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Doing the Work: Why Learning is Key to Agentic AI Success & Avoiding Workslop
Why we need to be ready to 'do the work' of organisational transformation if we are to realise the potential of enterprise AI, and thinking about what…
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Lee Bryant
AI Learning & Adoption Goes Further and Faster in Co-Op Mode
How can shared practice, not individual use, help accelerate learning and sustainable adoption of AI?
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Cerys Hearsey
Enterprise AI is a Social Technology, Not the Sorcerer’s Apprentice
Some links and thoughts on agentic AI's positive potential to transform work and jobs, and the need to avoid both magical thinking and AI panic
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Lee Bryant
AgentOps: The Scaling Layer for Agentic AI in the Enterprise
To move beyond prototypes and achieve practical impact, we need to build the organisational infrastructure for agent development, deployment, and…
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Cerys Hearsey
Collaborative Architectures for Agents, People & Machines
Some thoughts and further reading on how to think about creating collaborative architectures for agentic AI in the enterprise
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Lee Bryant

August 2025

Enterprise Context Engineering as a New Leadership Capability
How can leaders ensure that people, AI agents, and distributed systems all work with a common context and information landscape, without slowing things…
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Cerys Hearsey
The Growing Importance of Context Engineering for Leaders Adopting AI
How business leaders can play an important role in enterprise AI adoption without needing to become technical domain experts
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Lee Bryant
Enterprise AI Adoption Requires Connected Leadership Steering
How leaders working together with a simple Map → Change → Learn loop can turn scattered AI experiments into living, organisation-wide capabilities.
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Cerys Hearsey
Will AI be 'Winner takes it all' or General Purpose Technology?
Considering the diffusion of economic gains from AI, why enterprise AI is more interesting than consumer use cases, and why learning by doing is…
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Lee Bryant
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July 2025

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