{"version":"1.0","type":"agent_native_article","locale":"en","slug":"herd-mentality-venture-capital-hidden-costs-mpv7wpky","title":"The Herd Mentality That Finances the Future and Its Hidden Costs","primary_category":"transformation","author":{"name":"Diego Salazar","slug":"diego-salazar"},"published_at":"2026-06-01T12:03:32.689Z","total_votes":82,"comment_count":0,"has_map":true,"urls":{"human":"https://sustainabl.net/en/articulo/herd-mentality-venture-capital-hidden-costs-mpv7wpky","agent":"https://sustainabl.net/agent-native/en/articulo/herd-mentality-venture-capital-hidden-costs-mpv7wpky"},"summary":{"one_line":"Three quarters of last year's venture capital went to just five companies, revealing a structural concentration that distorts innovation funding, inflates AI valuations, and leaves most of the real economy underserved.","core_question":"How much of the capital flowing into AI and high-profile tech today is buying real value versus buying a position in a narrative that cannot yet sustain itself on revenues alone?","main_thesis":"Global venture capital is experiencing unprecedented concentration driven by herd mentality and narrative-chasing, which inflates valuations without external revenue validation, crowds out non-benchmark opportunities, and creates a correction that is not a risk scenario but a timing question."},"content_markdown":"## The herd mentality financing the future and its hidden costs\n\nThree quarters of the venture capital raised in the last year went to five companies. Not five sectors. Not five categories. Five companies. That figure, stated without euphemisms by Niko Bonatsos of Verdict Capital at a recent TechCrunch panel in Athens, summarizes with more precision than any market report what is happening in global venture capital: an unprecedented concentration that coexists, paradoxically, with a discourse of distributed innovation and open opportunity.\n\nThe event brought together Bonatsos alongside Andreas Stavropoulos of Threshold Ventures and Ben Blume of Atomico to discuss the state of venture capital, the imminent wave of major IPOs led by SpaceX, and where they see real space for opportunity. What they left behind was less a map of the future and more an honest X-ray of a market that mixes genuine signals with distortions that no one quite wants to name.\n\nThe question that organizes all of this is not whether artificial intelligence is going to change the economy. That debate is already closed. The operative question is how much of the capital flowing into that sector today is buying real value and how much is buying a position in a narrative that still cannot sustain itself on revenues alone.\n\n## When liquidity creates the illusion of a market\n\nSpaceX is approaching an IPO with a reported valuation of $1.75 trillion. Stavropoulos compares it to Google's IPO in 2004, which reactivated markets that had lost confidence in technology following the dot-com cycle. The argument is solid in its structure: large exits generate returns that flow back into the ecosystem as new capital, and that capital opens doors for the next generation of founders.\n\nBlume adds that SpaceX is such a singular company that its public access could capture the imagination and investment of segments that historically did not participate in private technology. Space as an investment domain open to the general market is, effectively, a category shift.\n\nBut there is a tension that none of the three fully resolves. Blume himself names it: a portion of the capital that goes to SpaceX consists of funds that would have gone to the next twenty or thirty software businesses. That is not neutral. In a market where early access to the right capital can separate a company that survives from one that does not, the reorientation of those allocations has real consequences for what gets built and what does not.\n\nThe dominant narrative says that liquidity generates more liquidity, that the cycle is virtuous, and that the returns from a major exit fertilize the next cycle. That is historically true as a trend, but it conceals a lag. Between the IPO of a company valued at $1.75 trillion and the moment that capital returns to a seed fund that finances a 23-year-old founder in Buenos Aires or Mexico City, there are years. And in those years, the distribution of capital is not homogeneous: it goes to the same managers, in the same markets, with the same selection biases.\n\nThe most uncomfortable question about SpaceX is not whether it will affect market liquidity in the short term. It is whether an exit of that size will concentrate institutional attention even further on benchmark assets and reduce the relative appetite for what is difficult to categorize — which is exactly where Bonatsos says the opportunities with low valuations are to be found.\n\n## The price of capital when everyone wants the same thing\n\nBonatsos describes Verdict Capital's strategy with a word that rarely appears in the language of venture capital: \"freaks.\" Founders who advance in a single day what the average person would accomplish in a week, who build in markets that do not yet have a name, and whose valuations are low precisely because large asset managers cannot give their teams the mandate to look for companies in categories that do not yet exist.\n\nIt is a strategy of first-money-in on unmapped territory. What makes it viable is not only the investment thesis, but the structure of competition: funds of ten or fifteen billion dollars cannot operate efficiently in that space. Blume, who manages a five-hundred-million-dollar fund, already feels the pressure of competing with those vehicles in artificial intelligence rounds, where the incremental value of a dollar to a small fund versus a large one is radically different. That distorts the size of rounds and makes it almost impossible to compare offers on equivalent terms.