When using AI systems, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?

To ensure AI-generated results are accurate, relevant, and aligned with original goals, project leaders should apply four key best practices:

Define Clear Objectives – Start with well-scoped prompts that reflect business context and intended outcomes.

Use Iterative Prompting – Refine inputs progressively to steer the AI toward higher-quality outputs.

Validate with Domain Expertise – Cross-check AI results against real data, stakeholder expectations, and subject-matter knowledge.

Monitor for Bias and Drift – Regularly assess outputs for consistency, especially when dealing with evolving project goals.

When used responsibly, these practices position AI not just as a tool, but as a strategic partner in decision-making and value delivery

As a relatively young person who grew up in an era where everything revolved around searching on Google, I remember that the better you were at finding the right combination of words—short and focused enough on your problem—the more of a 'Googling master' you were. Now, it’s quite the opposite, and shifting that mindset feels strange. We've gone from trying to search with 3 to 10 keywords on Google to sharing an entire context, where the hard part is figuring out what's enough.

What has worked for me is focusing my prompts based on the area where the information will be used. In other words, it’s not the same if a developer is reading it versus the QA team. That way, even though the tasks are used across teams, each prompt is shaped for the specific audience to properly cover all aspects of a task.

When providing instructions to AI, we need to ensure Instructions are clear structured and descriptive.

●Instruction - a specific task or instruction you want the model to perform
●Context - external information, Persona or additional context that can steer the model to better responses
●Input Data - the input or question that we are interested to find a response for
●Output Indicator - the type or format of the output
●Response Tone – Tone of the response