Welcome to the Digital Garden

This is digital space for curating thoughts, research, and experience about AI, data, and the infrastructure underneath.


What is a Digital Garden?

Unlike a blog with polished posts, a digital garden is a living collection of ideas at various stages of development. Notes grow from seedlings (rough ideas) to evergreen (refined thinking). You’re welcome to explore the weeds.


About

I’m Mike — leader, published AI researcher, and lifelong learner. This garden grows from my M.S. work in Information Design & Strategy at Northwestern and ongoing work in AI/ML systems.

This site is built with Quartz, hosted on Cloudflare Pages, and maintained with a workflow involving Claude for note creation and refinement.


How This Garden Works

Knowledge Architecture

Notes follow atomic design principles:

TypeWhat It IsExample
AtomsSingle concepts, definitions, principles”What is attention?”
MoleculesFrameworks, patterns, comparisons”RAG vs Fine-tuning”
OrganismsComplete articles, guides, essays”Building Production ML Pipelines”
ElementPurpose
Left PanelBrowse by domain, then drill into atoms/molecules/organisms
Right PanelSee note properties, graph connections, and table of contents
Graph ViewVisualize how ideas connect across domains

Domains

Explore the nine knowledge domains:

DomainFocusNotes
[index|Home]Sources, references, entry points107
[index|Human Centered Design]UX, design thinking, user research51
[index|Information Architecture]Structure, taxonomy, organization50
[index|Research Methods]Methodology, analysis frameworks33
[index|Data Engineering]Pipelines, infrastructure, data systems51
[index|AI Mechanisms]ML/AI concepts, architectures, techniques350
[index|Knowledge Engineering]Knowledge graphs, ontologies, reasoning88
[index|Cross Domain]Ideas spanning multiple areas103
[index|Professional Practice]Career, leadership, ways of working22

Start Exploring

If you’re interested in AI/ML: Start with [index|AI Mechanisms] — the largest domain with 350+ notes on transformers, attention, LLMs, and more

If you’re interested in data systems: Explore [index|Data Engineering] — pipelines, architectures, and infrastructure patterns

If you want to see connections: Use the graph view (right panel) to discover how concepts link across domains


Last tended: January 2026