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The Hidden Cost of AI Collaboration: We're Trading Skills for Efficiency
AI-human collaboration boosts accuracy today but quietly erodes the skills it depends on tomorrow. Research shows smart task allocation can add 20 accuracy points while reducing human judgement through lost practice, leaving no one capable when AI fails.
AI Makes Developers Faster—Except It Doesn't
A METR study found that AI coding tools like Cursor Pro and Claude slowed experienced developers by 19%, even though they felt 24% faster—revealing a major gap between perceived and actual productivity.
From Framework to Practice: Triaging Tasks for AI
Minutes saved don’t equal business value. This article shows how to assign AI tasks to the right control mode—Tool, Co-Pilot, Partner, or Supervised Autonomy—based on ambiguity and consequence. Build scalable governance that turns AI adoption into measurable performance gains.
The New Rules of Working With AI
The productivity gains from AI are real: 14% faster problem-solving, 50% faster coding. But treating AI as just another tool fails. Organizations succeeding treat it as a teammate with defined roles, transparent reasoning, and human oversight matched to risk. New rules for a new team.
Eight Books That Will Change How You Think About AI at Work
AI will transform your organisation, but will that transformation serve people or replace them? These eight books provide the roadmap for human-centred AI: aligning technology with human purpose, designing collaboration, and creating systems that elevate rather than displace human work.