Shumer warned that white-collar workers have to figure out plan B right now, because a Covid-like extinction event is coming for white-collar work. Almost simultaneously, Microsoft\u2019s AI chief Mustafa Suleyman gave it 18 months before anyone looking at a computer for a living will be out of work within that timeframe. This was a revival of sorts for the sort of doomsday predictions that marked the first half of 2025 before going ominously silent. Anthropic\u2019s Dario Amodei, for instance, predicted that AI would eliminate half of all entry-level white-collar jobs, while Ford CEO Jim Farley said it would wipe out half of white-collar jobs, full-stop. <\/p>\n
Tanmai Gopal says these dire predictions are a classic case of Silicon Valley self-projection, even narcissism. The co-founder and CEO of PromptQL, a $1 billion-plus Bay Area unicorn that helps companies with AI adoption, told Fortune<\/em> in a recent interview that the AI doomsday predictions definitely contain a grain of truth while also being massively overstated. \u201cThat\u2019s 100% what\u2019s happening where you have a bunch of \u2026 people who are in the hype cycle.\u201d Gopal said his community in the valley is \u201cfeeling the awesomeness of this AI\u201d but \u201cwe\u2019re projecting that into domains that we don\u2019t actually understand.\u201d<\/p>\n \u201cIt\u2019s like, oh, this is the problem for 7 billion people on the planet, because I\u2019m in Silicon Valley, so I obviously know what\u2019s best, right?\u201d Gopal also noted that cynics have a point, with these doomsday predictions occurring right around the time of the next funding multibillion-dollar funding round for many AI start-ups that have yet to go public, offering a clear funding rationale that may not bear out. In general, he added, \u201cTech people\u2026 think like, this affects me. So it\u2019s going to affect everyone like that.\u201d<\/p>\n Actually, Gopal said, that\u2019s just not the case. But when it comes to coders, even the senior software engineers, who are exposed to the \u201cawesomeness\u201d of the AI tools now available, he said those people are facing a paradigm shift.<\/p>\n Gopal was speaking to Fortune<\/em> weeks after the \u201cSaaSpocalypse\u201d wiped out $2 trillion in software-as-a-service valuations, with investors realizing, as Bank of America Research recently put it, that AI is a \u201cdouble-edged sword\u201d and not purely an upside play. It could very easily \u201ccannibalize\u201d many businesses, BofA said, such as software that AI is advanced enough to write itself. <\/p>\n Economists have been puzzling over very noisy data over the last year or so, with the U.S. economy largely flatlining in job production while also facing elevated tariff costs and far fewer immigrants entering the workforce. Some AI thought leaders, notably Stanford\u2019s Erik Brynjolfsson, looked closely at the data and saw productivity really starting to lift off in 2025. Writing in the\u00a0Financial Times<\/em>\u00a0op-ed, Brynjolfsson noted the latest jobs report revised all job gains for 2025 down to just 181,000, while his own calculation projected productivity of 2.7% for the year, versus the 1.4% average over the past decade. Of course, this lends weight to the AI displacement theory, with even Federal Reserve Governor Michael Barr recently warning that millions could be \u201cessentially unemployable\u201d in the near future.<\/p>\n Gopal said it\u2019s true that the tech industry has inadvertently automated itself, reaching the era of \u201cbaby AGI\u201d (Artificial General Intelligence) specifically for coding. The latest AI models have the judgment and taste of an \u201caverage senior software engineer,\u201d Gopal said, explaining that standard software engineering heavily relies on converting established business context into technical code and because AI excels at this translation, coding has become the first major domino to fall.<\/p>\n \u201cWhat used to be kind of sometimes considered the epitome\u2026 of white collar was like high-grade software engineering,\u201d Gopal noted. \u201cThat\u2019s been all the rage for the last 30 years and I\u2019m excited to see that go.\u201d He explained that his excitement stems from the robotic nature of the jobs that robots are already starting to perform and what he\u2019s seeing on the frontlines of his company, which helps Fortune 500 companies actually build AI tools and agents that are specialized to their business.