- Author’s Note & Lived Experience Disclaimer: I am a software engineering leader with an adult ADHD diagnosis who has navigated acute burnout in high-stakes enterprise tech environments. I am not a therapist, clinical counselor, or medical professional. The ideas and perspectives I share are non-clinical personal systems born out of lived experience, trial-and-error, and self-management practices. If you are experiencing severe distress or a mental health crisis, please consult a qualified healthcare provider.
The Spark at Seattle Tech Week
Recently, I attended a Seattle Tech Week workshop at the Seattle Central Library. It was hosted by Dr. Candice Balluru, Licensed Clinical Psychologist and founder of The Workplace Psychologist PLLC.
Her session was titled “Psychological Burnout in the Age of AI.”
Dr. Candice laid out a compelling look at how the conversation around burnout is shifting. Her core thesis hit home: technological integration and AI tools are accelerating at a rate that directly collides with fixed human biological limits.
It was validating, timely, and deeply needed. Especially in an industry currently racing at breakneck speed.
The Clinical Reality Check
During the session, Dr. Candice highlighted a conflict that isn’t talked about enough.
Executives are trying to figure out what AI can do for the business. Meanwhile, they are asking workers on the ground to just “figure it out.”
But learning, prompting, and validating a new AI system requires significant cognitive energy. To absorb these tools, your output actually has to slow down first.
She broke down our daily human cognitive capacity into two distinct modes:
- Volume Work: Transactional, high-frequency tasks like answering emails, replying on Slack, and basic administrative updates. Our brains can handle up to 4 hours of this per day.
- Depth Work: Deep problem-solving, synthesis, architecture, and critical evaluation. Our brains can only sustain about 90 to 120 minutes of true depth work per day.
When AI tools compress our depth work, companies tend to fill that newly opened time with more volume work.
Instead of getting a cognitive break or redirecting our energy to high-level oversight, we end up drowning in micro-tasks. We take a “break” from deep focus by doing four more hours of high-speed shallow execution.
We aren’t working smarter. We are just thrashing.
Bridging Psychology and Engineering
As a sensitive person in tech, an engineering manager, and someone living with adult ADHD, listening to Dr. Candice got my gears turning.
While she approaches burnout through the essential lens of clinical psychology and workplace mental health, I found myself translating those boundaries into the language of systems engineering.
In enterprise tech, when a system collapses under an unmanaged load, we don’t treat it as a moral failure. We don’t tell the database to just try harder.
Instead, we evaluate system capacity. We isolate environmental triggers, adjust our architecture, and implement load balancers.
Yet as technical workers, we rarely grant our own nervous systems that same objective grace.
Dr. Candice’s workshop was the catalyst I needed. It validated the need for systems-level personal solutions, prompting me to organize my own notes and experiences into a cohesive framework. More on this later!
The Attention Asymmetry (Jevons Paradox)
This is the Jevons Paradox of attention. As token costs slide toward zero, the cost of generating text drops to nothing. So we generate more of it—automated Slack summaries, infinite PR descriptions, endless Jira updates.
Our cognitive load (attention span) is a resource. As AI makes generating text more efficient, we don’t use less cognitive load, we use more until it is completely exhausted.
But the cost of reading, processing, and understanding that text remains completely fixed. Human cognitive bandwidth doesn’t scale. The cheaper it is to write, the more expensive it becomes to read it all.
If you’re a developer, you feel this daily. You’re trying to debug a race condition, but your Slack has three bots summarizing other bots, and your inbox is flooded with AI-generated status updates that take longer to parse than the actual code changes.
So how do we survive the flood?
It starts with basic attention hygiene:
- Skip the machine noise: If a colleague couldn’t spend two minutes writing a human TL;DR, you don’t owe them ten minutes parsing their AI-generated wall of text.
- Write like a human: Keep your PR descriptions brief. Keep Slack messages to one or two punchy sentences. Make your thoughts easy to digest.
- Treat attention as a tax: Every time you hit send, you’re taxing someone else’s limited processing power. Be a light tax.
Bonus: Put two humans in the loop. I’m half kidding here because having a human in the loop is supposed to keep AI from going off the rails but hear me out…
Instead of prompting a bot when you know it’s just going to trigger an alert for another human, try setting aside time to speak with that human directly. Invite them to the break room for a chat over coffee, or grab a 15-minute Zoom (and really keep it to 15). People destress and relax around other chill people. So far, AI hasn’t been shown to help us relax.
Critics will point out that individual behavioral hacks won’t solve a systemic technological crisis. They’re right. As long as the cost of generation is near zero, the flood will keep coming.
But until the industry refactors its macro incentives, you still have to run your own system. The practical fix is learning to filter out the noise and refusing to let cheap generation hijack your expensive attention.
Pro Tip: Treat your attention span like a finite resource. If you don’t periodically flush the cache and kill runaway processes, the whole system crashes. And unlike a VM, you can’t just reboot your brain in ninety seconds.
What’s Next: An Upcoming Series on my blog
Inspired by that room in the Seattle Central Library, I’m launching a multi-part blog series here.
Over the coming weeks, I’ll be sharing a personal, systems-oriented exploration of burnout, stress, and sustainability in tech.
We’ll look at how non-clinical framing, environmental design, and self-awareness can help us navigate high-velocity work environments. Especially for those of us managing neurodivergence or sensitivity in technical roles.
I want to extend a sincere thank you to Dr. Candice Balluru for leading such an important discussion at Seattle Tech Week and sparking this next chapter of writing for me.Stay tuned—Post 0 is officially set. Post 1 will be dropping soon.
Follow along on LinkedIn as we explore how to re-architect our systems and reclaim our focus.
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