The Productivity Paradox: AI reduces production costs but drastically increases the costs of coordination, review, and decision-making.
Siddhant Khare
We’ve all heard the promise: AI will save us hours of work, automate the mundane, and leave us with more time for “deep thinking.” But if you’ve spent the last few months juggling five different LLM tabs while feeling a strange, nagging sense of burnout, you aren’t alone.
I recently read a fantastic piece by Siddhant Khare titled “AI fatigue is real, and nobody talks about it,” and it puts into words something many of us are feeling but haven’t quite articulated yet.
The Productivity Paradox
The core insight of Khare’s article is as powerful as it is sobering: AI reduces production costs but drastically increases the costs of coordination, review, and decision-making.
On paper, our throughput has skyrocketed. What used to be a three-hour task—like scaffolding a new service or drafting a design doc—now takes 45 minutes. But here is the catch: we aren’t using that saved time to rest. Instead, we are adding more tasks to it.
As Khare points out, when individual tasks become faster, our capacity appears to expand. Managers see faster shipping, expectations adjust, and suddenly the “baseline” moves. We’ve traded one deep, focused problem a day for six shallow, AI-assisted problems.
From Creators to High-Speed Editors
The shift is psychological. Creating is often energizing; it involves flow states and “aha!” moments. Reviewing, however, is inherently draining.
By leaning on AI, we have transitioned from being creators to being high-speed editors and filters. We are now the “human in the loop” responsible for:
- Verification: Is this code actually secure, or just “correct-looking”?
- Context: Does this generated text align with our specific brand voice or project history?
- Coordination: Managing the flood of output that we—and everyone else—are now producing.
The “doing” might be faster, but the burden of ensuring quality and making the final call falls entirely on us. That mental load is heavy, and unlike the AI, the human brain doesn’t scale horizontally.
The Cost of the “Always-On” Sprint
When we use deterministic tools, we control the pace. When we use non-deterministic AI tools, we are in a constant state of vigilance. We are waiting for generations, prompting, re-prompting, and then bracing ourselves for the cognitive tax of a review.
Khare’s article reminds us that “more output” does not automatically equal “more value.” If we are shipping faster but burning out our best thinkers, we are merely building on a foundation of “productive exhaustion.”
How to Fight AI Fatigue
If you’re feeling the weight of the AI assembly line, Khare suggests a few ways to regain your sanity:
- Time-box AI sessions: Don’t let the “prompt spiral” eat your whole day.
- Separate Thinking from Executing: Protect your morning for deep work without AI assistance.
- Accept “Good Enough”: Stop trying to prompt your way to a 100% perfect result; get it to 70% and finish the rest yourself to save the mental energy of endless iterating.
Final Thoughts
AI is a tool, not a replacement for the human capacity to think, rest, and reflect. If we don’t talk about the fatigue it creates, we risk becoming the bottleneck in our own lives.
Thank you to Siddhant Khare for starting this conversation. If you haven’t read the original piece yet, I highly recommend checking it out here: AI fatigue is real, and nobody talks about it.
