About

Hi, I’m Clarence —a Senior Data Scientist, who likes turning messy problems into working systems (and decent jokes). I write about AI, Data Science, forecasting, and agentic systems with an emphasis on how they succeed (and sometimes hilariously fail) in the real world.

What you’ll get here

  • Explainers with receipts: practical breakdowns of RAG, agents, time-series, evaluation, and deployment—grounded in production lessons.

  • Case studies & playbooks: patterns that reduced incident times, cut forecasting error, or automated gnarly workflows.

  • Hands-on artifacts: notebooks, metrics, and checklists you can lift into your own stack.

  • A dash of humor: because nothing is more “naturally awkward” than a confident model that’s confidently wrong.

Check out my work:

Why subscribe

If you’re an engineer, data scientist, PM, or founder who wants clear, no-fluff guidance on building reliable AI systems, this publication is for you. Expect applied posts, occasional deep dives, and templates you can reuse.

If that sounds useful, subscribe—I’ll meet you in your inbox with ideas you can ship this week. It’s Free!

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Subscribe to Artificially Intelligent Naturally Awkward

If you’re an engineer, data scientist, PM, or founder who wants clear, no-fluff guidance on building reliable AI systems, this publication is for you. Expect applied posts, occasional deep dives, and templates you can reuse.

People

I'm a Senior Data Scientist who builds forecasting models, RAG/agent systems, and pragmatic AI tooling—then write up what actually works (with jokes).