💥Why You Need a New CFO, Small Funds Disappear, Optimal Portfolio Size, Future Path for AI Labs & More

1. Key Themes

Theme: Capital Concentration Is Reshaping Venture, and Small Funds Are Losing Their Seat

Insight: The last small-by-choice firms have scaled up.

• "Kyle Harrison at Contrary argues that USV and Benchmark, the last firms that stayed small by choice, have now scaled up, and asks what that shift means for the companies venture will fund."
• "USV announced $900M across its newest funds, the largest cycle in its history, about four months after Benchmark raised $2B, its first meaningful step up since 1999, including a first-ever $1.25B growth fund."

Insight: LP capital is highly concentrated.

• "In Q1 2026, roughly 73% of LP capital raised went to just five firms. a16z alone held over $40B in AUM, against roughly $4.8B at Benchmark before its new raise."

Insight: Fund size determines which outcomes matter to a lead investor.

• "Harrison argues the rounds that decide a company's fate now come later and are led by megafunds, so the only way to protect founders was to grow big enough to join them."
• "For founders, a lead investor's fund size decides which exits move its needle, so ask early what outcome it needs to return the fund."

Theme: AI Models Are Commoditizing, and Value Is Shifting to Distribution

Insight: Prices are falling as usage climbs.

• "Token usage has risen 50% since July while prices fell 41%, according to Ramp's AI Index. OpenAI cut prices on Luna by more than 80% to win share."

Insight: Buyers are trading down from frontier models.

• "The share of tokens going to frontier models, the most capable and priciest tier, slipped from 53% in August into the mid-40s, according to Ramp data, as companies defaulted to smaller, cheaper models."

Insight: Distribution and data become the moat.

• "Tunguz's playbook for labs has three parts: (1) resell other providers' models, as OpenAI has announced with Baseten, (2) own the interface customers use, and (3) use data on which model handles each request to lower future training costs."
• "If models become interchangeable, value moves to whoever owns the customer, so investors should weight retention and switching costs heavily when assessing AI application startups."

Theme: AI Tooling Is Changing Who Builds Companies and How Lean They Run

Insight: Solo founders are a growing share of new startups.

• "Solo founders led 37.9% of US companies founded on Carta in H1 2026, up from 23.4% in H1 2019, based on half-year founding cohorts."
• "The share climbed 5 points over five and a half years, from 23.4% in H1 2019 to 28.4% in H2 2024, then another 9.5 points in the 18 months to H1 2026."
• "Shad credits vibe coding tools with making a minimum viable product easier to build, though he doubts they can fully replace technical expertise for securing that software and keeping it robust long term."

Insight: The finance function is being re-architected around AI.

• "The authors see CFOs increasingly acting as 'finance engineers' who build their own tools with AI coding assistants. At Anthropic, one such tool produces a 90-95% complete monthly financial review in about thirty minutes."
• "The old rule of thumb put finance at about 5% of headcount. The leanest teams a16z sees now target 2%, hiring people who write SQL and prototype automations."

Theme: Portfolio Construction Math Should Drive Fund Strategy

Insight: Portfolio size changes the odds of a good outcome, not the average return.

• "The modeled average fund returns 2.06x gross at every portfolio size, but the median rises from 1.57x with 10 companies to 1.92x at 40 and 2.01x at 100, because each added company is another shot at the roughly 4% of deals that return 10x or more."

Insight: There is a trade-off between upside and downside protection.

• "A 10-company fund has a 34% chance of owning a 10x and a 26% chance of losing money. At 40 companies, those odds move to 80% and 4%."
• "The top 5% of 10-company funds return 5.5x or more gross, against 3.5x at 40 companies, assuming the 40th deal is as good as the 10th. Setting fund size aside, Leventis puts his sweet spot at 40-60 companies."

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2. Contrarian Perspectives

Contrarian View: The CFO's scarce skill is now architecture, not accounting, banking, or FP&A

• Conventional wisdom treats the CFO as a financial steward drawn from accounting or banking backgrounds. The a16z authors argue the role has changed with each era and is changing again.
• "Companies first hired CFOs from Big 4 accounting firms, then from investment banking, then for financial planning and analysis (FP&A). The authors see today's scarce skill as designing the data, workflows, and agents a company runs on."
• Evidence: the ~2% finance headcount target, and a CFO-built tool at Anthropic producing a "90-95% complete monthly financial review in about thirty minutes."

Contrarian View: Reference calls are the most underrated hiring tool, and most firms run them badly

• The default reference check is treated as a formality. Berson argues it is a wasted source of signal.
• "Berson says the typical reference check in tech and venture is a short call with generic questions and glowing answers from people the candidate picked, which adds little and can simply confirm what the team already believes."
• His fix is to scale rigor to stakes: "at least 3 references for junior hires, at least 5 for mid-level hires, and 12 or more for executives, since a wrong executive hire costs far more than a wrong intern hire."

Contrarian View: Diversification caps the upside, so a concentrated 10-company fund is not irrational

• The common wisdom is that more companies is safer. The model shows the tradeoff in tail outcomes.
• "The top 5% of 10-company funds return 5.5x or more gross, against 3.5x at 40 companies." A concentrated fund has roughly a 1 in 4 chance of losing money, but also a shot at standout returns.

