Charts of the Week: Tech Hiring Priortizes Experience, Streaming Habits Shift, Cyber Threats Accelerate, and Data Centers Boost Construction

Charts of the Week: Tech Hiring Priortizes Experience, Streaming Habits Shift, Cyber Threats Accelerate, and Data Centers Boost Construction A compilation of market data highlights emerging economic and technological shifts: tech hiring is favoring experience over defined skill sets, short-form video is squeezing Netflix's engagement, cyber vulnerability exploitation speeds are reaching extreme levels, and AI data center construction is significantly bolstering blue-collar employment. Revelio Labs data shows tech job postings since January 2025 require 5% to 10% more years of experience alongside a drop in the number of preferred skills, led by data, systems, and Java roles. While aggregate US social media time continues to edge up primarily via 17-to-25-year-olds, social media's share of mobile screentime fell roughly 3 percentage points since April, pressured by short-form video on YouTube. Netflix weekly active users and viewing time in the US have declined roughly 15% and 30% over the past three years, with Apptopia noting a 20% drop in YouTube users who also watch Netflix. Epoch AI and ZeroDayClock report a vertical climb in high-severity vulnerabilities, an 87% zero-day rate, and an expected median time to exploit reaching just one minute by next year. Bureau of Labor Statistics data shows data center construction spending rose by about $25 billion in six months, with Goldman Sachs attributing approximately 300,000 construction jobs to the AI buildout since 2022. Tech Hiring Shift Toward Experience Data from Revelio Labs indicates that since January 2025, tech postings reflect an approximate 5% to 10% increase in preferred years of experience alongside a matching decline in specific preferred skills. This premium on experience dominates in data, systems work, and Java, suggesting that early-stage AI adoption requires problem-solving capacity over defined existing skill sets until standardized practices mature. Attention Economy: YouTube and Netflix Trends Although aggregate social media time is slightly up among younger cohorts aged 17 to 25, social media's mobile screentime share fell roughly 3 percentage points since April, likely absorbed by short-form video like YouTube. In turn, Netflix has seen weekly users drop around 15% and viewing time fall 30% over three years, with overlap data showing YouTube users increasingly dropping Netflix despite Netflix's industry-leading customer lifetime value of nearly $1,500. Escalating Cybersecurity Risks and Market Response Cyber threat metrics show a surge in reported critical and high-severity vulnerabilities alongside a quadrupled Zero-Day Rate since 2020. The current rate sits just below 87% with a one-day median time to exploit, projected to drop to one minute by next year. In public markets, cybersecurity equities have outperformed broader software stocks within the IGV index, trading at elevated revenue multiples as defensive spending intensifies. AI Infrastructure Fuels Construction Growth Data center construction spending expanded by approximately $25 billion over six months, matching the prior two years of total growth according to the Bureau of Labor Statistics. While higher interest rates subdued broader construction activity, Goldman Sachs estimates roughly 300,000 construction and specialty trade roles added since 2022 stem directly from the AI infrastructure buildout.

a16z图表周报：招聘重经验轻技能、流媒体注意力转移与AI基建繁荣 本期a16z图表周报探讨了多项宏观与科技趋势：科技岗位对年资经验的偏好反超具体技能，社交媒体及YouTube正在挤压Netflix的屏幕时间，AI正在急剧缩短网络安全漏洞利用周期，而AI数据中心建设则逆势拉动了美国建筑业就业。 自2025年1月起，科技招聘对年资经验的要求上升5%-10%，对技能数量的要求则相应下降，数据和系统岗位溢价最高。 美国社交媒体时长受17-25岁人群驱动微增，但移动端时长占比自4月起下降约3个百分点；YouTube等短视频正冲击Netflix，后者周活与观看时长3年来分别下滑约15%和30%。 网络安全漏洞披露量与利用速度激增，零日漏洞利用率接近87%，漏洞中位利用时间预计明年将缩短至1分钟。 BLS数据显示数据中心建设支出半年内激增约250亿美元，高盛估计自2022年以来AI基建已带动约30万建筑及专业工种就业。 科技招聘转向：重经验轻技能 Revelio Labs数据显示，自2025年1月以来，科技岗位招聘对偏好工作年限的要求提升了约5%至10%，对技能数量的要求则同步下降。由于AI技术不断迭代，既有技能适用度降低而新技能尚未成型，具备探索能力的老手更加吃香。数据和系统类工作在经验溢价方面领跑。 注意力流向：YouTube与短视频挤压Netflix Apptopia数据显示，美国社交媒体整体时长微升，主要由17-25岁年轻群体驱动，而36岁以上人群自2025年10月起使用时长已趋缓。同时，社交媒体占移动端屏幕时间的份额自4月起下降约3个百分点，主要被YouTube等短视频分流。受此影响，同时使用Netflix的YouTube用户自年初以来减少约20%，Netflix过去3年多的周活跃用户和观看时长分别下滑约15%和30%。 网络安全威胁：漏洞利用进入“分钟级”时代 Epoch AI和ZeroDayClock数据显示，大型企业报告的高危漏洞大幅增加，零日漏洞利用率已接近87%，较2020年增长约4倍。漏洞被利用的中位时间仅为1天，并预计在明年缩减至1分钟。当前漏洞生存曲线在1.5个月时即降至0%，推动网络安全类股票在IGV成分股中持续领跑。 AI硬件建设：蓝领就业的逆周期支柱 美国劳工统计局数据显示，数据中心建设支出在过去半年内增加了约250亿美元，增幅相当于此前两年的总和。高盛估计，AI基建自2022年以来已为建筑和专业工种带来了约30万个就业岗位，其中近7.5万个来自过去一年，显著扭转了高利率环境下传统建筑业岗位减少的颓势。

