Writing
Notes & arguments on investment data, AI, and the platforms that connect them.
Working notes from inside the practice — what I think, why I think it, and what I've tried that worked or didn't.
Adoption is the metric
Internal tools don't fail at launch. They fail three weeks later, quietly. What I've learned about building platforms people actually open every morning.
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Driving AI inside an investment firm
What 'driving AI' actually looks like inside a major investment manager — the committee, the platform, and the gap between vendor demos and what investment teams actually need.
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Why Snowflake + Streamlit beats Power BI and Tableau for investment analytics
When the question is 'how should an investment team make decisions with data,' the traditional BI tools are answering a different question. The case for the data product mindset.
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Posts are written for myself first and shared because someone might find them useful. Opinions are my own. If you disagree with something, I'd rather hear why than not.