Curtis Harrison

Curtis Harrison writes about AI implementation, LLM architecture, and modern frontend engineering. He covers agent workflows, RAG and vector search design, and the TypeScript and React systems that make an AI feature usable.

His background spans enterprise software development and small business consulting, which shapes how he writes about AI: from constraints first. What a team can ship, staff, and keep running matters more than what a model can demo.

His guides tend to be implementation records rather than overviews, because the hard part of AI work is rarely choosing a model. It is the retrieval layer, the evaluation loop, the cost curve, and the person who has to maintain it in six months.