[America](https://www.a16z.news/t/america) | [Tech](https://www.a16z.news/t/technology) | [Opinion](https://www.a16z.news/t/opinion) | [Culture](https://www.a16z.news/t/culture) | [Charts](https://www.a16z.news/t/charts) Charts has already observed that one of the challenges for prospective entry-level hires (other than the fact that entry-level hires have always been a relatively small share of tech hiring) is that existing tech workers appear to be getting older. Why that’s the case is some combination of aging-in-place, plus remote work unlocking a broader pool of talent, plus perhaps some premium for more experienced workers—and while AI may have something to do with it, as well, the evidence for that is pretty weak. On the experience point, there’s some recent data from Revelio Labs that suggests experience is, indeed, becoming a higher priority for tech hiring: Since January 2025, tech job postings have seen a marked rise in preferred years of experience, with a concomitant drop in preferred number of skills. The change is small—\~5-10% in both cases–but noticeable, and it’s consistent with the notion that tech is looking for more experienced workers, rather than workers with any particular set of skills, let alone a broad range of skills. *That* could very well be an AI-driven shift: grappling with a new technology means that extant “skills” are less applicable, and the new set of skills is still a bit of a whitespace. When you’re operating on a new frontier, you don’t yet know what you’ll need, other than the need to be able to figure it out—and that’s where experience goes a long way. If you look at the types of jobs that require the largest premia to experience, it does seem like AI is the likely driver: It’s data and systems work (and Java) that dominate the leaderboard for the recent hiring premium to experience. AI has created new urgency around data wrangling, but the shape of wrangled data (and the process of wrangling) has changed dramatically, with optimal solutions still very much a moving target. If you don’t know what needs to be done, then the skillset hasn’t been defined yet, and someone who can figure it out as they go is the better choice. Eventually, though, as implementation matures, one would expect new skills to be defined, and it’s likely the skills/experience mix will shift again. A funny thing about social media consumption is that aggregate time spent in the US is still rising (albeit barely), but not for everyone: According to Apptopia, aggregate time spent on social media apps has risen (after a small drop), but it’s really the 17-25 yos doing all of the work—the folks 36+ appear to have tapered off their social media time since October ‘25. But that’s not actually the funny thing. The funny thing is that while social media usage is rising, social media’s share of screentime has actually dropped pretty substantially of late: Since April of this year, social media’s share of mobile has dropped \~3pp. OK, perhaps “substantially” is a bit of a stretch, but after years of steady growth (including double-digit growth as of last year), the dropoff is meaningful. So people are spending more time on social media, but even *more* screen time on other things. What other things? Apps perhaps. AI could also be drawing more attention. But a more likely culprit for social media’s diminished share of mobile is none other than short-form video, particularly via YouTube. OK, great, so more social media, more YouTube, and more screentime overall–a win-win-win for staying glued to our phones. That’s true so far as it goes, but there does, in fact, appear to be at least one victim of YouTube’s assault on our attention-spans, and that’s Netflix: Again, according to Apptopia, the number of YouTube users who also use Netflix has declined \~20% since the beginning of the year, while the number of Netflix users who also use YouTube has remained pretty steady. YouTube viewers seem more inclined to live without Netflix than the other way around. In general, Netflix’s active users and viewing time in the US have both been in mostly serial decline for the past 3+ years: Weekly users and time spent for Netflix have dropped \~15% and 30% respectively. Why *that’s* the case is anyone’s guess. Among other things, it could be the rise of short-form video, more streaming competition, or streamflation more generally. As a possibly relevant aside, Netflix stands out for having the highest customer LTV by far, at least according to this estimate from Owl & Co. A Netflix premium customer has an LTV of nearly $1,500 per customer, which is nearly 2x the next best offering. LTV reflects a combination of higher subscription prices and strong retention—good for Netflix—but