Burnout rates in technology climbed again last year. The irony runs thick. Tools that promise to accelerate work by factors of two to one hundred times have instead left many professionals juggling more open tasks than ever.
Rick Manelius captured the shift in a newsletter post published yesterday. He described how artificial intelligence first sparked a burst of ambition among founders and creators. Side projects that once sat dormant suddenly seemed within reach. “Claude: ‘But, maybe you can do it all now that I’m here!’” he recalled the model suggesting. The result? A list of one hundred article outlines ballooned into forty active proof-of-concept efforts. What began as efficiency turned into a cascade of make-work.
“You can have anything in life, but not everything.” That line, pulled from years of wisdom on priorities, lands harder in an era of abundant generation. Manelius drew directly from Greg McKeown’s book Essentialism, which urges doing less but better. The lesson feels newly urgent. Rick Manelius’s newsletter frames the emerging advantage not as speed alone but as the discipline to apply that speed selectively.
Recent data backs the observation. Lenny’s Newsletter surveyed tech workers this month and found burnout had jumped eleven points in a single year. Half the workforce reports feeling energized by artificial intelligence. The other half feels disoriented or resentful. “The great tech bifurcation: half the workforce is thriving, half is struggling, and burnout just hit a record high,” the July 12 report stated. Lenny’s Newsletter.
Yet the pattern repeats across industries. Professionals who once guarded their calendars now watch AI generate drafts, code snippets, and analyses in seconds. The temptation is to fill the freed time with additional initiatives. Invented responsibilities multiply. The same finite hours remain.
Garry Tan illustrated the difference with a striking comparison. A partial solar eclipse and a total one differ by just one percent of coverage. The visual and emotional impact, however, multiplies a hundredfold. The same principle applies to creative and professional output. That final increment of refinement often consumes half the total effort. Most stop at good enough. Those who push through produce work that lingers.
Manelius chose to apply the idea immediately. He had been rushing an article titled “Sesame Street Simple.” Realizing it fell short of his standard, he paused. The piece now receives two or three additional focused revisions. The decision cost short-term velocity. It preserved long-term quality.
Executives and researchers echo the theme. In a January analysis of AI fatigue, contributors noted that constant oversight of model output creates its own exhaustion. “AI brain fry,” one LinkedIn post termed the phenomenon of endless reading, approving, and correcting. The fix? Write first, then prompt. Ask the model to critique logic rather than generate from scratch. Preserve the human role in judgment. LinkedIn post by Amantha Imber.
Taste has surfaced as the distinguishing factor. Vanessa Andreotti, in a LinkedIn discussion, argued that success increasingly hinges on craft, judgment, decisiveness, and determination. Expertise alone no longer suffices when models can synthesize vast information. Agency decides what deserves attention and when to stop. The post gained traction among strategists watching the transition.
A Medium essay from late last week reinforced the point. “The Risk of Burnout: If you outsource all the problem-solving to AI, you deny yourself that reward. You risk becoming a bored ‘manager’ of code rather than a creator.” The author, Natan Shalom, stressed the need for research taste. Knowing which problems merit personal struggle separates those who advance from those who merely supervise. Medium article by Natan Shalom.
Enterprise leaders are adjusting their expectations for 2026. A Zapier analysis released this week found companies plan to scale AI maturity while redefining roles. “AI couldn’t assess ‘taste’ or cultural fit. The lesson we’re taking into 2026 is that AI can support the process, but can’t own it,” said AJ Eckstein. The report highlights governance, compliance, and human oversight as growing priorities. Zapier playbook on AI transformation.
Greg McKeown himself has addressed the intersection. In a recent podcast he warned against over-reliance. “If you start relying on AI for everything and you lose your own reasoning, critical thinking and human skills, you’re going to lose the one thing that you have a chance of being better at for the next 10 or 20 years.” The disciplined pursuit of less, he maintains, becomes even more powerful when amplification tools abound. Elevate Podcast with Greg McKeown.
Conversations on X this weekend show the idea spreading. One user wrote that “With #AI, focus is amplified and becomes a superpower. The pace of execution accelerates exponentially.” Others emphasized intensity over duration. Two hours of concentrated effort outperform ten hours of scattered activity. The posts, though varied, converge on a single observation: selectivity compounds.
Yet the pressure to produce volume persists. Corporate environments still reward visible activity. Promotion cycles favor those who ship frequently. The counter-movement requires courage. It means saying no to promising but non-essential experiments. It means accepting that some generated content will never see daylight.
Manelius plans fewer articles going forward. Each will receive deeper attention. The approach mirrors what many high-performing teams quietly adopt. They limit active initiatives. They allocate uninterrupted blocks for refinement. They treat the last mile of quality as non-negotiable.
Product builders at companies like Linear have spoken about similar habits. In an interview with Lenny’s Newsletter, founder Karri Saarinen described building with taste, craft, and focus. The conversation, published alongside the sentiment survey, underscores that these traits separate memorable products from functional ones.
So the new hierarchy emerges. Raw generation belongs to the machines. Curation, discernment, and persistence belong to people. Those who master them gain an edge that scales with capability rather than competing against it.
Burnout need not define the next phase. The tools exist to eliminate drudgery. The choice is whether to redirect that capacity toward depth or diffusion. Early evidence suggests the former delivers results that feel qualitatively different. Like the difference between twilight and totality. The sky does not merely dim. It transforms.
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