\n\nWhat is happening at the application layer of artificial intelligence is an accelerated version of what occurred in mobile between 2009 and 2013: too much capital chasing too many similar theses, with a very small subset of companies capturing the majority of returns. Stavropoulos anticipates this with more honesty than evasion: there is going to be a correction. The promise and the optimism are significantly ahead of the capacity to show results in the short and medium term. That does not cancel the long-term argument, but it does imply that many of the current valuations are not anchored in sustainable revenues but in expectations that still have no delivery date.\n\nWhat creates noise from a commercial analysis perspective is the combination of three factors that the panel describes with varying degrees of discomfort: unprecedented capital concentration, selection biases based on age and profile as substitutes for business signals, and revenue metrics defined in increasingly creative ways.\n\nBonatsos says it plainly: when there is a lot of money chasing specific themes, some people develop a short-term mentality that prioritizes appearance over substance. He receives emails from companies in his portfolio with annualized revenue figures that turn out to be 365 times what they billed on a good day following a campaign. The solution he proposes is to use minimum quarterly baselines. But the underlying problem is not the calculation method: it is that there is a market willing to finance those figures without asking the questions that should be asked.\n\n## Where capital does not reach and why that matters\n\nThe most interesting space in the analysis is not in what everyone is financing, but in what no one is looking at. Bonatsos points out that venture capital has practically abandoned the digital consumer: where previously half the partners at a fund worked in consumer internet, today barely half a partner is dedicated to that area. The argument is that ChatGPT, the most widely adopted consumer product of recent years, came from an artificial intelligence company. The consumer did not disappear: what disappeared was capital's interest.\n\nThat creates an asymmetry. If there are five investors available to finance a founder in consumer versus fifty to finance one in language model infrastructure, the price competition in the first case is lower. Entry valuations are more reasonable. The market is less efficient. For a fund with discipline in entry pricing, that is a structural advantage, not a concession.\n\nBlume sees the greatest opportunity at the intersection of artificial intelligence and the physical world. Not the humanoid robot performing pirouettes in a demonstration video, but the penetration of automation into the sectors that still move the largest share of global gross output: manufacturing, logistics, construction, agriculture. The proportion of economic value that still depends on non-digitized physical processes is enormous. The software infrastructure for those sectors is at an early stage compared to what was built over the last twenty years for purely digital processes.\n\nThat thesis has an advantage over those competing at the core of the language model market: it does not require winning against OpenAI or Anthropic. It requires understanding, in sufficient detail, the physical processes of a specific industry in order to make automation work under real conditions, with real variability, with real workers. That friction is also the barrier to entry. What makes that category difficult to attack is the same thing that makes it difficult to replicate once it works.\n\n## The market that finances itself needs an external buyer\n\nThe commercial architecture of the artificial intelligence boom has a structural problem that the panel orbits without fully landing on. A disproportionate fraction of the capital entering the sector comes from funds that also hold positions in the infrastructure on which those startups run. Spending on computing goes to the same providers whose venture capital funds or corporate investment arms are financing the rounds. That is not necessarily fraudulent, but it creates a circularity that inflates activity metrics without there being a net external buyer validating the value.\n\nA business sustains itself when someone who has no financial incentives in the chain decides to pay for the product with money they could have spent on something else. That is what Stavropoulos calls \"the capacity to show results.\" And that is precisely what is lagging behind the optimism of the valuations.\n\nThe cycle of major IPOs can inject liquidity back into the market. But the question of whether the companies being built with that capital have external buyers with a genuine willingness to pay prices that justify entry valuations still lacks a clear answer. Until that answer arrives in the form of verifiable revenues with real margins, the correction that Stavropoulos anticipates is not a possible scenario. It is an adjustment pending only in timing.","article_map":{"title":"The Herd Mentality That Finances the Future and Its Hidden Costs","entities":[{"name":"Niko Bonatsos","type":"person","role_in_article":"General Partner at Verdict Capital; primary source for concentration data, consumer market abandonment, and revenue metric manipulation"},{"name":"Verdict Capital","type":"company","role_in_article":"VC fund pursuing first-money-in strategy in uncategorized markets with low valuations"},{"name":"Andreas