I remember exactly how I felt when I first encountered ChatGPT, at the end of November 2022. It wasn’t fear. It was exhilaration. Having spent two decades in the information services sector, I could see the opportunities ahead and sense the magnitude of what was coming. We’d been building machine learning capabilities at PatSnap since the early deep learning era around 2012, training models on the world’s patent and R and D literature for more than a decade. So when the generative AI wave hit, it felt less like disruption and more like validation.
Matt Shumer’s viral essay “Something Big Is Happening” captured what many of us building in AI already know. We’re in the early phase of something far bigger than most people realize, and the single greatest advantage right now is simply being early. Early to understand it. Early to use it. Early to adapt. I agree with that urgency completely.
But I want to add something to the conversation that the productivity discourse keeps missing. The human operating system matters too. If we burn out the people driving the adaptation, we lose the race anyway.
3 Ways to Prevent AI Burnout
- Treat recovery as a performance metric.
- Treat unstructured thinking time as a strategic asset.
- Lead by example on sustainable intensity.
Exponential Technology, Linear Biology
We’re living in the exponential age. AI capabilities are compounding weekly. Every founder and executive I know feels the pressure to ship faster, learn faster, decide faster. That pressure is legitimate, and the window for competitive advantage has never been shorter. As Shumer puts it, “not quite there yet” in AI terms has a way of becoming “here” faster than anyone expects. The experience that tech workers have already had, watching AI go from helpful tool to genuine coworker, is the experience every knowledge worker is about to have.
But here’s what the discourse around urgency misses. SSRI prescriptions in the US are climbing across age groups including adolescents, young adults and adults. Anxiety is a global epidemic. But this goes deeper than anxiety and medication.
The always-on, hyper-stimulated way we work is driving hormonal and neurotransmitter imbalances that compound over time: chronically elevated cortisol, disrupted serotonin and dopamine pathways, suppressed testosterone and growth hormone.
These aren’t just mental health problems. They reshape body composition, destroy sleep quality, erode cognitive sharpness and change behavior in ways people don’t even recognize in themselves. You can feel it when you pick up your phone at 6 a.m. and your cortisol spikes before you’ve even had a glass of water. Our brains, our nervous systems, our biology. They don’t compound like AI does. They degrade under relentless pressure. We need sunlight, stillness and recovery. The machine does not.
It’s worth distinguishing AI productivity tools from the last wave of technology that reshaped how we work and live. Social media was designed for compulsive engagement. The infinite scroll and variable reward works to maintain our attention as long as possible.
But AI tools, used intentionally and effectively, do the opposite: They compress the time spent on routine cognitive work and return that time to you. AI won’t pull us in the way our phones do. The risk is that the speed it unlocks creates its own pressure to fill every recovered hour with more output.
AI will reshape how we work, and the question now is whether it sets the pace or we do. Getting that right isn’t a reason to slow down. It’s a reason to get smarter about how we sustain the pace.
Lean Into What’s Hardest to Replace
Shumer is right that the people getting ahead aren’t using AI casually. They’re pushing it into their actual work. Feeding it contracts, messy spreadsheets, quarterly data and automating work that used to take hours. At PatSnap, we’ve built agentic systems that can analyze an entire patent landscape in minutes. The speed is real, and you absolutely must embrace it.
But the question that follows is just as important. Once AI handles the routine cognitive labor, what’s left? What’s hardest to replace?
I’m dyslexic. For most of my life, I was made to feel like that was a liability, but now I think it’s been one of my greatest professional advantages. My brain doesn’t read something and file it away neatly. It holds onto threads over time. A comment from a colleague six months ago, a podcast I half-listened to, a pattern from an unrelated industry. Then suddenly they connect into something I hadn’t considered before. That kind of thinking is not fast, and it’s not linear. But it’s exactly what no AI system can replicate because it emerges from lived experience. It’s judgment, not optimization.
Studies show that rest is crucial to cognitive performance. Even short periods of downtime enhance our ability to encode and process information by desynchronizing cortical circuits. What looks like idle time is often the precondition for the breakthrough. The companies that will dominate this decade need both. They have to execute work urgently, and they must deliberately protect their people’s mental bandwidth through culture, rhythm and leadership.
Adapt Fast, Recover Faster
Shumer frames adaptability as the most important skill of this era. I’d go further and argue that sustained adaptability is. Anyone can sprint through a quarter. The question is whether you’re still sharp, still creative, still making good calls in year three of the exponential age. That’s a recovery question as much as a strategy question.
I’ve been experimenting with this approach personally. I wear a Whoop tracker, and I treat my biometric data with the same seriousness as a revenue metric. I can see my body’s response to back-to-back calls with no breaks, and I can see how that data translates to the quality of my decisions. The data is unambiguous. Recovery drives performance. Not occasionally, but consistently.
As a leader, this has shaped three principles I’m building into how we operate.
1. Recovery As a Performance Metric
First, treat recovery as a performance metric, not a perk. I wear a Whoop tracker and review my biometric data the way I review a dashboard. What it shows, consistently, is that the days after poor recovery aren’t just harder emotionally. Decision quality drops, risk tolerance skews, and you become a worse version of the leader your team needs.
Organizations can operationalize this without everyone wearing a tracker. Build recovery checkpoints into team rhythms, normalize capacity conversations in one-on-ones, and treat “I’m running on empty” as a signal worth acting on. The athlete who skips recovery doesn’t win more races. They get injured, and so do the teams led by people who never stop.
2. Unstructured Thinking Time As a Strategic Asset
Second, protect unstructured thinking time as a strategic asset, and be specific about what that means. Not “go for a walk,” but actual calendar space with no deliverable, no output, no follow-up required. The insight that changes your roadmap rarely comes from the eighth consecutive call. It comes when a pattern that’s been quietly forming finally has room to surface. As a leader, ask yourself: Can my organization afford the compounding cost of never dedicating time to simply thinking?
3. Lead By Example on Sustainable Intensity
Third, lead by example on sustainable intensity. Culture travels through behavior, and specifically the behavior of whoever holds the most power in the room. If you’re sending Slack messages at midnight, your team doesn’t read that as dedication. They read it as the baseline and adjust accordingly. Sustainable intensity means being visibly disciplined about your own limits. Block focus time and defend it. Treat rest not as something you’ve earned after the sprint but as part of the infrastructure that makes the sprint possible.
The Real Race
Let me be clear. I am not arguing for slowing down. Something big is happening, and the founders and teams who hesitate will be overtaken. Push AI into the routine work precisely so your team has the space to do the thinking it cannot do now. Automate ruthlessly. Be early. The exponential age rewards speed, adaptability and relentless curiosity.
But the race isn’t human versus machine. It never was. The race is between organizations that burn through their people chasing the machine and those that build teams resilient enough to keep compounding over years. The former might sprint faster in Q1. The latter will still be standing, and winning, in 2030.
Move fast. Embrace every tool at your disposal. But invest in the one system that no API can replace: The humans doing the thinking. The companies that get this balance right won’t just survive the exponential age. They’ll define it.