<\/p>\n \u201cWhat we\u2019ve been doing over the last year is \u2026 we\u2019ve been working exactly at that intersection,\u201d Gopal said, and for the most part, he\u2019s found that \u201cAI is not useful\u201d because it needs so much business context to be effective. \u201cPeople keep thinking it\u2019s a technical problem,\u201d but it\u2019s really about the difficult fact that AI can\u2019t access business context that lives inside people\u2019s heads and hasn\u2019t been translated to data\u2014and may never be. \u201cPeople are thinking, \u2018Oh, it\u2019s like a semantic layer and a data problem and get your data ready and make it work and whatnot,\u201d but the real issue is that data doesn\u2019t exist for the most useful information that the AI needs. \u201cNobody wrote that down. And if nobody wrote that down, you can\u2019t train AI on it.\u201d<\/p>\n Paradoxically for an AI executive, Gopal said that arguably, many businesses exist that AI can never be trained on, \u201cbecause this is real-life business that moves.\u201d Real people who have conversations and continually update a business context will always be one step ahead of the machines, he explained. \u201cAre you going to retrain for that one individual conversation for one day?\u201d he asked, and then retrain on a rolling basis every time your business context changes?<\/p>\n Gopal agreed with his interviewer that journalism was an example of a profession that could resist automation, because readers are interested in human insight, deep sourcing and forward-looking analysis, things that AI can\u2019t easily reproduce, if ever. He also mentioned salespeople, marketers and operations staff as examples. People in the field who have to make real-time decisions are inherently protected, in his view.<\/p>\n Gopal isn\u2019t the only executive who recognizes that AI requires human deployment to function. Tatyana Mamut, a former Salesforce and Amazon Web Services executive who now offers AI agent-monitoring purposes through her startup Wayfound.AI, told Fortune<\/em> that \u201cwe need to stop talking about AI like tools. <\/strong>It is not a tool, right? It\u2019s not like a hammer.\u201d Rather, she argued, it\u2019s more like a hammer \u201cthat thinks for itself, can design a house, can build a house better than most people who work in the construction industry can build a house.\u201d It still needs to be shown the construction plans, though.<\/p>\n Regarding business context, Mamut said she thinks \u201cvery few\u201d people really understand how to make this work with AI. \u201cYou need like real tools and mechanisms to capture that contextual learning.\u201d Companies with different brands, different systems and different processes all have different context that need to be captured by AI, she said, predicting that the smart SaaS companies will pivot into this territory. Instead of software-as-a-service, she said expert services will be delivered via agents with proper context capture.<\/p>\n Gopal was bearish about how much this context can be captured, estimating that 70% of the effort required to make AI useful relies entirely on unwritten business context that exists only in human heads. \u201cYou fundamentally cannot train a system\u201d on this fluid daily reality, Gopal explained, noting that real-life business constantly changes based on individual conversations and human interactions. While AI can automate tasks at the absolute top (coding) and the absolute bottom (physical robotics), the vast middle ground of knowledge work requires human context.<\/p>\n Ed Meyercord has been deploying machine learning processes for over a decade at Extreme Networks, a networking company that powers pro football and baseball stadiums and draws in over $1 billion in revenue. He told Fortune<\/em> in a recent interview that he sees dynamics similar to Gopal\u2019s on the operator\u2019s side of the table. His teams already use agents to design networks, spot failures before they happen, and even communicate with other agents in systems like ServiceNow, but he is adamant that there is always a human in the loop to review the work when the stakes are critical infrastructure.<\/p>\n \u201cA network is critical infrastructure, so we have to be right,\u201d Meyercord said. Extreme has built an agentic core into its platform, he added, \u201cbut effectively what that\u2019s allowed us to do is to be highly, highly accurate.\u201d Because accuracy is so paramount, he said, \u201cwe always want to have a human in the loop, show all the work that we\u2019re doing.\u201d<\/p>\n Like Gopal, Meyercord said he doesn\u2019t believe AI can simply \u201ctake our jobs\u201d outright; the role of the human is shifting from doing every task manually to orchestrating agents, gathering the right context, and deciding which problems to point the machines at. He said his job as CEO is, in many ways, to surround himself with specialists \u201ca lot smarter than I am\u201d while using AI as another hyper?fast teammate rather than a replacement. <\/p>\n On the other hand, anything that can be automated is already vulnerable to AI, Gopal said, nodding to the \u201cSaaSpocalypse\u201d in markets that is brutally punishing software-as-a-service stocks, insurance, wealth management and customer service. By the end of the year, he said, this will be even more visible in company valuations, as robots hoover up the work of anything that doesn\u2019t require business context. The exciting thing, he added, is what this means for work.