Stavropoulos","type":"person","role_in_article":"Partner at Threshold Ventures; source for SpaceX IPO comparison and anticipated market correction"},{"name":"Threshold Ventures","type":"company","role_in_article":"VC fund represented at TechCrunch Athens panel"},{"name":"Ben Blume","type":"person","role_in_article":"Partner at Atomico; source for physical-world AI thesis and fund-size competition pressure"},{"name":"Atomico","type":"company","role_in_article":"$500M VC fund competing in AI rounds against much larger vehicles"},{"name":"SpaceX","type":"company","role_in_article":"Central case study for large IPO liquidity effects and capital concentration risk"},{"name":"TechCrunch","type":"institution","role_in_article":"Organizer of Athens panel where the data and theses were presented"},{"name":"OpenAI","type":"company","role_in_article":"Referenced as benchmark competitor that physical-world AI startups do not need to beat"},{"name":"Anthropic","type":"company","role_in_article":"Referenced alongside OpenAI as dominant AI infrastructure player"},{"name":"Venture Capital","type":"market","role_in_article":"Primary subject of analysis — its concentration, distortions, and structural gaps"},{"name":"Artificial Intelligence","type":"technology","role_in_article":"Dominant investment theme driving capital concentration and valuation inflation"}],"tradeoffs":["Liquidity from large IPOs vs. multi-year lag before capital reaches early-stage founders in non-core markets","Narrative-driven valuation growth vs. revenue-anchored sustainable business value","Capital concentration in proven themes vs. first-mover advantage in uncategorized markets","Fund size and institutional mandate vs. ability to invest efficiently in early, unmapped categories","Short-term appearance of growth metrics vs. substance of verifiable revenues with real margins"],"key_claims":[{"claim":"75% of venture capital raised in the last year went to just five companies.","confidence":"high","support_type":"reported_fact"},{"claim":"SpaceX is approaching an IPO at a reported valuation of $1.75 trillion.","confidence":"high","support_type":"reported_fact"},{"claim":"Capital redirected to SpaceX comes partly at the expense of 20-30 software businesses that would otherwise have been funded.","confidence":"medium","support_type":"inference"},{"claim":"The returns from a major IPO take years to recycle back to seed-stage founders in emerging markets.","confidence":"medium","support_type":"inference"},{"claim":"Consumer internet has gone from half a fund's partners to barely half a partner dedicated to the area.","confidence":"high","support_type":"reported_fact"},{"claim":"A correction in AI valuations is not a possible scenario but a pending timing adjustment.","confidence":"interpretive","support_type":"editorial_judgment"},{"claim":"Some portfolio companies report annualized revenues that are 365x a single good billing day.","confidence":"high","support_type":"reported_fact"},{"claim":"The AI application layer is following the same pattern as mobile investment between 2009 and 2013.","confidence":"interpretive","support_type":"editorial_judgment"}],"main_thesis":"Global venture capital is experiencing unprecedented concentration driven by herd mentality and narrative-chasing, which inflates valuations without external revenue validation, crowds out non-benchmark opportunities, and creates a correction that is not a risk scenario but a timing question.","core_question":"How much of the capital flowing into AI and high-profile tech today is buying real value versus buying a position in a narrative that cannot yet sustain itself on revenues alone?","core_tensions":["Distributed innovation narrative vs. extreme capital concentration in practice","Optimism about AI's long-term value vs. valuations not anchored in current or near-term revenues","Large fund mandates requiring categorized markets vs. best opportunities existing in uncategorized ones","SpaceX IPO as ecosystem catalyst vs. SpaceX IPO as further concentration of institutional attention","Virtuous liquidity cycle narrative vs. structural lag and geographic bias in how that liquidity actually redistributes"],"open_questions":["When and how severely will the AI valuation correction materialize, and which fund vintages will be most exposed?","Will the SpaceX IPO concentrate institutional attention further on benchmark assets or genuinely open new investor segments?","How long is the actual lag between a $1.75T exit and meaningful capital reaching seed-stage founders in Latin America or other emerging markets?","Is the circular capital structure in AI (investors funding startups that spend on investor-owned infrastructure) a systemic risk or a self-correcting inefficiency?","Which physical-world AI sectors will reach the infrastructure maturity needed to attract mainstream VC attention, and on what timeline?","Can consumer internet re-attract VC attention, or has the category permanently ceded to AI-native consumer products?"],"training_value":{"recommended_for":["Venture capital analysts evaluating AI portfolio concentration risk","Startup founders seeking to understand capital availability dynamics in their sector","Corporate strategy teams assessing whether AI investment narratives align with verifiable business outcomes","Business agents trained to evaluate investment memos, funding rounds, or market entry decisions","Economists and policy analysts studying innovation funding distribution and its effects on economic geography"],"when_this_article_is_useful":["When evaluating whether an AI startup's valuation is anchored in real revenues or narrative momentum","When deciding whether to compete in a crowded investment theme or seek