Author: Xu Chao
Source: Wall Street News
AI coding tools promise to liberate engineers, but the reality is they have spawned a new wave of efficiency anxiety.
As the capabilities of AI programming agents like Anthropic's Claude Code and OpenAI's Codex continue to leap forward, tech companies are falling into a top-down "productivity obsession." Executives are personally writing code, employees are required to increase their frequency of interacting with AI, and overtime hours are rising instead of falling. AI, meant to be a labor-saving tool, has instead become a new source of pressure in many workplaces.
Survey data reveals a clear cognitive gap: a survey by consulting firm Section shows that over 40% of C-suite executives believe AI tools save them at least 8 hours per week, while 67% of non-managerial employees say AI saves them less than two hours, or is of no help at all. An ongoing study by UC Berkeley of a 200-person organization found that even as employees offload significant work to AI, their actual working hours are still increasing.
The spread of this anxiety has structural reasons. When CTOs are敲代码 (writing code) with AI at 5 a.m. and CEOs measure team effort by the amount of the bill, the entire industry's imagination of "efficiency" has been redefined—and the cost of this redefinition is being borne by ordinary employees.
Executives Jump Into Coding, Efficiency Anxiety Spreads Top-Down
The term "Vibe coding" initially came with a lazy expectation. Former OpenAI researcher Andrej Karpathy introduced the concept to the public in February 2025, describing a new programming mode where engineers只需与 AI 聊天 (just chat with AI) to complete development—"completely immersed in the vibe."
However, a year later, the vibe has long since changed tone.
Intuit CTO Alex Balazs described his recent routine: his wife came downstairs at 8 a.m. to find he had been working for hours. "She asked me how long I'd been up, and I said I got up at 5 a.m. to write code." More accurately, he was guiding an AI agent to write code for him, which he said allowed him to reconnect with underlying code he hadn't touched in years.
This kind of executive behavior is transmitting pressure downward. OpenAI president Greg Brockman recently posted on X, "Every moment your agent isn't running feels like a wasted opportunity." This statement precisely triggered the workaholic culture already prevalent in the tech industry.
Alex Salazar, co-founder and CEO of AI startup Arcade.dev, is more direct. He regularly checks the company's Claude Code bill—the bill is directly linked to how frequently engineers use the tool—and calls out employees who "aren't spending enough": "I'll say, 'You're not pushing hard enough.'" He said that after the first such "faith meeting," the company's AI programming tool bill soared tenfold, and he sees this expenditure as a sign of progress.
Employees Quantitatively Managed, "AI Fatigue" Quietly Spreads
In this atmosphere, the way employees are assessed is also quietly changing.
DocuSketch, a software company focused on property restoration, tracks the number of "interactions" engineers have with AI programming tools daily, defaulting that the higher this number, the stronger the team's productivity. Claude Code also generates a weekly report for each engineer, listing all the patterns where they got stuck in ineffective loops with AI and offering suggestions for improvement.
Wirick himself admitted to feeling a certain kind of "addiction." "I feel like I must complete a few more interactions each day, and I'm still thinking about how to do a few more before bed." He attributes this state to an "epiphany experience" when trying Anthropic's latest model, Opus 4.5, last November—he gave a functional prototype task that would usually be assigned to an engineer to the model, and 20 minutes later saw the model autonomously break down and implement the task, "feeling like my brain was rebooted."
This all-hands-on-deck acceleration mentality is eroding the boundary between work and life. The Berkeley study found that even though many tasks have been handed over to AI, people's working hours have not shortened. Some engineers are also beginning to openly admit they are experiencing "AI fatigue"—a constant worry about missing the next breakthrough, which always seems just one prompt away.
Cognitive Gap Between Executives and Employees Widens
The enthusiasm of executives stems largely from the novelty of creating things firsthand. Salazar admitted that building prototypes personally with AI provides more of a "productivity visual" than handling authorizations and decisions on a daily basis. He recently even directly responded to a service request from an important financial client by building a demo app from scratch.
At Intuit, product managers and designers are now encouraged to use the "vibe coding" method to build functional prototypes themselves within QuickBooks. Balazs said, "At least now, product managers can take a concrete thing to engineers and say, 'I want something like this.'"
However, survey data from consulting firm Section shows this cognitive gap is quite significant.
There is a huge断层 (fault line) between executives' perception of the AI dividend and the experience of frontline employees. Salazar believes this partly stems from employees bearing a higher transition cost when adapting to new tools: "They are implicitly asked to find time to explore and experiment, but the expectations of daily work haven't been adjusted accordingly to free up this space."
Concerns about job security are equally real. Salazar坦言 (admitted) that he originally planned to switch third-party web service providers, but now the marketing team can update the company website themselves using AI tools, so this outsourcing expense was cut.
"Task Expansion" and False Prosperity, The Other Side of the Efficiency Myth
The Berkeley researchers named this phenomenon "task expansion": when non-technical colleagues start generating code with AI, engineers have to spend time cleaning up these semi-finished products,反而增加了工作量 (instead increasing the workload). Intuit's Balazs坦承 (acknowledged) that this is reshaping previously clear-cut job divisions, pushing more and more roles towards "hybridization," and also making original collaborative relationships more complex.
A deeper question lies: is this construction boom creating valuable things, or is it just制造更多东西 (making more stuff)?
Analysts point out that if this AI-driven productivity obsession is not restrained, it could lead to a surge of "busyware"—minor website tweaks no one will notice, custom dashboards for a single user, prototype projects abandoned halfway by marketing managers, all eventually handed over to engineers to implement. Each seems justified in the moment, but most will end up in the trash can of废弃代码 (abandoned code).
Intuit's Balazs claims that measured by code production and delivery speed, the company's engineers' productivity has increased by about 30%. But in this future where code is increasingly "disposable," the real efficiency dividend might lie in the answer to another question: which things simply shouldn't be built in the first place.
