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Two weeks ago, I shared how I’m teaching my daughter to use AI responsibly as she starts college, while another mom told me her son was heading to school completely anti-AI because his teachers convinced him it’s cheating.

The post (https://lnkd.in/gJyHdaqv) sparked hundreds of comments from parents, educators, and professionals all wrestling with the same questions.

But one DM I received afterward caught my attention: “How are you teaching her not to get caught using AI in school?” That question helped me understand the mindset many of us are operating from. When we think about AI use in terms of “getting caught,” we’re approaching it as something to hide rather than a skill to develop.

Most of us feel caught between two choices: tell our kids to avoid AI completely, or let them use it freely and worry they’re not learning. We need a better approach.

Just like getting the right answer in math class wasn’t enough. We had to show our steps. Learning AI works the same way.

Consider this example. Your college student needs to write a research paper on climate policy.

The shortcut approach: “Write me a paper on climate policy and economic impacts.” Accept whatever comes back and submit it.

A more thoughtful approach starts with the student’s own perspective:

• Start with your viewpoint – “I believe carbon pricing hurts small businesses, but I want to explore this for my environmental economics class.”

• Set context – “The professor values multiple perspectives and evidence-based arguments.”

• Explore alternatives – “What are three different angles I could take? What makes each approach stronger or weaker?”

• Challenge your assumptions – “What evidence might challenge my belief? How would economists who disagree argue their case?”

• Seek different perspectives – “How would an environmental scientist versus a small business owner approach this?”

The difference is using AI as a thinking partner rather than a replacement for thinking. The student looks at various angles and makes the final call. The decision and final output is not outsourced to AI.

The biggest fear I hear is that AI will weaken our kids’ critical thinking. I believe students who guide AI thoughtfully actually develop stronger analytical skills. They question assumptions, look for multiple perspectives, and evaluate evidence.

You don’t need to become an AI expert. Start with conversations. Ask your kids how they’re using AI, not whether they’re using it. Show curiosity about their process. Help them see the value in showing their work.

If you’re ready for more, consider how your professional experience might help local schools. Teachers need support navigating this transition too.

Our kids will work alongside AI their entire careers. We just need to keep the conversation going and help our kids develop judgment to use powerful tools responsibly.

Feel free to use the links (in comments below) for helpful guidelines that I shared with my daughter.

As promised, here are some practical resources to help guide these conversations with our kids. These are the ones I shared with my daughter:

• 15 Smart Ways to Guide AI: https://lnkd.in/gwBSJpui

• Critical Thinking Questions to Ask AI: https://lnkd.in/gKDRDBhV

• Critical Thinking Framework and Real Life Examples: https://lnkd.in/gwD3K5mW

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Many go-to-market teams use AI to test subject lines, ad copy, and CTAs. But very few test the reactions of the stakeholders who decide if their strategy works.

Teams no longer have to choose between moving fast and getting strategic intelligence. AI simulation lets you preview how key stakeholders will respond in hours, not weeks. You can test reactions from your CFO, your customers, and your competitors before you spend budget or burn credibility.

This goes beyond testing copy and CTAs. We’re simulating reactions to market expansion strategies, new tiered platform pricing, and channel partner approaches.

Here are some takeaways from this week’s newsletter:

• Strategies don’t fail in planning, they fail in the reactions you didn’t anticipate

• Most teams start with messaging, but the real unlock comes when you simulate stakeholder feedback and responses to strategic moves

• The People Simulator Priority Matrix helps you focus on the stakeholders who can make or break your GTM motion

• You’ll still test in the real world, but simulation gives you a head start.

Big thanks to Claire Darling (CMO at Clari) and Justin Parnell (Founder of Justin GPT) for sharing how they’re putting simulation into practice at scale, from messaging auditors to dynamic workflows.

See full breakdown in the newsletter below.

To cater to different learning styles, see link in the comments for a 15-minute AI podcast version of this newsletter with two AI hosts.

If you found this helpful, please feel free to share it with others.

Here’s the 15-min AI podcast version of this newsletter to support different learning styles. Listen while driving, walking the dog, or having lunch 😉

https://drive.google.com/file/d/11Ohu96hJ1eIi-wylrgxsnUw1dqvwRVX/view?usp=share_link

Give it a few seconds to load after you hit play.

Note: AI-generated using Google’s NotebookLM and reviewed by me for accuracy and responsible AI use.

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