WorkAI Automations3 min read
Career paths every employee can see
One leveling framework, a ladder per job family, and a career page anyone can open before a review.
Built by our founder in the Chief People Officer seat of a private-equity-backed software company, for its own people function. Built in 45 to 60 days, inside the company’s own systems.
The problem
Sixty titles for fewer than two hundred people, several held by one person each, and nobody could explain what separated a senior from a lead.
Promotions were negotiated one at a time, exit interviews said no path, and a compensation project could not start because there was nothing to band against.
What we built
A leveling framework the leadership team confirmed, built from the existing titles and job descriptions, with AI proposing the job families and levels and people deciding them.
One ladder per job family, with the scope and evidence for each level written so adjacent levels are distinguishable.
A job description generator that writes every new description from the framework, so titles stop drifting.
A career page per family that employees can read, without pay data, and a promotion readiness checklist the manager completes in the performance tool.
How it works
A manager opening a new role starts from the framework, not from a blank page. The description is generated, reviewed by HR, and published to the hiring tool.
Before a review, the employee and the manager read the same ladder. The promotion conversation is about evidence against a level, not about persuasion.
The title-to-level map records every title that moved and why, so the history is explainable in diligence.
The result
Titles per hundred employees fall to a number a buyer would recognize, and stay there.
Every employee can see the next level and what it takes, which changes the exit interview conversation.
The compensation architecture project can start, because there is finally something to band against.