In chemistry, activation energy is the minimum energy required to start a reaction. It’s the barrier between potential and action, between “I could” and “I did.”
This year, AI collapsed that barrier for me.
As foundation models became better, and the tools built on top of them became more useful, the gap between having an idea and acting on it shrank to almost nothing. And for someone whose natural disposition is to try things, to experiment, to see what happens, this has been transformative. I have embraced using AI for work and play and for much else.
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From Thought to Artifact
I’ve written more consistently this year than ever before.
For many years, I used to maintain a list of ideas that I wanted to explore. Bookmarked sites, academic papers, and spicy social media takes. These ideas often were just abandoned or ignored until I forgot why I wrote them down in the first place.
Now, the time between having an idea, doing the research, writing an outline and then publishing it online has shrunk significantly because of AI. I use skills, deep research agents, and a set of prompts that have let me express myself faster and more coherently than ever before.
My recent post “The Same Window For Everything” exists because I noticed something interesting while reading Kiran Desai, opened Claude to think it through, and found myself with the skeleton of an essay. A year ago, that observation might have stayed in my head, filed away with all the other thoughts that never quite made it to the page.
There’s a passion project I’ve been building, a reading companion I’ll be launching soon. It exists because, in 2025, the distance from “what if I built this?” to “let me try” became trivially small. Just like my writing ideas, I have a huge list of side projects and experiments that I wanted to try but never got off the ground. This year, I did.
But, it’s not all serious stuff! I vibe-coded (built quickly with AI assistance) a tool to help me journal regularly. I use AI to help plan dinner for my kids. I have setup my phone so it launches ChatGPT in “search mode” at the press of a button. And, I ask it all kinds of questions! From dealing with my dog’s flatulence to figuring out why the minivan doors won’t open. I now look up things where before I would have just shrugged and moved on.
I have a different relationship now with making things; one where the cost of trying something has dropped low enough that I actually try it.
The Professional Stakes
Looking up recipes for spaghetti carbonara is all well and good, but AI has had a significant impact on my work as well.
At Jeavio, we’ve taken on more ambitious, outcome-oriented projects. Internal initiatives I sponsor, like our campus programs, have become more ambitious and aggressive because I believe we can get them done. That belief comes from now having enough experience with using AI tools to be confident on what my teams can and should be able to deliver.
We ran a company-wide hackathon late last year and a product-focused one in 2025. The hackathons shifted how Jeavio thinks about and uses AI tooling. They encouraged experimentation and built collective confidence about what capabilities these tools could unlock.
It’s not all fun and cheap inference though. Some projects have been challenging. We’re working at the frontier of what’s possible, and frontiers can be uncomfortable places.
But my risk appetite has increased. I understand the tools better now. I know what Cursor and Claude Code can do and, equally important, where they fall short. I have a clearer understanding of what guardrails should be in place and how to evaluate the performance of inherently probabilistic systems. That understanding translates into confidence: confidence to take on projects with ambiguity, and confidence to deliver clearer projects faster and more predictably.
The throughline is the same as the personal examples: lower activation energy. Faster exploration, quicker iteration, more willingness to try things that might not work than ever before. For my work at Jeavio, this is an energizing change.
Cyborgs and Foxes
Two frameworks have helped me make sense of what’s changed.
Ethan Mollick, in his research on AI and knowledge work, distinguishes between Centaurs and Cyborgs. Centaurs maintain a clear division of labor between human and machine, handing off discrete tasks to AI. Cyborgs blend the two. As Mollick puts it:
“Cyborgs don’t just delegate tasks; they intertwine their efforts with AI, moving back and forth over the jagged frontier.”
I’ve become a Cyborg.
AI is woven into how I think, write, and build. When I’m reading and want to explore an idea, I open Claude. When I’m coding and hit a wall, I think through the problem with an AI collaborator. The boundaries between what is truly my work and what is AI-mediated have become somewhat meaningless.
The second framework comes from David Epstein’s book Range: Why Generalists Triumph in a Specialized World. Drawing on Isaiah Berlin’s famous distinction and Philip Tetlock’s research on forecasting, Epstein contrasts hedgehogs, who know one big thing deeply, with foxes, who know many things and integrate broadly.
Hedgehogs thrive in stable, rule-bound environments. Foxes thrive in ambiguous, rapidly-changing ones. As Epstein writes:
“Foxes see complexity in what others mistake for simple cause and effect. They understand that most cause-and-effect relationships are probabilistic, not deterministic.”
I’ve always been a fox.
Broad curiosity, comfort with ambiguity, a tendency to wander across domains. But being a fox is expensive and risky. Every new domain requires starting from scratch. The activation energy to explore something unfamiliar is high.
AI subsidizes that cost. Becoming a Cyborg helps make my fox-like tendencies viable in ways they weren’t before. I can move into an unfamiliar domain, quickly get oriented, experiment, and learn, all without the friction that used to make such exploration feel indulgent.
These frameworks work on orthogonal dimensions. Cyborg describes how I work. Fox describes who I am. Becoming a Cyborg made me more comfortable leaning into my fox-ness.
Looking Forward
I’m aware this could sound like boosterism. The AI discourse is full of inflated predictions and productivity theater.
So here’s what 2025 has taught me. Becoming a Cyborg works for me. This may not always be true.
Maybe I am just a frog slowly boiling to irrelevance as AI takes away my agency and creativity.
Maybe the AI bubble might burst, and Anthropic and OpenAI will raise prices making vibe-coding a passion project or having a long conversations about literary fiction non-viable.
But until then: the distance between curiosity and creation has collapsed. I intend to exploit that gap.
More experiments. More wacky things. More small wins and instructive failures. The activation energy is low, and I have a lot of ideas. Bring on 2026.