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In the latest 6sense Market Makers, Carol-Lyn Jardine and Megan Ratcliff shared how Dice reimagined its marketing team, building a human-AI org with more than 100 AI teammates now working alongside humans.

I had the chance to partner with them on this journey, helping develop the human-centered playbooks, guide responsible adoption across roles, and support the mindset and behavior shifts that made scale possible.

In this session, we unpacked:

• How they structured the org and integrated AI teammates

• What changed in workflows, decision-making, and team roles

• Practical AI use cases across functions, from custom GPT-driven campaign planning to connected GTM workflows

• Lessons learned and the measurable impact in just six months

Replay + step-by-step playbook with templates and examples in comments.

Big thanks to Carol-Lyn, Megan, Gina Rau, Claire Couch, and Josh Decker for making this possible.

Watch the replay and grab the playbook here: https://lnkd.in/gpeDpJde

I can no longer tell if I’m reading a list of AI startups or a pharma label: Syfovre, Mounjaro, Anthropic, Bretzi, Voquezna, Groq. 🤪 Try guessing which are drugs and which are AI companies…

Somehow, we’ve reached peak naming chaos when biotech and AI sound like they share the same random word generator.

So I did what any normal person does on a long weekend. I turned this into an actual game. 😂

“AI or Drug?” is a quiz where you guess whether each name belongs to an AI company or a pharmaceutical drug.

I prompted both ChatGPT and Claude to:

• ➡︎ Make it tricky

• ➡︎ Add sound effects for right/wrong answers

• ➡︎ Give a short explanation after each guess

• ➡︎ Track progress and score

• ➡︎ Show a final “roast” screen with your score and a category name

• ➡︎ Add a “Why Drug Names Are Weird” button linking to [URL]

• ➡︎ Make it mobile-friendly, fun, and randomize every time

They built fully working games in minutes with audio, scoring, and UI. Some call this “vibe coding” where you just describe what you want in plain English and AI builds it.

I call it 2025. A random weekend thought became a working app before I finished my matcha latte. The gap between “wouldn’t it be funny if…” and “here’s a real thing” has basically disappeared.

Check out the short demo video below. Try the games via the ChatGPT and Claude links in the comments.

Want to build your own? Just copy/paste the prompt above and make it yours. (Note: I used ChatGPT o4-mini-high and Claude Sonnet 4)

How’d you do in the game? What was your score?

Claude quiz: https://claude.ai/public/artifacts/2e5a135d-454e-4d43-82f1-762d5b568378

ChatGPT quiz: https://chatgpt.com/canvas/shared/686a6ea25e908191a82cd0c94b3f09f5

To see more examples and learn how to do this: https://www.linkedin.com/pulse/dont-sit-idea-build-ai-liza-adams-lhfbc

Every 4th of July, I pause and think about that 14-year-old girl boarding a plane alone in Manila with nothing but a brown passport and a rag doll. Leaving behind her family, her language, her childhood… chasing an unknown future in the U.S., holding tight to hope.

That girl who grew up with so little, hoping for a better life for her and her family was me.

I’ve told my story before. And with so many of you who are newer to my story, I want to share it again. It’s raw and real. And it’s a big part of why I do the work I do today. You can read it here: https://lnkd.in/e9dWt5Z

Since I wrote that piece, a lot has changed. But the little girl from Manila? She still lives in my head. She’s still in awe. Still holding deep gratitude for what this country and its people made possible.

Today, I’m doing work that aligns with who I am at my core. Work that helps others rise. And I’m seeing the ripples of it. The DMs. The thank-yous. The “you’ve inspired us to think differently.” The support in rooms I’m not in. It’s humbling. And it keeps me going.

People sometimes ask me, “Aren’t you worried about sharing so much of your work for free?” I just think about how many people have given me so much for free.

I’ve learned something that my good friend Andy Crestodina says:

“We’re in the business of generosity.” Generosity doesn’t devalue your work. It proves it.

Some will take what I share and run with it. Others will want my help bringing it to life. Either way, it helps someone.

Someone told me something that stuck:

“If you chase butterflies, they’ll fly away. But if you build a beautiful garden, they’ll come to you.” I’m no longer chasing. I’m building. And the right people, the right opportunities, they keep showing up.

And as my long-time mentor and dear friend Christine / Chris Heckart always says:

Let kindness ripple. You’d be amazed what comes back to you.

To this country that took in a kid with very little and gave her everything… Thank you. I’m eternally grateful and the best way I know to show it is to keep paying it forward. One person, one opportunity, one act of kindness at a time.

Here’s the link to the demo video: https://www.youtube.com/watch?v=Tpwb4Y91Nr0&t=1888s

I shared my AI tool picks during Isar Meitis’ The Ultimate AI Showdown:

• ➡︎ Gemini for deep research

• ➡︎ ChatGPT for analytics

• ➡︎ Claude for frameworks and visualization

I shared the use case where I tested all three, including the prompts, conversations, and outputs. Link to the demo video is in the comments.

Ultimately, if you have the luxury to do so, the best approach overall is to leverage all three in combination, where each one is used in its area of strength.

These are my picks for these use cases and only for now, based on my experience. All bets are off tomorrow. AI continues to advance and the AI companies continue to leapfrog each other.

If you don’t have time to view the video now, save it for later. Watch it while you wolf down that lunch or during your “learning” time. 😉 Let me know your thoughts.

Get into the habit of asking AI its confidence level in its responses. You’ll be shocked how often it says “medium” or “low” including for some of the most compelling insights.

That’s the problem. I’ve been getting great research from AI, but I had no way to know how much I could actually rely on it.

So I now make AI check itself. Not just give answers, but audit them.

I ask AI to rate its own output on key dimensions. For each takeaway, I have it share:

• ➡︎ How confident it is (High/Medium/Low) and why

• ➡︎ What it’s assuming to be true

• ➡︎ What info would improve its rating

When AI says “Medium confidence because I’m assuming X, Y, and Z,” I know exactly what to check. I don’t waste time second-guessing everything. I zero in on where the risks are.

These insights turn AI into a thinking partner, not just a fast Q&A machine. I still verify the work, but now I know where to lean in instead of treating every output as equally trustworthy or equally risky.

I also ask it to rate things like risk assessment, evidence quality, implementation difficulty, and impact potential. Then explain the rationale and assumptions behind each.

“For each key takeaway, rate your confidence (high/medium/low) and explain why. List your assumptions, and note what would increase your confidence if it’s medium or low.”

Interestingly, AI has told me that it is not confident in its response because it can’t find on the web or in its knowledge any supporting data. Truthful and transparent. However, without the confidence level, I could’ve easy assumed that it’s a sound insight. (Sample output in the comments)

I put together a simple table below that shows what questions to ask for each dimension.

This helps me check what AI produces without having to be an expert in every topic. It’s a simple addition to the prompts that changed how I work with AI completely.

If you’re using AI for research or decision support, give this a try. Would love to hear what’s working for you.

If you found this useful, feel free to share it with others on your team.