Stop repeating yourself with standing instructions and projects
Restating your job, your product context and your expectations in every conversation wastes time and gives uneven answers. You learn to write instructions that carry over from one chat to the next, and to decide where each piece of context belongs depending on whether it applies to all your work or to a single topic.
Lesson objective
By the end of this lesson, you will be able to write standing instructions suited to your role and choose between global instructions, a project and memory depending on how widely the context needs to apply.
Topics covered
- custom instructions
- Claude and ChatGPT projects
- AI assistant memory
- persistent context
Where it fits
Set up an assistant, work with diligence
How do you stop starting from scratch, hand more work to AI and stay accountable for the result?
Lessons in this module
- Stop repeating yourself with standing instructions and projects (this lesson)
- Building a dedicated assistant, then handing tasks to an agent
- Working with diligence
What you will learn in the course
This lesson is part of the course Prompting for Product Managers: delegate, describe, verify
- Decide, for a task in your product cycle, whether to hand it to AI, in which mode (automation, augmentation, agent), and what you keep.
- Explain how an LLM behaves (prediction, dated knowledge, working memory, instruction following) to anticipate its mistakes and pick the right fix.
- Write a prompt that describes the deliverable, the process and the quality bar, with context, delimited data and examples when needed.
- Evaluate an AI output (content, process, behavior) against explicit criteria, then improve it through targeted iterations.
- Produce PM deliverables with AI (feedback synthesis, persona, interview guide, user stories) from real data, and check that they are faithful to it.
- Configure standing instructions and a dedicated assistant for a recurring task, test it on real cases, and decide when to move to an agent.
- Apply diligence rules (shared data, transparency, accountability) before using or circulating work produced with AI.
Related courses
- Build reliable Claude Skills for your product workAdvanced · ~2 hr 30 min
- Choosing and using AI tools at workAll levels · ~1 hr 40 min
- Understand what LLMs do well, and where they failAll levels · ~2 hr