Career advancement isn't a pure meritocracy. Promotions often go to the most visible and well-liked people, not just the most skilled. Therefore, investing time in building relationships and ensuring senior leadership sees your work's impact can yield greater returns than focusing solely on improving your technical abilities.

The belief that simply 'hiring the best person' ensures fairness is flawed because human bias is unavoidable. A true merit-based system requires actively engineering bias out of processes through structured interviews, clear job descriptions, and intentionally sourcing from diverse talent pools.

At Menlo, peer-driven promotion decisions hinge on a crucial question: "Does the rest of the team perform better when you are part of that project?" This evaluates an individual's value based on their ability to elevate others, prioritizing team amplification over solitary excellence.

To fix inconsistent performance assessments, Ocado's Product Ops built a standardized skills framework. The framework's success was so evident that engineering, UX, and data teams voluntarily adopted and adapted it, creating a unified approach to career development across a 3,000-person tech organization.

Early promo committees at Uber involved managers verbally advocating for reports in large, unprepared meetings. This was highly unfair because an employee's promotion depended heavily on their manager's ability to present a compelling case, not solely on their performance.

When using AI for sensitive tasks like hiring, consistency is paramount. Talent Sprout implements "guardrails" and structured evaluation scorecards for its AI agent. This prevents unpredictable variations and ensures that every candidate is assessed against the same criteria. This control is crucial for maintaining fairness, reliability, and trust in the AI-driven process.

To assess an internal candidate's readiness for promotion, give them the responsibilities of the higher-level role first. If they can succeed with minimal coaching, they're ready. This approach treats promotion as an acknowledgment of proven performance rather than a speculative bet on future potential.

Traditional big tech ladders often promote based on scope and cross-team influence, encouraging politics. A better system focuses on skill gradients like "truth-seeking." It rewards being right about foundational decisions, not just being loud or well-positioned, which fosters a healthier engineering culture.

The best individual contributors often make poor managers. Research on 30,000 salespeople shows a better predictor of managerial effectiveness is the number of "assists" a person gives to colleagues. To build strong teams, organizations should promote candidates who demonstrably elevate others.