Context Is King. But the King Needs a Queen.
Reflections on Big Data LDN 2026, the rediscovery of business meaning, and why understanding requires more than structure.
Notes from the Network
Writing on data, governance, AI and the people inside the systems.
Before We Teach AI
AI is forcing organisations to confront problems that technology never created.
Love the Question, Not the Answer
The strongest data cultures aren't built on certainty. They're built on curiosity.
The Candidate the System Couldn't See
The system could see experience. It couldn't see capability.
What Measurement Makes Visible
Metrics help us see, but they also shape behaviour. The challenge is knowing whether we are improving the measure or improving the thing that actually matters.
The Human Layer
Reflections from Data Decoded London on AI, leadership, and why people remain the most important system inside any organisation.
Will the Vibe Survive Production?
AI assisted coding expands access, but production systems still demand depth and discipline.
Working in the Open
On collaboration, psychological safety, and why good systems are built together.
When Tools Are Asked to Do Human Work
Why tools and platforms are often asked to solve problems they were never designed for.
When Accountability Becomes Design
As AI systems embed themselves in organisations, accountability is moving from policy into architecture.
Where People Re Enter the System
As AI systems mature, attention is shifting back to the human structures that surround them.
When Data Becomes the Constraint
As AI systems settle into daily use, data quality and visibility are emerging as the real limits.
Where Agency Meets Structure
As AI systems gain autonomy, the limits of unstructured foundations become harder to ignore.
When Systems Start to Matter
Attention is beginning to shift from AI capability to the systems that surround it.
Making the Invisible Visible
Why MycoFlow exists, and what the mycelial network taught me about building systems.