The Algorithm
Notes on building AI systems that actually work.
What I've learned building AI systems across healthcare, finance, ecommerce, and government — the architecture decisions, design tradeoffs, and organizational dynamics that determine whether an AI project succeeds or stalls.
Latest
What Actually Makes AI Work in Production
A model can interpret a request, draft a response, and still fail in production. Reliable AI systems need interpretation, boundaries, context, measurement, and human judgment working together.
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I Built a 25-Agent AI Operating System
Most people doing serious knowledge work with AI still start in the same place: a blank chat window. I replaced that setup tax with a personal AI operating system built from specialized agents, composable skills, and persistent memory.
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The Difference Between Relevant and Reliable
Most production failures get diagnosed as relevance failures. But many enterprise AI systems fail for a different reason: the model had access to the relevant information, and the surrounding system still produced the wrong outcome.
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Browse by Series
Foundations
The analytical and structural thinking that everything else builds on.
8 postsStop Thinking in Tools
Why the tool is never the point, and what to focus on instead.
3 postsCompound
How a personal AI operating system of specialized agents is designed, structured, and improved over time.
1 postSubscribe to The Algorithm
Notes on building AI systems that actually work.