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HoneycombCharity Majors8 min readintermediate

AI Norms & Values, Part 2 of 3: AI for Honeycomb Engineering

Summary

Honeycomb’s engineering leadership outlines why the org is “all‑in” on AI, sets a north‑star to be in the top 10 % AI‑enabled teams, and publishes concrete 2026 goals (e.g. 25 % of PRs auto‑merged by AI with <3 % failure) plus an FAQ covering support, measurement, agent usage, and coping with workflow changes.

  • AI is framed as a productivity multiplier (2× impact) and a way to stay ahead of industry trends.
  • North‑star: be in the top 10 % most AI‑enabled engineering teams of similar size.
  • 2026 targets: 25 % AI‑reviewed/auto‑merged PRs with <3 % change‑failure rate, maintain SLOs, reshape work, and share learnings externally.
  • FAQ clarifies resources (subscriptions, tokens), measurement heuristics (≈1 shareable insight per month), and expectations around agentic workflows and Slack discussions.

Provides a concrete, metrics‑driven example of how a mid‑scale SaaS company is operationalizing AI across the software development lifecycle, offering a template for other engineering orgs seeking to set measurable AI adoption goals and cultural guidelines.

5/10

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