Part 3: Working effectively with AI
Understanding usage limits
Every AI platform has usage limits — either message caps (free tier), rate limits, or context window constraints. Rather than treating this as a frustration, understand it as a design feature that encourages better practice.
The principle is simple: working within constraints forces you to structure your work more deliberately. Instead of asking an AI to "do everything," you break the task into discrete pieces, provide clear context, and get focused outputs. This usually produces better results than asking for everything at once.
For specific guidance on your chosen platform's limits and how to optimise within them, refer to the platform's official documentation or resources like Claude 101 which cover advanced usage patterns.
Avoiding agreement without pushback
AI will tend to validate your thinking. It won't push back unless you ask it to. You need to deliberately create space for critical thinking.
In your Custom Instructions, include something like: "When I ask for analysis or advice, challenge my assumptions. Tell me if the framing seems wrong, if I'm missing something obvious, or if the evidence points elsewhere. Don't just agree with me."
This is particularly important in health work where decisions affect real people. You want a thinking partner, not a rubber stamp.
Systems over prompts
There is no point in spending hours perfecting the perfect prompt. The more effective approach is to build good systems and then use simple prompts.
A good system means: clear personalisation files (who you are, how you work), organised context (reference documents, frameworks), and structured workflows (file naming, folder organisation, consistent question-asking patterns). Once these foundations are in place, your prompts can be short and direct because the AI already understands the context.
Build the system first. The prompts will be better and simpler as a result.