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3. Companies Identified

Union Square Ventures (USV)

• Description: Venture firm that previously stayed small by choice.
• Why mentioned: Case study in the end of the small-fund model.
• Quote: "USV announced $900M across its newest funds, the largest cycle in its history."

Benchmark

• Description: Venture firm known for its small partnership and fund size.
• Why mentioned: Scaled up for the first time since 1999.
• Quote: "Benchmark raised $2B, its first meaningful step up since 1999, including a first-ever $1.25B growth fund."

a16z

• Description: Large venture firm.
• Why mentioned: Example of capital concentration; also authors of the CFO piece.
• Quote: "a16z alone held over $40B in AUM, against roughly $4.8B at Benchmark before its new raise."

OpenAI

• Description: Frontier AI lab.
• Why mentioned: Competing on price and distribution as models commoditize.
• Quote: "OpenAI cut prices on Luna by more than 80% to win share."

Baseten

• Description: AI inference/model provider.
• Why mentioned: Partner in OpenAI's reselling strategy.
• Quote: "resell other providers' models, as OpenAI has announced with Baseten."

Ramp

• Description: Spend management company that publishes the AI Index.
• Why mentioned: Source of token usage and pricing data.
• Quote: "Token usage has risen 50% since July while prices fell 41%, according to Ramp's AI Index."

Anthropic

• Description: AI lab.
• Why mentioned: Example of a CFO-built finance tool.
• Quote: "At Anthropic, one such tool produces a 90-95% complete monthly financial review in about thirty minutes."

Carta

• Description: Cap table and equity management platform.
• Why mentioned: Source of the solo founder data.
• Quote: "Solo founders led 37.9% of US companies founded on Carta in H1 2026."

Correlation Ventures

• Description: Venture firm with a data-driven approach.
• Why mentioned: Provided the dataset for the portfolio size model.
• Quote: "using Correlation Ventures data on 21,640 US financings."

Affinity

• Description: AI-first private capital CRM (newsletter sponsor).
• Why mentioned: Promoted its ROI Calculator for deal team time loss.
• Quote: "time leaks out of every stage: logging notes and updating CRM records, piecing together context the firm already has, and tracking down connections a teammate already made."

Contrary, Theory Ventures, First Round

• Description: Venture firms whose partners authored the cited analyses.
• Why mentioned: Sources of the featured research and perspectives.
• Quote: "New insights from a16z, Carta, Contrary, First Round, Theory Ventures & more."

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4. People Identified

Kyle Harrison

• Description: Contrary.
• Why mentioned: Analyzed the scale-up of USV and Benchmark.
• Quote: "Kyle Harrison at Contrary argues that USV and Benchmark, the last firms that stayed small by choice, have now scaled up."

Fred Wilson

• Description: USV co-founder.
• Why mentioned: Expectation of USV's returns from mid-sized winners.
• Quote: "Fred Wilson still expects USV to produce strong returns if its biggest winners land in the single-digit billions."

Mackey Leventis

• Description: Fund modeler/analyst.
• Why mentioned: Modeled optimal portfolio size.
• Quote: "Setting fund size aside, Leventis puts his sweet spot at 40-60 companies."

Tomasz Tunguz

• Description: Theory Ventures.
• Why mentioned: Argues AI models are commoditizing and describes the labs' playbook.
• Quote: "Tomasz Tunguz at Theory Ventures argues that AI models have reached commodity status."

Hamza Shad

• Description: Carta.
• Why mentioned: Tracked the rise of solo founders and links it to vibe coding.
• Quote: "Hamza Shad at Carta tracks the share of newly founded US startups on Carta led by a single founder."

Seema Amble, Ivan Makarov, David Borecky

• Description: a16z authors.
• Why mentioned: Argue AI turns the CFO into an architect of the operating system.
• Quote: "AI-native tools are making the CFO an architect of the company's operating system, run by a smaller, higher-leverage finance team."

Brett Berson

• Description: First Round.
• Why mentioned: Developed "composite referencing."
• Quote: "Brett Berson at First Round explains how he runs reference calls as a core hiring tool, a method he calls composite referencing."

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5. Operating Insights

Hire a first CFO who builds, not just reports

• "Founders hiring a first CFO should look for someone who decides which finance work software should handle and builds those tools, since the a16z team expects this to free up the CFO's time for bigger decisions like pricing and compute spend."
• Staff finance with people who "write SQL and prototype automations."

Route each task to the cheapest model that works

• "Founders can turn falling token prices into margin by sending each task to the cheapest model that handles it well."
• This aligns with buyers' observed shift to smaller, cheaper tiers.

Run references early and widen the circle

• "He runs about a third of references early, before the team is committed, mixes candidate-named references with backchannel calls, and ends every call by asking who else knows the candidate."
• "Prepare about 10 questions built around the role and your open doubts... When praise sounds hesitant, dig deeper with follow-ups."

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6. Overlooked Insights

Frontier-tier token share is quietly eroding

• "The share of tokens going to frontier models... slipped from 53% in August into the mid-40s." Frontier labs' pricing power may be weakening faster than headline usage growth suggests, since the premium tier is losing share even as total usage rises.

The portfolio-size model's assumptions overstate real-world returns

• "These are pre-fee figures assuming equal checks and no follow-on funding, so actual returns will come in lower."
• The solo founder data also has limits: "The data counts newly founded companies only and does not show whether solo-led startups raise or exit at similar rates, so treat it as a sourcing signal for now."