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Intercom
Intercom — Organization. scale: 1305 employees, 500 R&D, 8,5M lines of code, 30 000 B2B customers, 313 deploys/day, 2M+ QPS peak
Intercom runs 500 people in R&D against 8.5 million lines of code, 313 production deploys a day, and 30,000 B2B customers. Nine months after «Darragh Curran» publicly committed to doubling R&D productivity in twelve months, he published a report card on 16 April 2026 claiming 3× over sixteen months with no plateau in sight.
The numbers are the reason this case keeps coming back. 93.6% of pull requests are agent-driven, 19.2% are AI-approved against a stated target above 50%, defect backlog is down 54%, cost per PR down 50%, downtime from breaking changes down 35%. Median merge time for «Claude Code» in auto-approved mode is 14.6 minutes, against 75.8 minutes for the organisation as a whole. Curran treats the merged PR as the pivot metric and describes R&D as a factory producing high-quality increments.
The organisational piece is the «Skills-Based Plugin Architecture», a private marketplace distributing specialised «Claude Code» configurations with auto-update: 153 contributors built 267 skills in three months, 31% of R&D contributing actively. Adoption spilled past engineering, with 1,100 «Claude Code» users among 1,305 employees.
Curran's own method is anti-perfectionist: don't search for perfect measures, embrace imperfect ones, monitor holistic outcomes. The «Ramp» convergence sits alongside this as a second data point from a scale-up publishing its receipts. What remains open is whether AI-approved PRs actually cross 50%, which Curran predicts but has not yet shown.
- Type
- Organization
- scale
- 1305 employees, 500 R&D, 8,5M lines of code, 30 000 B2B customers, 313 deploys/day, 2M+ QPS peak
- relations
- 11
- Cited in
- 1 fiches
Adoption measures
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3× R&D productivity in 16 months
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93,6% agent-driven PRs
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19,2% AI-approved PRs
↻ Source ↗
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cost per PR -50%
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defect backlog -54%
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median Claude Code auto-approved merge at 14,6 min
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>50% PRs AI-approved
↻ Source ↗
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"19% of PRs auto-approved, deployments doubled, breaking-change-related incidents down 35%"
Neighborhood
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