one could see why customers might begin to balk at the price. One could also see why Netflix is branching out into live sporting events and clips and shorts of its own. Bigger picture, though, it’s fair to wonder if Netflix is having its Blockbuster moment, roughly two decades after Netflix gave Blockbuster its Blockbuster moment. It’s too soon to tell, of course, but in a different timeline, where AI was not such a big deal, this would be a much bigger deal. Have you heard of the [‘Hugging Face Incident’](https://openai.com/index/hugging-face-incident-and-the-road-ahead/)? I mean, you probably have, but if you haven’t, you probably shouldn’t, and then you’ll sleep easier at night. (Old heads might be reminded of the [Noodle Incident](https://calvinandhobbes.fandom.com/wiki/Noodle_Incident), but sadly, these are not the same.) Anyways, HFI aside, there’s plenty of recent data to suggest that the threat landscape for cyber events has changed dramatically. Consider this nightmare fuel from Epoch AI: The number of reported critical and high severity vulnerabilities from major firms has gone vertical this year, since the beginning of the spring. Whether there are actually more vulnerabilities, or whether there’s some reporting or definition change, it’s hard to say just by looking at the chart, but it’s likely that at least *some* (and perhaps a lot) of this parabolic growth is attributable to a major substantive change in either how vulnerabilities are discovered and/or what is still considered secure. Here’s another bit of nightmare fuel for the cyber-minded: According to the ZeroDayClock, the Zero-Day Rate (i.e. the percent of vulnerabilities exploited on the day of disclosure (or before)) has basically quadrupled since 2020—including a \~60% increase from last year alone. The Zero-Day Rate is now just under 87%, with a median time to exploit at just one day . . . but projected to reach 1 minute sometime next year. To repeat, the ZeroDay estimate is that *it will take only a minute between discovery and exploitation of a vulnerability* (at the median) by sometime next year. Even now, the “Exploit Survival Curve” falls to 0% at just 1.5 months: Back in 2022, a full 50% of exploits were still there for the taking after 1.5 months (and at 3 months, too), but now, if you haven’t plugged all the holes, by then, someone else will have already found them. Clearly AI has changed the game, not only for identifying vulnerabilities, but also exploiting them. The good news is that AI will also change the game for the defense. Either way, the urgency for cyber has intensified, and as Charts has observed before, investors are way out in front of this one: Of the $IGV constituent stocks, Cyber has massively outperformed the field, and forward revenue multiples are consistently higher, as well. Whether and to what extent the incumbents successfully step into the breach, or whether some new cyber platforms emerge to face the challenge, remains to be seen, but there are surely going to be a whole bunch of new sheriffs in town (or else). One final aside on the [economic driver that is the AI buildout](https://www.a16z.news/i/212038345/data-centers-are-a-blue-collar-bonanza). BLS released its latest estimate of data center construction spending, and while there was no reason to think otherwise, the pace is blistering: Data center construction spending jumped by \~$25B in just half a year, which is roughly the same amount it jumped over the past two years. But, more to the point, alongside the jump in construction spending is a jump in construction job openings, which have otherwise been in steady decline since interest rates went up, and most other construction slowed substantially. Goldman estimates that \~300,000 construction and specialty trade workers have been added to the workforce since 2022 that are attributable to the AI buildout, with nearly 75,000 of those coming in the past year alone: Again, while the overall trend for hard hat workers has been directionally negative since rates went up, that trend has reversed to the upside since the middle of last year. Like ‘em or not, data centers are major jobmakers, bringing [a pretty wage premium, as well](https://www.a16z.news/i/212038345/data-centers-are-a-blue-collar-bonanza)—and it’s fair to say that *without* data centers, the employment picture, especially for blue-collar types, would be substantially worse. *This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. Furthermore, this content is not investment advice, nor is it intended for use by any investors or prospective investors in any a16z funds. 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