AI & LLMs

Evaluating Observability Tools for the AI Era

March 12, 2026

Evaluating Observability Tools for the AI Era

This guide gives you a more rigorous framework for evaluating observability tools in an era where your AI assistant depends on them as much as your engineers do. The criteria that matter most are not the ones that show up first in a sales cycle.

AI & LLMs

Observability

Honeycomb Metrics Is Now Generally Available

March 11, 2026

Toni Chou

Honeycomb Metrics Is Now Generally Available

The tradeoff between data completeness and cost has been a feature of metrics platforms for as long as they’ve been around. And as AI becomes central to how engineering teams build and operate software, it is about to become a much more expensive problem.

March 11, 2026

Observability Where You Work: Introducing the Honeycomb Slackbot in Beta

The Honeycomb Slackbot is available now in beta for Enterprise customers. Reach out to your customer success team to learn more and get set up!

AI & LLMs

Product Updates

Create a Custom Service Health Board With the Honeycomb MCP

March 9, 2026

Jessica Kerr (Jessitron)

Create a Custom Service Health Board With the Honeycomb MCP

The best dashboard is one created just for your application, or your service, or your team. You can get that in minutes with the Honeycomb MCP.

AI & LLMs

Observability

Your Questions About AI-Assisted Development Answered

March 5, 2026

Austin Parker

Your Questions About AI-Assisted Development Answered

We recently hosted a webinar on AI-assisted development with DORA, and the audience had a lot of questions—far more than we could get to in an hour. I picked out six that get at the stuff people are wrestling with day to day.

AI & LLMs

The Next Era of Observability: Founders’ Reflections Additional Q&A

February 19, 2026

Rox Williams

The Next Era of Observability: Founders’ Reflections - Additional Q&A

Charity took the time to answer a few additional audience questions we didn’t get to. Dive in below!

Observability

AI & LLMs

February 17, 2026

Tyler Helmuth

Teaching AI How to Refinery

We released a new tool for our MCP server which helps your AIs understand Refinery, and how Honeycomb handles sampling. In this blog, I’ll walk you through the new feature and show how it can help you run Refinery.

Sampling

AI & LLMs

Happy Birthday to Us: Honeycomb 10 Year Manifesto, Part 1

February 11, 2026

Charity Majors

Honeycomb 10 Year Manifesto: Observability in a World of AI-Generated Code

When we left Facebook, we were determined to build a tool that would help solve the hardest problems in software. Not by copying everyone else’s architectural hand-me-downs and making incremental improvements, but by borrowing from powerful BI and product tools, and reasoning from first principles about what software engineers need to understand their code in production.

Observability

AI & LLMs

How Honeycomb Supercharges OpenTelemetry for AI

February 6, 2026

Fahim Zaman

How Honeycomb Supercharges OpenTelemetry for AI

The nature of software development has changed as AI-code generation and agent-based features gain adoption. In perhaps a more subtle shift, the fundamentals of software instrumentation are changing too.

OpenTelemetry

AI & LLMs

AI in Production Is Growing Faster Than We Can Trust it

January 23, 2026

Fahim Zaman

AI in Production Is Growing Faster Than We Can Trust it

AI reliability and trust is naturally becoming a top-of-mind concern. By 2028, Gartner predicts 40% of organizations will have implemented some form of dedicated AI observability.

AI & LLMs

Measuring Claude Code ROI and Adoption in Honeycomb

January 22, 2026

Mae Capozzi

Measuring Claude Code ROI and Adoption in Honeycomb

Claude Code supports OpenTelemetry out of the box, which means sending telemetry to Honeycomb takes just a few minutes of configuration. In this post, I’ll walk you through exactly how I set this up for one of our monorepos and the insights we gained.

AI & LLMs

January 19, 2026

Jessica Kerr (Jessitron)

Observability with AI? Honeycomb with AI!

Honeycomb exists to help people understand custom software. It doesn’t pretend to know what matters in your application. That’s an interpretive task, not programmatic.

AI & LLMs

“You Had One Job”: Why Twenty Years of DevOps Has Failed to Do it

January 15, 2026

Charity Majors

“You Had One Job”: Why Twenty Years of DevOps Has Failed to Do it

I think the entire DevOps movement was a mighty, twenty year battle to achieve one thing: a single feedback loop connecting devs with prod. On those grounds, it failed.

Software Engineering

AI & LLMs

Teams & Collaboration

AI-Powered Observability: From Reactive to Predictive

December 11, 2025

Rox Williams

AI-Powered Observability: From Reactive to Predictive

If there’s one thing clear from our AI-powered observability webinar, it’s that observability has officially graduated from a “nice-to-have” to a business-critical discipline, and AI is helping lead that charge.

AI & LLMs

AI Isn't Here to Replace Your Dashboard… Yet

December 2, 2025

Martin Thwaites

AI Isn't Here to Replace Your Dashboard… Yet

Non-deterministic UIs are the future, but they’re not here yet. So until then, we’re stuck with conversational interfaces.

AI & LLMs

November 24, 2025

Jessica Kerr (Jessitron)

What’s Special About MCP?

When MCPs don’t hog context, they still won’t often beat using the innate knowledge of the model. But when you are ready to curate the access that agents have to your SaaS or data, MCPs are fantastic.

AI & LLMs

Canvas Is Now GA: AI-Guided Observability for Modern Teams

November 19, 2025

Morgante Pell

Canvas Is Now GA: AI-Guided Observability for Modern Teams

We’re thrilled to announce that Canvas is now Generally Available (GA) for all Honeycomb users.

AI & LLMs

Product Updates

Fast and Close to Right: How Accurate Should AI Agents Be?

November 13, 2025

Austin Parker

Fast and Close to Right: How Accurate Should AI Agents Be?

In this blog, I’d like to discuss why hallucinations aren’t the biggest problem in observability agents, the tradeoffs around data fidelity and task accuracy inherent in agent and tool design, and how to evaluate agentic capabilities as they apply to observability.

AI & LLMs

If it Wanted to, it Would: The Bitter Lesson for LLM Users

November 12, 2025

Hannah Henderson

If it Wanted to, it Would: The Bitter Lesson for LLM Users

Systems, like people, have things they "want" to do. Each model has patterns of reasoning and synthesis it performs naturally. Power users learn to align with these representational grooves to get the "best" results and the highest-signal reasoning per token.

AI & LLMs

Coffee and Claude: How Honeycomb MCP Makes AI Work for You

November 4, 2025

Rox Williams

Coffee and Claude: How Honeycomb MCP Makes AI Work for You

Hosted by Austin Parker, Morgante Pell, and James Bland from AWS, the conversation explored how Honeycomb’s new Model Context Protocol (MCP) is changing the way developers and AI agents interact with data.

AI & LLMs