uncategorized, lower-competition markets","When assessing the credibility of annualized revenue figures in early-stage company pitches","When analyzing the downstream effects of a major IPO on early-stage capital availability","When building investment theses around physical-world automation or consumer internet as contrarian plays"],"what_a_business_agent_can_learn":["How to identify herd mentality signals in investment markets: excess capital, similar theses, creative revenue metrics","Why fund size creates structural market inefficiencies that smaller, disciplined investors can exploit","How to distinguish between liquidity-driven valuation and revenue-anchored valuation when evaluating investment targets","Why circular capital structures (investors funding startups spending on investor-owned infrastructure) inflate activity metrics without external validation","How to use sector attention asymmetry (consumer vs. AI infrastructure) as a signal for entry valuation discipline","Why the lag between large exits and downstream capital redistribution matters for founders outside core VC geographies"]},"argument_outline":[{"label":"1. The concentration fact","point":"75% of VC raised in the last year went to five companies, not five sectors. This is not a distribution story — it is a winner-take-almost-all allocation.","why_it_matters":"It reframes the entire 'distributed innovation' narrative as largely rhetorical. Capital is not flowing broadly; it is pooling at the top."},{"label":"2. The SpaceX IPO as liquidity signal and distortion","point":"SpaceX's ~$1.75T IPO is compared to Google's 2004 IPO as a market reactivation event, but it also redirects capital that would have funded 20-30 software businesses.","why_it_matters":"Large exits generate downstream capital, but with a multi-year lag and the same geographic and managerial selection biases. The virtuous cycle is real but slow and uneven."},{"label":"3. Fund size creates structural market inefficiency","point":"Funds of $10-15B cannot efficiently invest in uncategorized, early-stage markets. This leaves low-valuation, high-potential opportunities structurally underpriced.","why_it_matters":"For disciplined smaller funds, this is a competitive advantage. For the ecosystem, it means capital misallocation at scale."},{"label":"4. AI application layer mirrors mobile 2009-2013","point":"Too much capital is chasing too many similar AI theses. A small subset will capture most returns. A correction is anticipated by the panelists themselves.","why_it_matters":"Current valuations are not anchored in sustainable revenues but in expectations with no delivery date. This is a known pattern with known outcomes."},{"label":"5. Revenue metrics are being gamed","point":"Bonatsos reports receiving emails with annualized revenue figures that are 365x a single good day. The market is financing these figures without asking the right questions.","why_it_matters":"When capital is abundant and thematic, due diligence degrades. This is a systemic signal, not an isolated bad actor problem."},{"label":"6. Consumer and physical-world sectors are structurally underfinanced","point":"Consumer internet has gone from half a fund's partners to barely half a partner. Physical-world AI (manufacturing, logistics, agriculture) is early-stage relative to its economic weight.","why_it_matters":"Asymmetric attention creates asymmetric entry valuations. Less competition means more rational pricing and higher potential returns for disciplined investors."}],"one_line_summary":"Three quarters of last year's venture capital went to just five companies, revealing a structural concentration that distorts innovation funding, inflates AI valuations, and leaves most of the real economy underserved.","related_articles":[{"reason":"Directly complementary: analyzes how AI investment misallocation leads to value destruction, mirroring the article's thesis that capital concentration and narrative-chasing produce inflated valuations without real returns.","article_id":13179},{"reason":"Examines the blind spots in corporate AI adoption reporting — relevant to the article's point that revenue metrics are being gamed and that optimism is structurally ahead of verifiable results.","article_id":13274},{"reason":"Illustrates the inverse case: a company with real revenues trading at a discount due to market misreading, which contrasts with the article's analysis of companies with weak revenues trading at premiums due to narrative.","article_id":13301}],"business_patterns":["Herd mentality in VC mirrors mobile 2009-2013: excess capital, similar theses, small subset capturing most returns","Large exits create virtuous capital cycles but with geographic and managerial selection biases that reproduce existing inequalities","Market inefficiency as competitive advantage: sectors with fewer investors have more rational entry pricing","Circular capital structures in boom cycles: investors financing startups that spend on infrastructure the same investors own","Revenue metric inflation as a lagging indicator of capital excess: creative accounting follows abundant thematic capital"],"business_decisions":["Whether to invest in benchmark AI assets or seek uncategorized, low-valuation opportunities with less competition","Whether to use annualized revenue projections or minimum quarterly baselines as funding criteria","Whether to allocate to consumer internet given structural underinvestment and lower entry valuations","Whether to pursue physical-world AI (manufacturing, logistics, agriculture) as an alternative to core LLM infrastructure plays","Whether large institutional funds should participate in early-stage rounds where their size creates structural inefficiency"]}}