Prompt Engineering Articles for Reliable AI Workflows
Technical articles on prompt reliability, file-based AI workflows, evidence boundaries, ChatGPT work modes, and engineering ownership in AI-assisted work.
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How to Write for AI Models: The Language of Effective PromptsWrite prompts as clear, focused, testable task specifications
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AI File Upload vs. Full-File Review: How to Verify CoverageUnderstand why file upload is not proof of full-file review
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Vibe Coding Risks: Code Defects and Verification GapsAI-assisted coding without losing engineering ownership
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6 published articles
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Beyond the prompt: AI models, reasoning, and speedHow model choice, reasoning effort, and speed settings affect quality, response time, and token use.
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How to Write for AI Models: The Language of Effective PromptsLearn how to replace conversational filler, theatrical personas, leading premises, and competing tasks with prompt ...
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User Prompt vs. Model Context: What an LLM Actually ReceivesA user prompt is one part of model context. Learn which instructions, history, files, retrieved data, tools, and...
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AI File Upload vs. Full-File Review: How to Verify CoverageFile upload does not prove full-file review. Learn how extraction, chunking, retrieval, and active context affect s...
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Vibe Coding Risks: Code Defects and Verification GapsWhy working interfaces can hide code defects, and how verification and engineering ownership address the gaps.
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Prompt Engineering for Reliable AI WorkBuild reliable AI prompts for professional work using five failure modes, evidence rules, input-coverage checks, to...
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Cognitive Closure in AI Use: Why We May Stop Too Soon
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