When Time Is No Longer Linear: Cognitive Overload in Software Engineering
In software engineering, progress isn’t just about what we build—it’s about understanding what we’ve built. It’s measured by how our work impacts the business: was it the right thing? Can our customers leverage it effectively? Can we explain it to stakeholders to ensure everyone is aligned?
With AI agents and models enabling us to write code faster than ever, the mental gymnastics required to keep up can feel overwhelming. Lately, I’ve found myself caught in a strange paradox:
while my ability to produce has skyrocketed, my ability to process and comprehend has struggled to keep pace.
It’s as if my brain has a built-in system of checks and balances—a mechanism that forces me to slow down to truly understand what’s been created. But the more I rely on AI to assist in building, the more this balance feels strained, like a circuit board nearing its limit.
The Role of Collaboration in Staying Grounded
Fortunately, I don’t navigate this alone. Most of my days are spent pair programming with LedgerAI’s Lead Software Engineer, Nate Ferrero . Together, we tackle the complexities of building something innovative while trying to stay grounded in the process.
One of the benefits of working so closely with someone like Nate is his ability to bring a sense of calm to even the most intense workflows. He often reminds me, both in words and through his demeanor, that the building piece is actually quite easy when you’re fully in sync, together. No red tape. No space for confusion.
It’s a sentiment that rings true.
Nate, a prolific thinker in many ways, helps ground our team with his calm perspective, allowing us to carry the weight of each day’s work. Pair programming with him isn’t just about shared coding responsibilities—it’s about creating a shared mental space where focus and understanding can thrive.
But even with two brains tackling the problem, we both find ourselves out of sorts earlier in the day than we used to. Many days, when I comment on feeling disoriented, exhausted, or even experiencing headaches, Nate will gently remind me:
“Ash, time is no longer linear.”
That phrase hits home. As engineers, we’re used to thinking about time in logical sequences—steps in a process, tasks in a sprint, lines of code executed in order. But the reality of working with AI introduces a new rhythm, one where time bends and twists. What used to take hours now takes minutes, but the cognitive demand to make sense of it all doesn’t scale down proportionally.
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Pair programming in this environment has another benefit: it keeps us both on the same path. We’re running dangerously fast, and with both of us building together, there’s no room to lose sight of where we’ve been.
The Mental Health Cost of AI-Assisted Development
AI tools are incredible productivity boosters, but they also present a mental health challenge. The feeling of constantly being behind—not in terms of deadlines but in understanding—creates a persistent undercurrent of anxiety. It’s the weight of trying to stay ahead of something that’s already ahead of you.
For me, this manifests as fatigue and unease. Do I truly comprehend what we just did? As CTO, it’s my job to know every corner of this application, after all. For Nate, it might be the calm realization that time itself feels warped. Together, we’re navigating this new frontier, but the path isn’t always clear.
Finding Balance in the Warp
To manage the cognitive overload, we've started building rituals into our day:
Nate and I often joke that our conversations about engineering have become philosophical, but there’s truth in it. The work we do isn’t just technical—it’s deeply human. In an era where time is no longer linear, finding balance may mean redefining productivity, not by how much we build but by how much we truly understand.
Embracing the Paradox
As software engineers, we’re trained to embrace complexity, but the age of AI demands something deeper: resilience in the face of cognitive overload. The tools we use are changing faster than we can adapt, but perhaps that’s the point. The process of catching up to our own creations is where growth happens.
In the end, it’s not just about writing more code, faster. It’s about building something meaningful—and understanding it well enough to stand by it.