# Honeycomb Blog

## What Comes After Observability?
A year ago, I predicted ways in which AI was about to fundamentally change observability as we knew it. Here's what we've seen happen since—both at Honeycomb and with our customers—and what we're building for the future.

## 30 to 70 PRs a Day: How We Managed to Not Wreck Our Systems
The Honeycomb engineering team set out to double our productivity in a year. This is how we did it, what we did to keep things stable, what it cost us, and what we’re still figuring out.

## Shipping Is Your Company's Heartbeat: A Letter from a CTO
In an open letter to engineering leaders everywhere, Fin CTO Darragh Curran explains that AI isn't a magic wand but rather an amplifier—of the good and the bad—of your engineering practices. And engineering rigor is more important than ever.

## Lattice Watch: Smarter Guardrails for Design System Observability
In the past, I was part of a group of engineers responsible for doing random code reviews with an eye for design system adherence. The design system team had been tracking who used their system the most and invited those engineers to help them review PRs.

## Best AI Observability Tools
Compare the best AI observability tools for tracing, evals, token cost tracking, agent workflows, and production reliability in 2026.

## Instrumenting AI Agents for the Agent Timeline: A Practical OpenTelemetry Guide
The LLM is rarely the root cause of agent failures. This technical guide shows how to instrument AI agents using OpenTelemetry's GenAI semantic conventions so they appear in Honeycomb's Agent Timeline.