Charts of the Week: AI App Slop, Shifting Venture Vintages, SaaS Resilience, and Startup Jurisdictions

Charts of the Week: AI App Slop, Shifting Venture Vintages, SaaS Resilience, and Startup Jurisdictions An analysis of recent data indicates that while AI code generation has flooded app stores with little corresponding demand, AI is reshaping the timeline for new unicorns, even as legacy startups navigate higher shutdown rates and regional cost disparities. New app releases on iOS, Android, and Chrome have doubled or quadrupled, but downloads remain stagnant and the share of apps reaching meaningful download or rating thresholds has plummeted. US app revenue grew by roughly 2% and time-spent rose 7% over the past eighteen months, with growth concentrated in Productivity (ChatGPT, Claude, Gemini, Grok) and Dev Tools (Replit), while paid consumer AI adoption sits near 3%. SVB data shows the median age for new venture unicorns dropped 37% since 2023 to just over four years, with the 2022 startup cohort doubling revenue from year three to four ($2.8M to $5.6M) at three times the rate of pre-GPT vintages. While peak-ZIRP era companies face rising shutdowns—with B2B SaaS accounting for over 25% of H1 closures—public software stocks have steadily rebounded since April as companies largely met or beat financial expectations. Massachusetts LLC startup fees run around $1,000 (five times the national median), coinciding with a net loss of approximately 17,500 businesses across nine quarters. Surging App Supply Meets Flat Consumer Demand AI code generation has led to a flood of new app publishing, variously doubling or quadrupling monthly app output across iOS, Android, and Chrome. However, downloads and ratings have remained largely flat, causing the proportion of apps achieving escape velocity—such as 10+ ratings or 100+ downloads—to drop sharply. SensorTower data similarly indicates a largely stagnant US app economy, with total revenue rising about 2% and usage time up 7% over the past year and a half. The primary pockets of usage expansion are centered in Productivity, led by major AI assistants like ChatGPT and Claude, and Developer Tools led by Replit, even as broader paid consumer AI adoption hovers around 3%. Evolving Venture Lifecycles and Unicorn Ages Data from SVB reveals that recent venture-backed unicorns are emerging faster than earlier cohorts, with median age falling to slightly over four years—a 37% decline since 2023. Startup revenue trajectories have also altered, as the 2022 cohort recorded a median revenue increase from $2.8 million to $5.6 million between years three and four, a jump roughly three times larger than historical pre-GPT baselines. Meanwhile, the macro environment and shifting venture capital strategies since Q1 2022 have caused median revenue growth among tracked tech companies to drop from 40%–70% down to 15%–30% in favor of near-breakeven margins. Startup Shutdowns Versus SaaS Public Market Performance Companies established during the zero-interest-rate peak are experiencing historically high failure rates, with SimpleClosure data showing that B2B SaaS represents more than a quarter of H1 shutdowns, while AI startups represent a shrinking share. Conversely, concerns over a broader public software collapse have not materialized fundamentally: software equities have trended upward since April, and first-half earnings demonstrate that the majority of software enterprises have met or exceeded analyst expectations despite a recent uptick in lowered guidance. High Formation Costs and Business Outflows in Massachusetts An examination of jurisdictional startup friction highlights Massachusetts, where LLC formation costs hover around $1,000, roughly five times the national median. Ranked 49th nationally for the cost of doing business, the state has recorded downward-trending net business formation since 2017, culminating in a net loss of roughly 17,500 businesses over a nine-quarter span based on zero-employee establishment metrics.

