Hey there. If you're meeting my curated digital self, well, nice to meet you. I hope to meet you properly someday.
A simple rundown. I'm interested in, and actively working on, representations, information quality, and the data engineering underneath it. Entity resolution, NER, classification. In more marketable terms: record linkage, knowledge graphs, semantic layers, and intelligence.
Mostly I want to know whether a system understands what it is acting on, and whether it knows when to refuse.
My route here was not a straight line. Geospatial data, then open source, then leading teams, then building things of my own. What I kept noticing is that the interesting problems were never the models. They were underneath, in what the data was actually supposed to represent.
Today I sit close to the business, at the point where a decision has to be **accurate and consistent**. Attribution models, customer records, behavioural signals, addresses, fragmented identifiers. The kind of work where someone asks a simple question and the honest answer depends entirely on whether two rows are the same person.
I am not on a platform team and I am not an infrastructure engineer. I am usually the one explaining why a number moved, and finding that it moved because the data was wrong about who or what it was describing, and had been for months without anyone noticing. You learn a lot about entity resolution from the consequence side. It is harder to wave away a bad match when someone is about to make a decision on it.
So rather than dashboards for their own sake, I care about the systems that decide *what the data actually represents*. How entities get formed, merged, split, and understood over time, and how confident anyone should be in any of it. That leads straight into attribution, customer 360, identity stitching, and the trust problems most teams run into constantly but rarely name out loud.
I am also a member of the **[PKI Consortium](https://pkic.org/)**, which I joined to learn public key infrastructure properly rather than by osmosis. My interest there is narrow on purpose. Non-repudiation, confidentiality, and security, and how those connect back to representation and identity. I have no ambition to become a cryptographer. I would just like the things I build to still verify in ten years.
Alongside my professional work, I am studying and experimenting with ideas from entity resolution theory, spatial identity, probabilistic reasoning, and high-dimensional representations. This is not abstract research for its own sake; it’s a way to build better mental models for how real systems should work under uncertainty.
If my hypothesis is valid, AI systems in 3-5 years will:
- know *what* entity they are acting on
- know *why* they believe that
- know *how confident* they are
- refuse to act when confidence is insufficient
- leave audit trails humans can inspect
That’s not AGI.
That’s **responsible autonomy**.
## If you are new here
Five to start with, and why.
- **[Identity is an inference problem](/posts/identity-is-an-inference-problem/)** — the post where the thing I actually care about finally got a name. If you read one, read this.
- **[What entity resolution actually is](/notes/what-entity-resolution-actually-is/)** — the technical idea in plain language, with a coffee shop and no equations.
- **[Alignment starts with reference](/notes/alignment-starts-with-reference/)** — why a perfectly aligned system acting on the wrong person still does harm.
- **[Busyness isn't growth](/posts/busyness-is-not-growth/)** — not about data at all. About the difference between moving and getting somewhere.
- **[Five years](/five-years/)** — what the number in the footer is counting, and what I am actually trying to do.
There is also a [timeline](/timeline/) of what has happened, a [list of 99 things](/list/) I want to do, and some [paradoxes](/paradoxes/) I keep running into.
That is what the [five years](/five-years/) are for.
This space is where the threads come together. Life, tech, and meaning. If you are into data, open source, or just trying to become a better version of yourself, you are in the right place.
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Companies I've Worked With
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Articles and References:
- [LDBC to GDC: A Landmark Shift in the Graph World by Dennis Irorere](https://www.graphgeeks.org/blog/ldbc2gdc) - Article
- [Agentic Workflow for GraphRAG: Building Production Ready Knowledge Graph](https://odsc.medium.com/from-architecture-to-execution-inside-week-2-of-the-agentic-ai-summit-88baa36ca3b5) - Workshop
- [Travel Plus Experience Meets Data at Viator by Dennis Irorere](https://www.viator.com/blog/Travel-Plus-Experience-Meets-Data-at-Viator/l114209) - Article
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Outside of data, I have a profound love for nature and photography. My goal is to visit 15 countries in the next three years,I’ve already explored three, with 12 more to go. Capturing the world’s beauty through the lens of my FujiFilm xT20 brings me immense joy, and I’m eagerly looking forward to upgrading to the xT30. Follow along for my travel adventures and the stunning moments I’ll be sharing.
## Away from the screen
I run a small **book club** here in England. A handful of us, a book a month, and an argument that usually turns out to be about something other than the book. It is the best standing appointment in my calendar.
I am also serious about **tea**. Not in a precious way, I just think it is the correct drink and I will happily talk you through why.
## Location
Currently based in England, UK. If you are in town, let's get a tea.