<\/p>\n This symbiotic relationship between the human worker, who has a business context, and the AI, which can work faster and even smarter but lacks the input, will define the future of white-collar work that Shumer has warned about, according to Gopal. \u201cYou have to pick and choose the context and you have to keep capturing the context, right? And I think that\u2019s really what the shift is for the average white-collar worker is that they have to understand.\u201d<\/p>\n Gopal related an anecdote from his team, expressing frustration with a mediocre software engineer now that they have AI coding tools. \u201cWe\u2019re like, \u2018Man, like, it\u2019s just more expensive to talk to you than it is to do it myself. Like, to explain what I need built on the product takes more time than me just slamming it out of AI on the side.’\u201d The time it takes to talk to a mediocre engineer could be spent managing an AI output instead, he added. He likened this to every employee having a personal technical co-founder by their side at all times, potentially enabling them to produce 20 times as much work.<\/p>\n Meyercord agreed, saying that computer-science graduates don\u2019t need the same skillset as before, but they will \u201cneed a different skillset.\u201d He said he\u2019s already starting to see new skillsets develop, not necessarily all liberal arts graduates who are deeply trained in critical thinking, but more a sense of \u201cpeople that are helping us develop.\u201d He needs people who can delegate work to AI agents, talk with agents, vet their work, and oversee workflows. It sounds a lot like what Gopal predicted.<\/p>\n The job of the human has to evolve to feed the proper inputs to the AI agents that will power the business, Gopal predicted, and he put a name on it. \u201cOur job as humans and people is that we are now context gatherers instead of just workers.\u201d Most people have taken this for granted up until now, he said, because they didn\u2019t have AI agents to work alongside. \u201cWhat makes us good at our job, and what gives us promotions, and what makes us more impactful is actually that ability to gather context. That\u2019s what makes us good.\u201d<\/p>\n The only people who genuinely need to fear for their jobs, Gopal warned, are those who are \u201crefusing to grow\u201d and deny this new reality. If everyday workers fail to adopt these tools, they risk handing all economic power to a select few who do understand the technology, potentially creating a dystopian wealth gap. But for those willing to adapt, the future is incredibly bright. \u201cI don\u2019t think AI will just come and take our jobs,\u201d Gopal said. \u201cThat\u2019s not even kind of possible\u201d.<\/p>\n Meyercord said his business is still growing, and he argued that the AI job-loss narrative misses the forest for the trees. \u201cOn the one hand, you can do a lot more with less,\u201d he said, \u201cor you could do more with the same [number of workers]. Or you could do a lot more with a little more, right?\u201d If you hire the right context gatherers, Meyercord added, you can really grow your business. \u201cIt\u2019s like, how do you think about what you want to try to accomplish? We want to do a lot more.\u201d<\/p>\n<\/div>\n #CEO #billion #unicorn #peers #blind #spot #jobs<\/p>\n","protected":false},"excerpt":{"rendered":" Silicon Valley\u2019s artificial in… <\/p>\n","protected":false},"author":1,"featured_media":23887,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[579,13965,542,529,1827,8404,522,2491,11611,4603,7029],"_links":{"self":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/23886"}],"collection":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=23886"}],"version-history":[{"count":0,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/23886\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/media\/23887"}],"wp:attachment":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=23886"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=23886"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=23886"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}The real jobs disruption is coming from inside the valley<\/h2>\n
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<\/div>\n<\/figure>\nThe white-collar worker shift<\/h2>\n