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
The Cheaper Half of Oversight
Reviewing outputs answers whether the work is good. Reviewing plans answers whether it was the right work — and only one of those questions can be answered before the scope locks.
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Stop Trying to Automate the Whole Workflow
The organizations getting the most from AI right now are mostly not building sophisticated autonomous systems. They found one expensive step in a process that already works and made that step better.
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The Torch Has Passed
Anthropic and OpenAI represent the first genuinely new foundational technology companies in two decades. Most senior leaders are reading this as a procurement decision — which model do we bet on? That question is less important than it sounds. The moat isn't the model. It's how well you build the system around it.
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Series
Foundations
The analytical and structural thinking that everything else builds on.
8 postsIn Production
What it takes to make AI work in production — the failure modes, misdiagnoses, and the questions worth asking.
5 postsCompound
How an AI operating system of specialized agents is designed, structured, and improved over time.
3 postsGround Truth
Plain observations on what AI is actually doing to knowledge work, organizations, and the people who lead them.
1 postSubscribe to The Algorithm
Notes on building AI systems that actually work.