better With Traffic

Jun 29, 2026 By Ken Ahrens In Speedscale
In the first experiment, I wanted a baseline: if an AI coding agent gets the same production signal a human would get, can it fix bugs in a codebase it has never seen? Yes, but only when I gave it better context. With only an alert, the agent passed 51% of the runtime tests. When I added captured traffic, the actual request and response for the failing call, it climbed to 77%. This post is the second pass.
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statusgator

Monitor metrics now available in the v3 API

Jun 24, 2026 By Colin Bartlett In StatusGator
Monitor metrics are now available through the StatusGator v3 API for both Website Monitors and Ping Monitors. These endpoints provide the same latency and performance data available in the Monitor Metrics tab, making it accessible through the API and MCP server. You can find the endpoints in the API documentation.
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speedscale

Five things your logs will never tell you

Jun 22, 2026 By Matthew LeRay In Speedscale
A customer escalation hit my queue when I was on the customer smoke jumpers team at an observability vendor. My team was the group that parachutes into Fortune 500 accounts one bad week from churning and usually after a big customer outage. The customer had filed a billing dispute three weeks earlier and their on-call engineers were stuck. They had our full stack: logs, metrics, traces, end-to-end instrumentation, every product we sold and some we didn't. They could see the request came in. They could see it returned a 500. They could not see the body. The trace was sampled out. The log line was truncated at 4KB.
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