After 23 years in corporate full-time roles, leading teams large and small, 2025 was the first full year of being an independent AI advisor, thought leader, speaker, author, and trainer. Time for a recap.
If anything stands out, it's intentionally saying YES to too many things in order to learn and explore as much as I could. I had a simple goal of answering three questions this year: Where is the money? Where is the fun money? And what am I not going to do again? So, I could narrow down where to focus in 2026.
Being independent not only changes the game, but also its rules. Luckily, you get to write some of these rules yourself. For me, it was defining a flywheel of four equal parts: industry insights, advisory, speaking, and workshops/ training. Insights from one dimensions increase my relevance for the next, and everything I create has to be reusable more than once to minimize rework.
Speaking
If you want to be a speaker, you need to speak. It’s as simple as that. Sometimes, it’s giving the main keynote at an industry conference or a vendor event, and rearranging your talk track on short notice (or even creating a new one). Other times, it’s moderating panels at Philly Tech Week, Generative AI Week, or The AI Summit.
Among this year’s highlights is giving the opening keynote for the Project Management Institute’s Community AI Day, which more than 15,000 members have watched to date.
My takeaway: Nothing beats the level of ownership of articulating your own thoughts and sharing your own message. Nothing beats the confidence that comes from your subject matter expertise.
My recommendation: Regardless of the session format, the more aware you are of AI trends and how they relate to different businesses and industries, the easier it all becomes—adapting talk tracks, responding to audience questions, and pivoting at a moment’s notice. It sounds contradictory, but you cannot outsource your knowledge and thinking to AI. Forming your own opinions without AI is one of the most critical things you can do for yourself, not just when you’re independent. (That's not to say you shouldn’t use AI to research and explore information, by the way.)
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Training
Staying ahead of trends and their downstream implications means anticipating demand ahead of time. After creating and filing several courses on LinkedIn Learning from home, I visited the studio in California to record my latest course. It’s all about giving practical tips for preventing low-quality AI-generated content (aka workslop).
Together with business partners in Europe, we help multinationals and solopreneurs alike learn the ins and outs of successful AI leadership.
More than 80,000 learners have taken my courses on LinkedIn learning within the past year. Several of them were part of LinkedIn’s AI Skill Pathways promotion this spring and have helped thousands of learners get practical information on AI agents.
My takeaway: The spectrum of company cultures and personal mindsets is fascinating, and attendees’ questions are a good pulse check for what’s happening inside organizations right now.
My recommendation: Demanding everyone use Copilot or become “AI-first” overnight is a bit silly when the company isn’t even AI-ready yet. Investing in hands-on training through social blended learning as part of your AI strategy leads to much better results.
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True thought leadership requires human thoughts and thinking. Most of the time, it comes from connecting the dots between concepts or curiously asking, “What if?” Other times, it’s learning about where leading industry players are headed.
My personal highlights this year were an event about Agentic AI in the integration layer (MuleSoft) and evolving identity security for agents and users at Oktane (Okta).
My takeaway: Innovation is happening faster than most organizations can adopt it. Having led these conferences and interviews from the vendor side of the table, it’s refreshing to be on the other side now, while having walked in the marketing and PR teams’ shoes.
My recommendation: Whatever domain or industry you are in, strive to stay on top of the key developments and shifts. That way, you can connect the dots, put news at events in context, and gain expertise that makes you a relevant and valuable team member.
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Conclusion
This year, I set my flywheel in motion. Learning about product news has informed my advisory and workshops to help executives get insights beyond prompting 101. In turn, participants’ questions in leadership workshops have helped me make my keynote talk tracks more tangible and identify gaps for new training programs. The list goes on.
In my new book, The HUMAN Agentic AI Edge (available in February), I have summarized my key learnings and recommendations for leaders to shape the next generation of AI-ready teams. Join the waitlist to get the latest infos and launch date: https://humanagenticaiedge.com
Thank you for your readership this year! I can’t wait to continue on this journey with you. Happy New Year!
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The flywheel model you laid out is really well thought through, especially the part about everything needing to be reusable more than once. That constraint forces clarity on what's actually worth creating vs busywork. I've seen too many consultants get trapped in custom one-off deliverables that drain time without compounding value. What jumped out was the Okta identity security piece, becuase agentic AI is already creating huge identity sprawl issues that most orgs haven't even begun to address. The gap between what's being built and what's being secured is getting pretty wild.
"you cannot outsource your knowledge and thinking to AI. forming your own opinions without AI is one of the most critical things you can do for yourself."
this hit different coming from someone who advises on AI for a living.
the flywheel model you've described — insights feeding advisory feeding speaking feeding workshops — is the kind of compounding that actually works. but it only works because you're the one connecting the dots. the AI can't build your relationships. it can't show up at oktane and notice the identity security implications for agents. that's human pattern-matching.
here's the dichotomy i keep circling: the people who understand AI best are often the most clear-eyed about its limitations. meanwhile, the loudest AI evangelists are frequently the ones who've never tried to deploy it in a real workflow. confidence and competence have become inversely correlated.
your "everything i create has to be reusable more than once" constraint is something i'm stealing. that's the discipline that separates thought leadership from content production. most people create for the moment. you're creating for the compound.
curious: after a year of independence, what surprised you most about where the money actually is vs. where you expected it to be?
The flywheel model you laid out is really well thought through, especially the part about everything needing to be reusable more than once. That constraint forces clarity on what's actually worth creating vs busywork. I've seen too many consultants get trapped in custom one-off deliverables that drain time without compounding value. What jumped out was the Okta identity security piece, becuase agentic AI is already creating huge identity sprawl issues that most orgs haven't even begun to address. The gap between what's being built and what's being secured is getting pretty wild.
"you cannot outsource your knowledge and thinking to AI. forming your own opinions without AI is one of the most critical things you can do for yourself."
this hit different coming from someone who advises on AI for a living.
the flywheel model you've described — insights feeding advisory feeding speaking feeding workshops — is the kind of compounding that actually works. but it only works because you're the one connecting the dots. the AI can't build your relationships. it can't show up at oktane and notice the identity security implications for agents. that's human pattern-matching.
here's the dichotomy i keep circling: the people who understand AI best are often the most clear-eyed about its limitations. meanwhile, the loudest AI evangelists are frequently the ones who've never tried to deploy it in a real workflow. confidence and competence have become inversely correlated.
your "everything i create has to be reusable more than once" constraint is something i'm stealing. that's the discipline that separates thought leadership from content production. most people create for the moment. you're creating for the compound.
curious: after a year of independence, what surprised you most about where the money actually is vs. where you expected it to be?