图表观察：AI引发应用激增却陷需求疲态，风投格局与SaaS分化凸显 数据显示，生成式AI工具导致应用供给激增，但用户下载与消费整体停滞，呈现明显的“应用泛滥”现象。与此同时，AI正在重塑风投生态，催生更年轻的独角兽并加速部分初创企业营收增长；而传统B2B SaaS面临关闭潮但上市公司基本面尚存韧性。此外，美国各州创业成本差异加剧了企业外流。 iOS、Android与Chrome平台的月均新应用数量翻倍至四倍，但整体下载量停滞，获得基础使用量的应用比例锐减。 SensorTower显示美国应用总营收近一年半仅增约2%，使用时长增7%，但生产力与开发工具等AI相关类别增长亮眼。 Consumer Edge数据显示第一季度付费消费者AI渗透率仅约3%，年轻人渗透率是年长者的约4倍。 SVB数据显示新晋独角兽中位年龄降至4年多（较2023年下降37%），2022年批次初创企业第3至4年的营收中位增幅达此前批次的约3倍。 SimpleClosure显示B2B SaaS占2026年上半年关闭企业的四分之一以上；而上市软件股自4月触底回升，上半年业绩普遍符合或超出预期。 应用供给暴增与需求疲软的断层 AI代码生成工具推动了新应用的爆发式增长，跨iOS、Android和Chrome平台的新增应用数量增长了两到四倍。然而，下载量与评分几乎停滞不前，跨越10次以上评分或100次以上下载门槛的应用比例急剧下滑。SensorTower数据同样表明，美国应用总营收和使用时长仅分别微增约2%和7%，尽管ChatGPT、Claude等驱动的生产力类以及Replit带动的开发工具类逆势高增，但整体呈现出“AI自身应用广受欢迎，而由AI编写的应用无人问津”的局面。此外，付费消费者AI采用率在第一季度仅为约3%，显示AI应用仍处于极早期。 风投周期重构：新生独角兽提速与SaaS关闭潮 在风投领域，AI正驱动价值向极少数企业集中，并催生出成长更快、更年轻的独角兽群体。硅谷银行（SVB）数据显示，风投支持的新独角兽中位年龄相比2023年缩短了37%至4年左右，2022年批次初创企业从第3年到第4年的中位营收增幅达此前批次的约3倍（从280万美元增至560万美元）。与此同时，高利率与策略转移促使老牌科技企业以增长换盈利，中位增速从40%–70%下滑至15%–30%。在清算端，零利率繁荣期成立的企业迎来倒闭高峰，SimpleClosure统计显示B2B SaaS占2026年上半年关闭企业的25%以上。 上市软件股的韧性与地区创业成本差异 尽管市场盛传软件行业的终结，但上市SaaS企业的基本面表现仍有支撑。软件股自4月以来波动回升，今年上半年多数软件公司业绩达到或超出市场预期，虽然提供疲软指引的公司比例有所增加，但全面的“SaaS大灾难”尚未在财务端兑现。在营商环境方面，美国各州创业成本出现严重极化：马萨诸塞州的有限责任公司（LLC）注册成本约为全美中位数的5倍，在全美商业营商成本排名中位居倒数第二；受此影响，该州净企业成立量自2017年起下滑，9个季度内净减少约17,500家企业。

[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 (and others) has observed that one effect of AI code gen tools has been the proliferation of code. More code has, among other things, also led to a pronounced spike in the number of apps. Everyone’s a vibecoder now, which means everyone’s an app publisher now, too. Of course, just because there are now more apps to choose from, doesn’t mean that those apps are particularly compelling, or that people are suddenly spending more time in the app store. Supply may increase, but demand may have a life of its own. As it happens, a recent paper sheds some light on the demand-side of the equation, and the results are pretty clear: the supply of apps has, indeed, surged . . . but, for the most part, no one is really using them: Across iOS, Android and Chrome, total new apps per month have variously doubled or quadrupled. On the other hand, the number of downloads (or ratings, in the case of iOS) has been pretty much stagnant. And, in case you’re wondering whether there’s been any share-shift, such that aggregate downloads are flat, but *within* that universe are still some winners—well, the researchers cover that one, as well. Alas, the share of apps with any indication of escape velocity—10+ ratings, 100+ downloads (for Android), and/or 10+ downloads for Chrome—has plummeted. In other words, yes, the data suggests that App-Slop is the story, for now. AI has led to a lot more apps, but they are not successful apps, in any meaningful sense. That’s not really surprising. Building successful apps (or software) has always been more than just generating the code. Plus, it’s still very early, and one would expect that all the amateur tinkering would produce supply ahead of demand. For what it’s worth, SensorTower’s data corroborates the story, for the most part. In the US, total app revenue has been basically flat since the beginning of last year, with a modest increase in total time-spent: SensorTower’s estimates indicate a \~2% increase in app revenues, and a 7% increase in usage time, over the past year and a half. Once again, more apps has not led to a boom in the app economy. Beneath the surface, however, it is nonetheless clear that AI is making a difference: The category with the fastest growing time-spent (and the second fastest growing revenue, after the relatively tiny Food & Drink category) is Productivity, driven by none other than ChatGPT, Claude, Gemini and Grok. Another standout category, albeit a tiny one, is Dev Tools, where Replit is by far the category leader for growth. AI apps are plainly very popular, but the apps made by AI, not so much. Consider this one small footnote in the broader question of “when will AI adoption show up in GDP?” (and the answer, in this case, is when the apps get much better). In the bigger scheme of things, paid consumer AI adoption remains quite low, even as it grows: Consumer Edge indicates that, as of Q1, paid consumer AI adoption was around \~3%, with younger folks out-adopting older folks by \~4x. So, yes, as cringey as it is to say, it’s nonetheless true: we’re still so early. On the subject of AI’s early ripple effects through the economy, one area where they are clearly visible is in the landscape for venture-backed companies. Not only is AI driving [historically large value creation](https://a16z.com/catching-the-venture-bus/) in a historically small share of companies, there’s some data to suggest that AI is minting an entirely new breed of unicorn—one that is younger, and faster-growing than before. According to data from SVB, while the entire universe of venture-backed $1B+ companies has gotten steadily older, the recent vintage has gotten progressively younger: The “full herd” has gotten \~7% older, but the median age for new unicorns is now just a shade over 4 years, reflecting a 37% decline since 2023. It’s not just that unicorns are being minted earlier in their lifecycle than before. Across *all* the companies in SVB’s data, median [revenue growth for the post-GPT generation](https://www.a16z.news/p/charts-of-the-week-cycles-different?utm_source=publication-search) is