How I built a global recruiting style guide and trained an AI system to scale it

(2025 - Ongoing)

My Role

I built the Bain Careers style guide, the first editorial standard built specifically for Bain's global recruiting content. I also partnered to develop a custom GPT trained on that guide, giving the team a system that could draft, review, edit, and restructure copy based on the standard, and adapt it to whatever channel it was written for.

The Challenge

No documented editorial standards existed for Bain's global recruiting content. Copy varied across the careers website, job descriptions, event promotions, and social and password-protected platforms, with no shared rules for voice, tone, or brand consistency across 65 markets.

The Approach

I tailored Bain's existing commercial editorial style guide into a dedicated Bain Careers guide, built around concrete dos and don'ts and codified brand voice rules. I then partnered to build a custom GPT trained specifically on that guide, capable of drafting new copy, reviewing and editing existing copy, and restructuring content entirely depending on the channel it was headed to, whether Bain.com/careers, event descriptions, social media, or content descriptions for podcasts and videos.

The Outcome

The style guide and GPT system are now used across the majority of Bain's global talent acquisition web team, producing and refining consistent, on-brand copy across the careers website, job descriptions, event promotions, and digital and password-protected channels.

Performance

• Broad adoption across the global talent acquisition web team

• 65 markets aligned to a single editorial standard

• 4+ content types standardized

Key takeaway

Consistency at scale isn't enforced through more oversight, it's designed into the system from the start. Standards only work if they're concrete enough to apply without guessing, adaptable enough to fit the channel, and built into the tools teams already use.