The Federal Reserve meets this week with the S&P 500 sitting just shy of all-time highs. Consensus is for a25 bps cut, with some probability of50 bps. Historically, such moves have been powerful tailwinds:
JPMorgan: Since 1958, cuts made within 1% of all-time highs delivered+15% average returnsover the next year.
Carson Research: In20 of 20 cases since 1980, the S&P was higher 12 months later, averaging+13.9%.
Adam Kobeissi: Since 1980,every timethe Fed cut near record highs, new records followed within a year.
The near-term picture is less reliable, with equities down roughly half the time in the first month. But the historical lesson is clear:short-term volatility, long-term upside.
Valuations, Liquidity, and Capital Flows
Equity valuations remain elevated. TheShiller CAPE ratio near 40is well above average, leaving limited room for pure multiple expansion. Still, lower rates support valuations and activity across credit markets, M&A, and IPOs.
Rate relief matters most in refinancing and liquidity:
Corporate debt: Roughly$6.3Tin maturities through 2029.
Commercial real estate:$1.5T+due by 2026.
Mortgages: 30-year rates near6.35%could unlock$200–300Bof refinancing.
Current Venture Market Snapshot
Venture capital has entered a period of recalibration after the exuberance of 2021, but activity remains significant:
Global VC investment (2024): ~$270B across more than30,000 companies.
U.S. VC fundraising (2024): Over$70B raised, leaving substantial dry powder.
Deal activity: Seed and early‑stage rounds still dominate in volume, while late‑stage deals are more concentrated in AI, defense, and vertical SaaS.
Leading Companies and Valuations (2025 overview)
AI now soaks up ~half of global VC dollars.In Q2’25, funding to private AI companies reached~$47.3B across ~1.4k deals, marking thethird straight quarter above $40B. The quarter was highly concentrated: thetop 10 rounds captured ~60%of AI dollars. With global VC at~$91Bin Q2, AI absorbedroughly halfof total funding.
Capital concentration is extreme.Across venture, dollars keep tilting to the biggest checks: Q2’25 was thethird consecutive quarter >$90Beven asdeal counts fell to multi-year lows; analysts note a clear shift toward fewer, larger financings.
Unicorn creation has re-accelerated.June 2025 alone saw20 new unicorns—the most in three years. Year-to-date,~77 new unicornshave been added, and theglobal unicorn roster is ~1,600companies (methodologies vary by provider). The U.S. leads new additions, with China and India also active.
Valuations: late-stage up, seed softer.PitchBook data showmedian pre-money valuations rose across stages, withventure-growthjumping sharply year-over-year, whilepre-seed/seed medians fell ~20%versus 2024. Big checks remain pivotal:$100M+ deals represented ~41%of totals at the start of 2025 (down from 49% in 2024 but still elevated).
Secondaries are the pressure valve—and pricing is bifurcated.Secondary volumes surged to~$102B in H1’25, on pace for anotherrecord year (~$175–200B). Pricing hasnarrowed meaningfully: companies that raisedrecent primary roundsare tradingnear par (≈0–8.5% median discount), whilepandemic-era namesstill clearat sizable markdowns; across the market, amedian ~-27% discountis a reasonable guidepost, improved from ~-39% a year ago.
What to take away:2025’s “leaders” are less about individual names and more aboutwhere capital is pooling—AI, mega-rounds, and late-stage vehicles. Valuation strength isuneven but improvingat growth stage, unicorn formation hasrestarted, and thesecondary marketis providing real liquidity withtighter discounts—especially for companies with fresh marks.
AI Infrastructure: The New Internet
The real story is the build‑out of AI infrastructure. The Magnificent 7 are investing more than$100B per quarterin CapEx:
Amazon: $100B+ projected for 2025.
In total, 2025 AI/data‑center CapEx will surpass$350–400B, creating the backbone for AI training, inference, power, and connectivity. This spend is structural, not cyclical—it will happen regardless of Fed policy.
Beyond Chatbots: Unlocking Enterprise Value
ChatGPT introduced AI to the public, but the larger opportunity is in enterprise adoption. Corporations sit ontrillions of dollars in latent valuelocked in proprietary datasets. Unlocking it requires:
Guardrails: Governance, compliance, and safety frameworks.
Foundations: Infrastructure for training, inference, and secure data integration.
Integrations: Embedding AI into workflows, leveraging proprietary datasets to create defensible moats.
This is far more complex than the SaaS wave of the last decade, which delivered dashboards and analytics. AI involves piping, interconnectivity, and massive data engineering. The costs—hundreds of billions, if not trillions—are difficult for even seasoned investors to fully quantify, but they are necessary to realize AI’s potential.
Implications for Venture Capital
Valuations: Some are frothy, but multiple support from public comps and easing rates will help stabilize the market.
Liquidity: IPOs and M&A will gradually reopen, while secondaries provide interim exits.
Capital flows: LPs will reallocate from cash and credit into venture, chasing innovation.
Vertical AI: Startups will dominate industry‑specific applications, from healthcare to finance to defense, building on hyperscale infrastructure.
Winners and losers: There will be failures, but history shows that venture returns are defined by outliers. Microsoft, Amazon, Alphabet, and Meta—once risky startups—were all VC‑backed. Outliers will again outweigh losses.
We are in the early innings of building the new internet. Rate cuts support capital markets, but the AI super‑cycle is what drives the transformation. This requires building the guardrails, the foundations, and the integrations that allow enterprises to adopt AI at scale.
Yes, valuations are high, and yes, there is some frenzy. But this is what it takes to finance foundational infrastructure. The money on the sidelines—hundreds of billions in dry powder—will flow. Winners will emerge, losers will be absorbed, and the outcome will be a new layer of the economy built on AI.
Venture capital is in the business of exits!And in this cycle, the exits will be defined by the companies that build and harness the infrastructure of intelligence itself.
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