1 link tagged with all of: decision-making + context + prompting + llm-workflow
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Modern AI models are capable enough to make meaningful decisions about how to solve problems, so you should tell them your priorities and context instead of just giving them a narrow spec. This lets them suggest better approaches and avoid wrong assumptions about what you actually want.
- Early AI agents needed explicit step-by-step instructions; now they fail because they misunderstand your goals, not because they're confused about how to execute
- Sharing broad context—your long-term aims, constraints, and what tradeoffs matter—lets models suggest improvements you wouldn't have thought to specify
- Explicitly ranking your priorities (e.g., "I care less about performance than observability here") gives models the information they need to make smarter choices