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Tales From the Trench: Building With LLMs and Honeycomb
Tales From the Trench: Building With LLMs and Honeycomb

AI discourse these days is all over the place. Depending on who you talk to, AI’s are absolute flash-in-the-pan junk, or they’re the best thing since sliced bread. I want to cut through the noise, though, and see for myself what someone can do out here on the bleeding edge. Thus, I’m setting myself a challenge: write a usable—and useful—application with Claude Code, from soup to nuts.

It's The End Of Observability As We Know It (And I Feel Fine)
It’s The End Of Observability As We Know It (And I Feel Fine)

In a really broad sense, the history of observability tools over the past couple of decades have been about a pretty simple concept: how do we make terabytes of heterogeneous telemetry data comprehensible to human beings? New Relic did this for the Rails revolution, Datadog did it for the rise of AWS, and Honeycomb led the way for OpenTelemetry.

Beyond Shift Left: Engineering Leaders Increase Speed and Resilience With Observability
Beyond Shift Left: Engineering Leaders Increase Speed and Resilience With Observability

We recently had the privilege of hosting several industry experts and technology executives across platform strategy, SRE, and engineering enablement for breakfast at our Observability Day in London. We noted that they’re all facing the same fundamental tension: deliver faster, scale smarter, stay resilient, and somehow get ahead of what’s coming next. But how do you move fast without breaking things? And how do you prove the value of the things you don’t break?