Prompting to Production: Documented, Evaluated AI Workflows

AI tools can produce useful results quickly, but a useful prompt is not the same as a reliable workflow. If your process exists only in your head, changes every time you use it, or cannot be easily repeated by someone else, it is difficult to maintain, evaluate, or improve.

Prompting to Production is a practical intensive for professionals who already use AI tools and want to move from informal experimentation to a structured, repeatable, and documented AI workflow.

You will work through a real task from your own professional context, define what good output looks like, build and refine your prompts, evaluate results against clear criteria, identify failure points, and document the process so another person could understand and run it.

By the end of the session, you will have one documented and evaluated AI workflow built around a real use case, rather than a collection of disconnected prompts.

Who this is for

This session is designed for professionals who already use AI in their work and want to make their processes more consistent, measurable, and transferable:

• Analysts working with research, reporting, or data

• Marketing and communications professionals

• Project and programme coordinators

• Policy and administration officers

• Operations and business support professionals

• Specialists using AI for recurring professional tasks

• Practitioners who want to turn successful prompts into repeatable workflows

You should already have some experience using AI tools. This is not an introduction to prompting. It is about building a more structured way of working with AI.

What we will do together

• Define the problem before the prompt: Clarify the task, desired outcome, quality standard, inputs, and potential consequences of poor results before building your workflow.

• Build structured prompts: Learn how to structure prompts using role, task, context, constraints, and output requirements, treating prompts as working specifications rather than one-off instructions.

• Evaluate outputs systematically: Create clear evaluation criteria and use a practical rubric to assess AI outputs based on evidence and requirements, rather than subjective impressions.

• Identify failure modes: Test where your workflow can go wrong, document common failure patterns, and establish checks to catch issues before they reach the final output.

• Turn prompts into controlled workflows: Define the required inputs, review points, boundaries, responsibilities, and quality checks around your AI process.

• Document for handover: Create practical documentation that allows a colleague to understand the workflow, follow the process, and reproduce the intended result.

What you will take home

By the end of the session, you will have developed a complete working package for one AI use case, including:

• A documented and evaluated AI workflow

• A versioned prompt with its purpose and rationale

• An output evaluation rubric and log

• A failure-mode and error log

• A practical workflow handover one-pager

• A clearer framework for improving and maintaining AI workflows over time

Good to know

This is a hands-on professional development session, not a lecture. You will spend the session building and testing a workflow around a practical use case.

Please bring your laptop and, if possible, a recurring task from your role that you already use AI to support or would like to improve. Avoid bringing confidential, sensitive, or personally identifiable information.

With a limited number of participants, the session provides space for individual review and practical feedback as you develop your workflow.

No advanced technical or coding experience is required. The focus is on structured prompting, AI workflow design, evaluation, documentation, quality control, and practical implementation.

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