The Future Solving Company

“Start with what problem you want to solve.” It’s the advice everyone will give you. But it’s wrong. And here’s why: Problem solving systematically drives out innovation. Full explanation in the video. Share with your innovation leaders.

AI agents are so hot right now! but are they just hype? This was one of three topics we covered on Tuesday at our kickoff to our Executive Breakfast Club, which I had the pleasure of cohosting in Seattle with Jelena Joffe Weil, Kate Niedermeyer, and Amazon Web Services (AWS) Venture Innovation. (Stay tuned as we announce our 2025 cities and schedule) I am so excited about what we are building with this community — connecting and empowering senior executives focused on making an impact on the future of the market and society. We also discussed: 🧐The problem with solving problems (and why we need Future Solving) 🔬How being data-driven is unscientific (and what it means to be reason-driven) If you want to join our community and be the first to hear about upcoming virtual events or when we're coming to your city, check out the link in the comments. Thank you to the following leaders for joining us — Michael Atalla, Rashmi R. Rao, John Kraski, Alicia Fratto (Heddon), Nathan Haralson, Ryan Cudney, Taylor DeWater, Dominic Smargiassi, Adam Sheppard, Sid M., Robin Twyman, Ryan Mayfield, and Stephen Gerrard

𝗟𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗮 𝘁𝗵𝗼𝘂𝗴𝗵𝘁-𝗽𝗿𝗼𝘃𝗼𝗸𝗶𝗻𝗴 𝗿𝗲𝗮𝗱 𝘁𝗵𝗶𝘀 𝗵𝗼𝗹𝗶𝗱𝗮𝘆 𝘀𝗲𝗮𝘀𝗼𝗻? I highly recommend adding Brian Evergreen's 𝘈𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴 𝘛𝘳𝘢𝘯𝘴𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯 to your reading list. While I’m still working my way through it, this book is already proving to be one of the most compelling and insightful reads I’ve encountered all year. What stands out to me is Evergreen’s continual focus on 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗵𝗼𝗹𝗶𝘀𝘁𝗶𝗰𝗮𝗹𝗹𝘆. He presents frameworks, methods, and strategies that reimagine organizations and ecosystems as 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗲𝗿𝗲𝗱 𝘀𝗼𝗰𝗶𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺𝘀, paving the way for a kind of organizational renaissance where the 𝘀𝗼𝗰𝗶𝗮𝗹 𝘀𝗰𝗶𝗲𝗻𝗰𝗲𝘀 𝗮𝗿𝗲 𝘀𝗲𝗮𝗺𝗹𝗲𝘀𝘀𝗹𝘆 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗶𝗻𝘁𝗼 𝗮𝗹𝗹 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗲𝘀. His process for pursuing a human-centered transformation (his “𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗰𝗲𝘀𝘀”) builds the creation of a human future into the process as a practical component of how we implement AI and other converging, adjacent technologies – no fighting through the dual edges of right for people vs right for the business. Evergreen paints a bold vision, and provides a practical, “gluey” blueprint, of how we can 𝗿𝗲𝘀𝗵𝗮𝗽𝗲 𝘁𝗵𝗲 𝗻𝗮𝘁𝘂𝗿𝗲 𝗼𝗳 𝘄𝗼𝗿𝗸 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗯𝗲𝘁𝘁𝗲𝗿 while creating a brighter future for humanity. For anyone thinking deeply about the intersection of technology, humanity, and organizational transformation, 𝘈𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴 𝘛𝘳𝘢𝘯𝘴𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯 is a must-read. Add it to your list, and let me know how his ideas affected yours. I’m sure you’ll find something useful and inspiring. (Quick shout-out to Michael Carroll for putting Brian and his work on my radar screen!)

🔬Being Data-Driven is unscientific, and I can prove it. 📍video recorded at Amazon Web Services (AWS)’s office in Seattle at the kickoff to our Executive Breakfast Club, which I had the pleasure of cohosting with Jelena Joffe Weil and Kate Niedermeyer. Thanks for joining us and snapping this, John Kraski!

AI agents are so hot right now! But most people have them all wrong. They are creating one man bands. When in reality they should be creating symphonies. The future of the internet is a full AI agent tech stack. Trust me on this one. Check out another wonderful video with Brian Evergreen at his breakfast co-hosted with AWS Venture Innovation and Jelena Joffe Weil.

A harsh AI truth: Being strictly data driven is highly unscientific when it comes to AI. Don’t believe me? Watch this video with Brian Evergreen one of the world’s top AI minds just dropping the AI knowledge like it’s hot!

The biggest mistake companies are making when it comes to AI? They are trying to only problem solve. When in reality they should also be future solving. Watch this amazing video of Brian Evergreen breaking it all down at his AI breakfast hosted with AWS Venture Innovation and Jelena Joffe Weil.

Execs in Seattle—do you have breakfast plans tomorrow? (We still have a few spots left) We have VP through C-level execs joining from: - American Express - Edelman - State of Washington - F5 - DocuSign - AWS and more. I’ll share a few remarks about my new book Autonomous Transformation (with signed copies for everyone, courtesy of Amazon Web Services (AWS) Venture Innovation). Attire is: holiday sweater optional And John Kraski is flying up from Los Angeles to join us. This is an invite-only event, but we have a few spots left, so we’re opening up to more F2000 VP+ execs. If that’s you, you can see more details and apply to join us here: https://lu.ma/ix98wiy6

Suddenly everyone's talking about AI agents. (But we're not all talking about the same thing) There are three main definitions of AI agents floating around: - Anything that uses AI and "feels like an agent" - LLM agent: “an artificial intelligence systems that utilizes a large language model (LLM) as its core computational engine.” - Multi-agent: a scripted series of prompts that interact with each other 👎🏼 Here's how I define an AI agent: - "A system that can perform tasks and make decisions on your behalf" Rather than trying to define these systems by how they're made, we need to define them by what they do. Some systems are sources of information, Some can perform research, Some can train or guide you through a process, And some, but only a very small number of systems so far, are actual agents that can act on your behalf (and you know, have agency). When you read or hear someone talking about AI agents, plot what they're talking about on this graph. Are they really talking about AI agents?

CNN has lost 90% of its viewership in the past 3.5 years. And it’s not just CNN. Where and how we get information is shifting. And it comes down to trust. Whom do you trust? Who tells you what you need to know and what it could mean? Take AI - what do you believe about AI? If you wrote a list of each thing you believe about AI, then next to each thing you listed where you read, experienced, or heard that thing — what are your sources?