Building Your Own AI Workflow

You have learned how LLMs work, how to write effective prompts, how to use structured patterns, and how to apply AI to research, writing, coding, and study. You understand the risks — hallucinations, bias, over-reliance — and the ethical considerations around transparency and integrity.

Now it is time to bring it all together. This final lesson is about building a personal AI workflow — a set of habits, templates, and decision-making frameworks that let you use AI consistently, effectively, and responsibly in your daily work and learning.

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Step 1: Choose the Right Tool for the Task

Not all AI tools are equal, and not every task benefits from AI.

When AI Adds Value

• Tasks with a "blank page" problem: Brainstorming, outlining, getting started on a draft
• Mechanical text work: Grammar checking, reformatting, translating, summarising
• Learning and explanation: Understanding new concepts, getting personalised explanations
• Pattern-based generation: Boilerplate code, standard email formats, data transformation
• First-pass review: Catching obvious errors in code, text, or data before human review

When AI Adds Less Value (or Risk)