AI Over 40 Series - Week 8: Building Your AI User Manual

Why the most critical AI skills have nothing to do with prompt engineering

Here’s a deceptively simple question that transformed how I collaborate with AI: Do I need to be polite to a machine?

You might scoff—“Greg, it’s a computer, not a person!”—but hear me out. AI models are trained on the full spectrum of human language: emails, novels, dialogues, support tickets, tweets. When you frame a request with encouragement—“Could you explore this idea further?”—the AI’s output becomes more creative, expansive, and thoughtful. Conversely, a curt or dismissive tone yields minimal, cautious responses.

The takeaway: Politeness isn’t about teaching machines manners; it’s about unlocking richer, more innovative results. This insight revealed a glaring gap in most AI training: we focus almost exclusively on “how to write prompts,” but ignore the conversational dynamics that shape every AI interaction.

Beyond prompt engineering: The four pillars of AI collaboration

After months of experimenting across Claude, ChatGPT, Gemini, and Copilot, I’ve distilled four fundamental practices that underpin truly effective AI partnerships—principles you won’t find in any generic “prompt engineering” guide.

Conversational dynamics matter

Think of your favorite human collaborator: they thrive on encouragement, balk at criticism, and open up when you show curiosity. AI behaves the same way.

• From criticism to curiosity:
  • Instead of: “That’s wrong—try again.”
  • Try: “Interesting angle—what if we considered a different perspective?”
• From commands to invitations:
  • Instead of: “Give me three options.”
  • Try: “I’d love to hear your most creative ideas—what possibilities can you imagine?”

These subtle shifts in tone can transform a bland response into a burst of insight. You’re effectively cueing the AI’s training on human conversational norms.

Context management is your responsibility

Every AI chat has a finite context window—and as you approach its limit, the model “forgets” details from earlier in the conversation. Left unchecked, you’ll end up with disjointed or shallow answers.

Refresh techniques to keep AI on track:

• “Based on our conversation so far, what are the key takeaways?”
• “Before we proceed, please summarize the main points we’ve covered.”
• “Given our earlier discussion about [topic], how would you approach this next step?”

By prompting a brief recap, you force the model to re-ingest critical context, much like giving a colleague a moment to skim their notes before a meeting.

Organization strategies transform results

Imagine juggling ten separate consultants—each time you meet, they need to be brought up to speed. That’s the experience of using one-off chats for complex, ongoing projects.

Leverage “Projects” or conversation folders (available in ChatGPT, Claude, etc.) to group related sessions:

• Ideal for:
  • Strategic planning that spans weeks
  • Multi-step research initiatives
  • Learning trajectories (e.g., mastering a new framework)
• Reserve one-off chats for:
  • Quick, standalone questions
  • Sensitive topics you don’t want stored
  • A/B testing different prompting styles

Keeping all related threads in a dedicated project preserves context, accelerates follow-up, and lets you build momentum over time.

Plan for AI portability

What if you lose access to your current AI platform? Or want to migrate insights from Claude into ChatGPT? Relying on proprietary conversation stores is a gamble.

My portability playbook:

1. Regular exports: Download key conversations at least weekly.
2. Format conversions: Turn JSON dumps into clean Markdown for readability.
3. Chunking large histories: Split massive exports into topic-specific files.
4. Insight summaries: Maintain a living document of the most valuable takeaways.

It’s not perfectly seamless—export formats vary, and most platforms choke on huge imports—but this discipline safeguards the knowledge you’re accumulating.

Why this changes everything

Traditional AI training treats models like search engines: craft the perfect query, hit “enter,” and hope for the best. In reality, AI thrives when you treat it as an eager, context-needing partner:

• You encourage innovation through tone and phrasing.
• You manage context proactively to maintain coherence.
• You organize conversations to build on past work.
• You plan for portability to protect your AI intelligence.

Master these four pillars, and you’ll collaborate with AI far more effectively than any prompt-templating hack.

Your Week 8 Challenge: Build your personal AI user manual

This week, document your own preferences and practices for working with AI:

1. Test conversational dynamics
   • Pose the same question in a critical tone and an encouraging tone.
   • Compare the depth and creativity of the responses.
2. Experiment with context management
   • In a long chat, interrupt mid-conversation with, “Please summarize our discussion so far.”
   • Observe how the recap influences later replies.
3. Organize strategically
   • Create a new Project/folder for an ongoing topic.
   • Notice how continuity improves follow-up sessions.
4. Export and review
   • Export a key conversation to JSON or Markdown.
   • Convert and chunk it for easy future reference.
5. Draft your AI User Manual
   • Capture what tone, context-refresh phrases, organizational structures, and export routines work best for you.

Treat this manual as living documentation—your personalized guide to getting the most out of every AI interaction.

The deeper implication

If you can’t collaborate effectively with AI—if you can’t maintain context, cultivate creativity, stay organized, and ensure portability—how will you ever entrust it with autonomous tasks? True AI adoption isn’t about flipping a switch; it’s about building the literacy and frameworks that make autonomous agents possible down the road.

Organizations that skip these foundational steps risk brittle implementations and missed opportunities. Your AI User Manual isn’t just a personal playbook; it’s the competitive edge that will distinguish leaders from laggards in an AI-driven world.

This post is part of our “AI Over 40” series. It first appeared on LinkedIn: AI for the Over 40 – Week 8: Building Your AI User Manual.

Next Week: AI Agents 101 – why you must master collaboration before handing off control, and how to structure your first autonomous agent safely and effectively.

Read more AI and Copilot blogs.

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