Articles
Find AI Information Through Builders, Not Just Influencers
Use interpreters to discover questions, builders to find firsthand context, and primary evidence to reach a bounded conclusion about an AI claim.
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Use interpreters to discover questions, builders to find firsthand context, and primary evidence to reach a bounded conclusion about an AI claim.
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Reduce an AI request to the minimum permitted evidence, replace real values when possible, and stop when sanitization cannot protect the material.
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Evaluate a computer science degree by its curriculum, learning support, cost, alternatives, and evidence—not by broad predictions about AI.
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Build a scheduled, low-noise routine that turns relevant AI updates into verified decisions instead of continuous news consumption.
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Use prose, structured documents, schemas, and code to expose assumptions and make parts of AI-assisted work mechanically checkable.
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Practice broad foundations, initiative, and mental robustness through a semester plan with observable work and review.
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Choose Markdown, JSON, XML, YAML, CSV, or prose from the interface requirements of people, software, and LLM workflows.
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Translate course-specific AI rules into clear boundaries for tutoring, substitution, disclosure, privacy, and published solutions.
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Capture a successful AI-assisted task as a durable record of the problem, reasoning, commands, risks, and verification.
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Turn an AI-assisted result into a verified asset that works independently of the original conversation.