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A thought leadership piece arguing that AI development is shifting from prompt engineering to context engineering — how systems are structured, remember, and reason, not just how they're prompted. Written for AI/SaaS audiences. Published on Medium.
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Currently building autonomous AI systems that actually survive production — not just the demo.
Most AI projects work beautifully in a controlled test and then quietly fall apart on real data, edge cases, and concurrency. I focus on the unglamorous engineering that closes that gap: data validation pipelines, boundary checks, error handling, and knowing exactly where deterministic logic should own the decision instead of the model.
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Open to Applied AI / AI automation projects.
Keep it up!