operating on a noticeably different curve: For the 2022 cohort, the revenue jump from year 3 to 4 at the *median* is \~3x larger than earlier cohorts. Put another way, instead of going from $2M to $3M (as per the pre-GPT cohorts), the ‘22 batch went from $2.8M all the way to $5.6M. Is that AI? It’s possible, but we’ll have to wait a bit to see if the ‘23 and ‘24 batches follow a similar trend. Truthfully, the reality is a bit more complicated. AI has changed the venture landscape, but one feature of that shift has been greater allocations to non-software businesses, which one would expect to have very different growth curves. By contrast, one could easily imagine that the ‘22 batch is full of fast-growing “AI wrappers” that may or may not be able to keep it up. Growth-curves aside, it is undoubtedly the case that AI has changed the game for pre-AI techcos. For one thing, the combination of AI-driven shift in VC strategy plus higher interest rates has led to a noticeable change in operating priorities: beginning in Q1’22, techcos in all verticals tracked by SVB, began trading growth for profitability: Growth went from 40%-70% at the median all the way down to 15%-30%, while margins did the opposite, running from deeply unprofitable to nearly breakeven. By contrast, the companies getting funded most recently have growth/profitability profiles not unlike the ‘22 standard. Now, to be fair, ‘22 was something of a pandemic-reopening-ZIRP high watermark for growth, and then later, when interest rates went up, *everyone* battened down the hatches—public companies traded growth for profitability, too. Plus, growth does appear to have reaccelerated recently. That all being said, companies minted during the previous cycle are confronting a decidedly new-normal. An historic number of businesses were founded, and now an historic number of businesses are shutting down: Unsurprisingly, the largest share of shutdowns comes from the peak-ZIRP vintages. Likewise, [SaaSpocalypse](https://www.a16z.news/p/charts-of-the-week-saaspocalypse) appears to have hit startup land, as well: According to data from SimpleClosure, while AI startups are an increasingly small share of shutdowns, B2B SaaS represents more than a quarter of H1 ‘26 shutdowns. Again, the denominator was high—B2B SaaS was a very popular category—and, beyond that, it’s hard to say how much of this is AI-driven disruption vs. [a shift in thematic winds](https://www.a16z.news/i/212038345/winds-of-thematic-change), but either way, the new cycle is not like the old cycle, and that’s not fun for everyone. Speaking of SaaSpocalypse, here’s a fun one. Remember that Citrini doompost that foretold the end of software (and pretty much everything)? Well, for now at least, Citrini seems to have ticked the bottom of the software selloff: Software performance for all companies big and small has climbed unsteadily upwards since April . . . so Citrini didn’t quite tick the bottom, but came awfully close (at least for now). Charts has gone over [software’s selective selloff](https://www.a16z.news/p/charts-of-the-week-softwares-selective) a few times, so no need to rehash it all here, but suffice it to say that fundamental performance for SaaS has more or less held up. That doesn’t mean it will continue to hold up, of course, but a rough summary of the headlines shows that software companies have generally beat or met expectations for the first half of the year: Notably, the share of software companies with disappointing guidance increased in the most recent quarter, but meet or beat was still the predominant story. Take this data with a grain of salt because it’s not comprehensive, and it says nothing about actual performance—it’s of course easy to exceed low expectations, and similarly easy to disappoint high expectations, but in both cases, actual performance can be variously strong or weak. In all events, whatever SaaSpocalypse may be in the offing, it hasn’t arrived yet. Apropos of nothing (except a [passing interest in jurisdictional competition](https://www.a16z.news/p/charts-of-the-week-dexit-real-or?utm_source=publication-search) for startups), it turns out that there is a very not-normal distribution of startup costs, by state: LLC costs in Massachusetts run \~$1,000, or \~5x the nationwide median. To be fair, $1,000 is a rounding error in the big scheme of business costs, but these things do add up, and may be symptomatic of a broader policy posture. [MA was ranked 49th in the nation for the cost of doing business](https://www.cnbc.com/2026/07/09/americas-top-states-for-business-full-rankings.html), and despite having some of the best research institutions in the world (and some of the best talent), Massachusetts has been hemorrhaging businesses over the last few years: Net business formation has been trending downwards since 2017, and has been sharply negative since the pandemic reopening, leading to the worst ratio in the country. Approximately ***17,500 MA businesses were lost*** (on net) over a 9-quarter period. To be fair, the data lags (because a business has to report four quarters of zero employees to be considered a “death”), so it’s possible things have improved . . . but for now, it seems that Massachusetts is a pretty unfriendly place to open up shop. *This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. 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