Damian Nomura recently shared something that made me stop scrolling: "AI was supposed to give us more time. Instead, it just raised the bar." In his viral LinkedIn post, he goes on to describe what Wharton researchers call "the efficiency trap" and how, after an afternoon with three AI terminals running, "anything less felt like slacking."

To ground this, here is a short excerpt from what Damian wrote:

AI was supposed to give us more time.

Instead, it just raised the bar.

Wharton researchers call this "the efficiency trap."

Here's how it works:

→ You complete a project in 3 days instead of 5
→ Great. Now 3 days is the new expectation
→ The time you saved doesn't become free time
→ It becomes time for more work

That idea hit a nerve with me, and judging by the post's engagement, it resonated with thousands of others who feel both more productive and more overwhelmed at the same time.

The AI efficiency trap Damian Nomura described

As Damian Nomura pointed out, AI was sold to us as a way to reclaim hours in the day. We imagined shorter workdays, more creative time, and space to think strategically instead of grinding through repetitive tasks.

But the reality in many workplaces looks different:

The report that used to take you five hours now takes one.
The presentation that used to take a week now takes a day with AI assistance.
The email sequences, code drafts, and market research can be generated in minutes.

And yet, no one is going home earlier.

Damian captured the cycle perfectly: once you show you can do something faster, the faster pace becomes the new baseline. The time you "freed up" is quietly reallocated to more tasks, more projects, and more expectations.

When productivity gains become the new baseline

This is the core of the efficiency trap. Every gain in efficiency is treated not as a one-time bonus, but as a permanent upgrade in what "normal" looks like.

In practice, that can sound like:

"You finished that analysis in three days last quarter—so we'll assume three days is standard now."
"You used AI to write that deck? Great, then you can handle two decks instead of one."
"Since your inbox is under control, let's add a few more responsibilities to your plate."

None of this is malicious on its own. Managers are under pressure. Teams are understaffed. Organizations are chasing growth. When a powerful new tool appears, it's natural for leaders to see it as a way to do more, faster.

But as Damian highlighted, that logic has a human cost. Workers report feeling "simultaneously more productive and more overwhelmed." Your output climbs while your sense of control and well-being quietly erodes.

This isn't a bug in AI. It's how we use it.

One of Damian Nomura's most important lines in the post is this:

This isn't a bug in AI.
It's how we've designed our relationship with productivity tools.

We tend to optimize for output and assume the humans will adapt. Historically, that looked like email, smartphones, and chat tools that made us "always on." Today, it's AI tools that make us "always faster."

When you plug AI into that same mindset, you don't get liberation. You get acceleration—and acceleration without limits eventually feels like burnout.

The unspoken agreement at work

Most of us operate under an unspoken agreement: "If I become more efficient, my job will feel easier."

What Damian's post reveals is the darker version of that agreement: "If I become more efficient, my job will just expand to fill the space."

That's the psychological trap. Your brain remembers how much you got done on that one hyper-productive, AI-powered afternoon. As Damian experienced, the next day your brain expects that pace to continue. Anything less feels like slacking—even if that pace is unsustainable.

Over time, you can end up:

Pushing yourself to maintain "AI-boosted mode" every day.
Feeling guilty whenever you're not maximally optimized.
Losing the distinction between healthy effort and harmful overextension.

Redesigning our relationship with AI tools

If the problem isn't AI itself but the way we use it, then the solution has to be intentional design—at both the personal and organizational levels.

Here are a few shifts that build on Damian Nomura's insight:

1. Treat AI gains as optional margin, not mandatory output

When AI helps you finish something in three days instead of five, ask: "What do I want to do with the two days I just got back?"

That could mean:

Investing time in deep thinking, learning, or experimentation.
Improving the quality of the work instead of just the quantity.
Blocking off recovery time so you don't operate at redline all week.

The key is to consciously resist the reflex that "free time must be filled."

2. Set humane baselines before you automate

Before you apply AI to a workflow, define what a healthy, sustainable pace looks like without it. Then decide in advance how much of the AI-driven efficiency will translate into more output—and how much will translate into more breathing room.

This protects you from quietly raising the bar on yourself every time a new tool appears.

3. Make expectations explicit with your team

The efficiency trap thrives in silence. If your manager sees that you're suddenly twice as fast, they may naturally assume that's the new normal—unless you talk about it.

Practical moves:

Share that your recent sprint was boosted by a specific AI setup and wasn't meant to be your new everyday pace.
Propose guidelines: for example, "AI lets us handle spikes and special projects, but our standard workload stays here."
Encourage team norms that celebrate sustainable productivity, not just heroic bursts.

Leaders, in particular, have a responsibility here. If you treat every AI gain as a reason to raise targets, you're training your team to hide their tools or burn out using them.

Practical ways to avoid burning out with AI

To translate Damian's warning into action, consider:

Time-boxed intensity: Use AI to sprint for a defined window, then deliberately downshift.
Scheduled slack: Block time on your calendar that is protected from AI-enabled work—thinking time, learning time, or simply non-optimized work.
Quality over volume: Measure success by outcomes (clarity, impact, reliability) rather than sheer volume of tasks completed.
Regular check-ins: Ask yourself weekly, "Do I feel more in control or less in control since adding this AI tool?"

If the answer is "less in control," you're likely slipping deeper into the efficiency trap.

The human question behind AI avatars

At the end of his post, Damian Nomura mentions that the accompanying video isn't really him—it's an AI avatar. He asks: is it soulless, or a successful experiment?

That question connects to the same theme. As AI lets us clone our presence and accelerate our output, we risk separating "what looks productive" from "what feels human."

AI avatars, automated content, and synthetic meetings might save us time—but if we simply use that time to cram in more work, the net effect on our humanity is negative.

The real opportunity is to let these tools handle low-value presence so we can show up more fully, more authentically, in the moments that matter.

Closing thoughts

Damian Nomura's post is a timely reminder that tools do not automatically free us; culture decides what we do with the freedom they create.

AI can absolutely reduce drudgery and open up space for creativity, rest, and deeper thinking. But only if we resist the reflex to turn every efficiency gain into a new expectation.

Use AI to raise the quality of your work, not just the quantity of your workload. Protect the time it saves you as fiercely as you protect a project deadline.

This blog post expands on a viral LinkedIn post by Damian Nomura. View the original LinkedIn post →