Frame your interaction with AI as if you're onboarding a new employee. Providing deep context, clear expectations, and even a mental "salary" forces you to take the task seriously, leading to vastly superior outputs compared to casual prompting.

Instead of asking AI for answers, command it to ask you questions. Use the "Context, Role, Interview, Task" (CRIT) framework to turn AI into a thought partner. The "Interview" step, where AI probes for deeper context, is the key to generating non-obvious, high-value strategies.

People struggle with AI prompts because the model lacks background on their goals and progress. The solution is 'Context Engineering': creating an environment where the AI continuously accumulates user-specific information, materials, and intent, reducing the need for constant prompt tweaking.

The key skill for using AI isn't just prompting, but "context engineering": framing a problem with enough context to be solvable. Shopify's CEO found that mastering this skill made him a better communicator with his team, revealing how much is left unsaid in typical instructions.

A powerful workflow is to explicitly instruct your AI to act as a collaborative thinking partner—asking questions and organizing thoughts—while strictly forbidding it from creating final artifacts. This separates the crucial thinking phase from the generative phase, leading to better outcomes.

The effectiveness of agentic AI in complex domains like IT Ops hinges on "context engineering." This involves strategically selecting the right data (logs, metrics) to feed the LLM, preventing garbage-in-garbage-out, reducing costs, and avoiding hallucinations for precise, reliable answers.

Surveys show people believe AI harms creativity because their experience is limited to generic chatbots. They don't grasp "context engineering," where grounding AI in your own documents transforms it from a generalist into a powerful, personalized creative partner.

Users get frustrated when AI doesn't meet expectations. The correct mental model is to treat AI as a junior teammate requiring explicit instructions, defined tools, and context provided incrementally. This approach, which Claude Skills facilitate, prevents overwhelm and leads to better outcomes.

The early focus on crafting the perfect prompt is obsolete. Sophisticated AI interaction is now about 'context engineering': architecting the entire environment by providing models with the right tools, data, and retrieval mechanisms to guide their reasoning process effectively.