Matt Burgess

We each get so much content and opinion, in a different order, that we lose our hold on what we think. The Greeks called it stasis, and AI is making it worse.

What’s a boundary object, and what isn’t. And why AI is making things worse, not better.

The word ‘customer’ is spelt the same in every meeting, every deck, every system. It doesn’t mean the same thing in any of them. AI just made that impossible to ignore.

AI struggles with accurately understanding customers due to the lack of a consistent definition of “customer” across organizations, which a new product called Stratum aims to address by capturing and preserving authentic customer expressions.

The inconsistency problem in enterprise AI isn’t a model quality problem. It’s a memory architecture problem - and the graph was always the answer.

Your customers aren’t bots. But most internet traffic now is. That changes everything about what customer signal is worth - and what happens to it when AI touches it first.

Ontological registers, Looney Tunes, and why low confidence scores deserve a second look.

Every organisation loses customer signal in transit - hand to hand, meeting to meeting, summary to summary. It accumulates invisibly. I’m calling it signal debt. And AI is about to make it very expensive.

Organisations are losing signal at every crossing. There’s a word for what’s going wrong — and for what good looks like. They just haven’t imported it yet.

Enterprise fragmentation is likened to the parable of the Blind Men and the Elephant, highlighting how different departments perceive only parts of a larger structure, leading to failures in understanding and delivering customer value.

Innovation in AI requires a shift from blind prompting to a strategic understanding of systems, integrating data effectively to overcome performance plateaus.

An experiment in machinic reconciliation, boundary objects, and the void in between.

Fragmented methods of gathering customer feedback lead to disconnection in enterprises, hindering a coherent understanding of customer experiences.

Different perspectives on the same object, like a tomato, highlight the need for a shared ontology in business to improve communication and collaboration across departments.

Different fields, including philosophy and mathematics, converge on similar diagrams that illustrate the mechanics of emergence and relationships within complex systems.

Micromegas by Daniel Libeskind challenges traditional architectural drawing by exploring the complexities of space-making and the intersections of human intent and technical limitations.

Daniel Libeskind’s architectural work intertwines complex historical narratives and human memory, translating abstract concepts into physical forms that communicate absence and trauma.

An architect reflects on the lessons learned from deconstructing traditional enterprise structures and emphasizes the importance of exploring human movement and ambiguity in transforming organizations.