Management In The Age Of AI
AI Summary
The article explores how engineering and product management must evolve in 2026 due to advanced AI tooling. It argues that managers must become hands-on builders to understand their teams and efficiently solve small requests themselves. Additionally, managers need to raise output expectations using tools, manage consumption-based AI budgets, enforce precise goal clarity to prevent building the wrong things quickly, and actively force team collaboration to combat isolated agent-driven silos.
Key Takeaways
- Managers must learn and use AI tools directly to properly guide teams and evaluate expectations.
- AI pricing models are shifting to consumption-based token budgets, requiring managers to allocate resources per person.
- The performance gap between great and mediocre engineers equipped with AI tools is massive, making hiring and raising the bar essential.
Why it matters
As AI dramatically accelerates individual development and shifts software economics toward consumption pricing, traditional management playbooks fail. Understanding how to handle token budgets, high-leverage tooling, and the massive performance delta of engineers using AI is critical for engineering leaders.
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