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What Dimitri Learned

A collection of insights about various marvels of life that I stumbled into

whatdimitrilearned.substack.comSource feed ↗10 posts

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Week of 2025-08-17: Breadboard and Opal

Where I describe the relationship between Breadboard and Opal.

Week of 2025-01-20: Machine Thinking

Where I ramble on about the difference between how LLMs and humans think.

Week of 2025-01-13: Recipes for Thought

Where I highlight a different approach to using LLMs and expand it into the whole repeatable thinking recipes bit.

Week of 2024-07-15: Teaching AI to write lyrics

Where I learn by teaching – the best kind. In this case, it’s a detailed account of applying a variety of techniques and patterns with the aim of getting good lyrics out of a large language model.

Week of 2024-06-02: Casino Creativity + Jamming with Udio

In this musically inclined rendition of the newsletter, I learn about the kind of creativity that requires so little skill that it’s mostly about the vibes, and report on my attempts to conduct a jam session with a generative AI.

Week of 2024-05-06: The third option + Chrysalis

Where I riff on the idea of finding a path out when stuck in a particularly vicious polarity, and … wait, what is that? A poem? Inspired by the Adult Development Theory? Can we chalk it up to diversifying your palate?

Week of 2024-04-01: Flexibility of the medium

Where I contemplate the future where medium is so malleable that it shapes around not just our needs, but even around our minute whims.

Week of 2024-03-25: The Bootstrapping Phase + Thinking to write

A rare twofer: where I try to articulate this interesting period in a software engineering project that I call the “bootstrapping phase”, and talk about the depth of thinking that motivates writing.

Week of 2024-02-26: Aircraft carriers and zodiac boats

Where I learn about the distinction between velocity and agility, and use a naval metaphor to make sense of it.

Week of 2024-02-12: AI Baklava

Where I learn more about layers of abstraction, their relationship to the context windows of large language models, and, perhaps overly ambitiously, the future of software engineering.