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Alexander Sterling writes about applied artificial intelligence, with a focus on the systems, patterns, and design choices that make AI agents actually work in the real world.
After a 23 year career as a systems engineer working with some of the most recognised names in enterprise technology, he has spent the past several years focused entirely on the frontier of AI — specifically, the engineering challenges of building agentic systems that can plan, act, and adapt outside the safety of a demo environment.
His interest sits at the intersection of two questions most builders skip past: how do you get an LLM-powered system to operate reliably in production, and why do so many promising agent projects quietly stall at the prototype stage? The answers, in his experience, rarely live in the model itself. They live in architecture, memory, role design, and the unglamorous engineering decisions that turn a clever demo into something dependable.
He writes for the practitioner who is past the hype cycle and wants a clear, structured way to think about what they're building. When he isn't writing or breaking things in a terminal, he reads widely across systems thinking, cognitive science, and the history of automation.
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