Charity Majors Urges Engineers to Bridge AI Divide as Fin Reports 3x Output in 9 Months
Updated
Updated · O'Reilly Media · Jul 9
Charity Majors Urges Engineers to Bridge AI Divide as Fin Reports 3x Output in 9 Months
3 articles · Updated · O'Reilly Media · Jul 9
Summary
Charity Majors says engineering teams are splitting into AI enthusiasts and skeptics, with both camps reacting to real existential risks rather than simple hype or resistance.
Her argument centers on a broken feedback loop: AI wins get celebrated in talks and all-hands, while cleanup, reliability damage and on-call pain stay with downstream teams that often lack a voice.
Fin, formerly Intercom, is presented as a model of disciplined adoption after reporting 3x output in 9 months, a defect backlog cut by more than half and 35% less downtime.
Majors argues the fix is to tell the whole story about AI gains and costs, then treat adoption as an engineering problem—adding tests, evals, guardrails and observability before pushing for unread code in production.
The broader warning is that AI amplifies both strong and weak engineering cultures, making leadership, trust and technical discipline more critical as teams shift from pre-AI to AI-native work.
AI acts as an amplifier. How can leaders ensure it multiplies strengths, not a team's hidden dysfunctions?
AI boosts developer speed, so why does company output barely increase? What's the real bottleneck?
Achieving 3x R&D Productivity: Fin’s AI-Driven Blueprint and the New Era of Engineering
Overview
In early 2026, Fin set a new industry benchmark by tripling its R&D output through the strategic integration of Artificial Intelligence. This achievement highlights how AI, now seen as the most impactful technology of the 21st century, is transforming engineering productivity. By leveraging AI agents, Fin dramatically reduced software development cycle times from weeks to hours, automating tasks like implementation, testing, and documentation. These fundamental shifts in the development process have not only increased output but also redefined the role of engineers, showing how business leaders can use AI to drive sustained productivity and foster a more inclusive future of work.