Gergely Orosz on AI token usage being set as a KPI
The Pragmatic Engineer author Gergely Orosz responded to a plea for help from a middleware engineer in South Korea: their manager, influenced by the GenAI hype, set "AI token usage" as a KPI and repeatedly pressured the engineer because they rarely use AI. Orosz believes the manager is using a clumsy approach to push them to adapt to change, and says "excellent" and "refusing to learn new things" are not mutually exclusive—refusing to adapt is still unprofessional. He offers two paths: accept that AI is changing how work is done, or honestly bear the cost of refusal—the companies willing to hire you will keep shrinking.
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View original postA middleware engineer in South Korea wrote to me, seeking help on what to do now that their manager is "blinded by GenAI hype" and set an "AI token usage" KPI. This eng is using v little AI, so manager is poking them to use more. My response: your manager is trying to help you https://t.co/i0hjgUCSYA
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A middleware engineer in South Korea wrote to me, seeking help on what to do now that their manager is "blinded by GenAI hype" and set an "AI token usage" KPI. This eng is using v little AI, so manager is poking them to use more. My response: your manager is trying to help you https://t.co/i0hjgUCSYA
Body · AI translation
The Pragmatic Engineer author @GergelyOrosz shared a very typical problem for developer friends: the boss has been brainwashed by all kinds of explosive AI news and has set "AI token usage" as a KPI! And the engineer asking for help rarely uses AI, so he keeps getting hammered by management. He feels a lot of pressure and believes he has been labeled as an "outdated, inefficient engineer who refuses to embrace new technology."
Gergely's stance surprisingly sides with management:
1. Reinterpreting management's motive: the manager isn't picking on you, he's "helping" you; he's using a clumsy way to push you to adapt to an inevitable industry change.
2. Bluntly agreeing with that label: the engineer complained about being stigmatized, and Gergely's answer was "unfortunately, that's the fact." He made a key distinction: you may be an excellent engineer, but "excellent" and "refusing to learn new things" are not mutually exclusive. No matter how refined your personal skills, refusing to adapt is still unprofessional behavior. The term "professionalism" is used very heavily here: in his view, continuously learning new tools is itself part of professionalism, not an option.
3. Giving a binary decision framework: for engineers who have "gotten comfortable" in the status quo, there are only two paths · Get on board: accept that AI will profoundly change the way you work, and endure the discomfort brought by rapid change; · Refuse: that's also fine, but you must honestly accept the cost; the pool of companies willing to hire you will keep shrinking, and you can only be self-employed, or simply leave the tech industry.