Which Startups (And VCs) Survive a Bear Market — With Nina Achadjian

Episode Summary

Executive Summary: The episode examines how the 2022 market downturn is reshaping startups and venture capital. Nina Shadian argues that the era of cheap money, inflated valuations, and growth-at-all-costs is ending, pushing founders back toward fundamentals: efficient growth, mission-critical products, and profitability. She sees this as a healthy correction that will likely slow hiring, cool late-stage investing, and favor high-quality companies, while still leaving plenty of capital for early-stage startups and new innovation in AI and vertical software.

Main Topics: Market downturn and its impact on startups: The discussion opens with public-market declines and how they affect startup funding, exits, and IPO appetite. Nina explains that startup valuations and fundraising behavior were distorted by cheap capital and strong public markets, and that the current downturn is forcing a reset. How startup fundraising changed during the boom: Nina details how pre-seed, seed, Series A, and growth rounds expanded dramatically in size and came with faster timelines and higher valuations. The result was misalignment between company traction and investor expectations. Return to fundamentals and 'quality' startups: The conversation centers on what makes a durable company in a tighter market: mission-critical software, efficient customer acquisition, revenue growth, and a path to profitability. Nina says weak startups will be exposed by this environment. Late-stage VC, IPOs, and capital returns: The episode explores the challenges for late-stage venture firms that need public-market-style returns. Nina argues that many late-stage deals are hard to underwrite now, which will likely delay IPOs and push companies to improve their financial story before going public. AI's real-world enterprise applications: Nina is optimistic about AI when applied to business workflows, especially in sales, healthcare, and back-office automation. She highlights companies like Gong and DeepScribe as examples of AI moving beyond technical teams into everyday enterprise functions. Vertical software as a durable investment theme: She identifies vertical software—industry-specific tools combined with embedded payments and fintech infrastructure—as one of the most promising areas in tech. These products are tailored to real operational needs in industries often overlooked by Silicon Valley. Crypto skepticism and healthy debate: Nina says she is not focused on crypto and remains cautious due to regulation, safety, and unclear customer value. She supports open criticism and believes technologies need to withstand scrutiny to prove long-term value.

Key Arguments: The last two years featured historically cheap capital, which inflated startup valuations far beyond underlying traction. Founders often accepted oversized rounds because competitors were raising big sums, which increased pressure to keep up. Higher valuations brought hidden costs, including option pool dilution risk and underwater employee equity when market multiples reset. The current environment forces startups and boards to focus on burn reduction, unit economics, and revenue efficiency. Late-stage venture is especially difficult because investors need large multiples, but public-market comparables no longer justify previous pricing. A major IPO backlog exists, and many companies are waiting for a better market and a stronger profitability narrative before going public. Venture capital as an asset class still has abundant committed capital, so the system is not starved of money even if some crossover money leaves. AI is most promising when it automates high-value, nontechnical work for sales, medicine, and operations rather than only for engineers. Vertical software is attractive because industry-specific products can bundle workflows, software, and payments into durable businesses. Crypto remains interesting but faces unresolved issues around regulation, transparency, and real customer utility.

Data Points: S&P 500 year-to-date decline: 13% down - Used at the start to describe the public-market downturn affecting sentiment and startup exits. NASDAQ year-to-date decline: 23% down - Presented as the tech-heavy index most relevant to startup and tech IPO expectations. Typical pre-seed round size: $500K to $1M - Described as the early funding range for a founder getting started. Typical seed round size before the boom: $2M to $3M - Historical seed-round size before the last two years of expansion. Typical seed round size during the boom: $5M to $7M - Seed rounds grew because investor demand was intense and capital was cheap. Typical Series A round size before the boom: $7M to $10M - Historical Series A benchmark before 2020-2021 inflation. Typical Series A round size during the boom: $10M to $25M - Series A rounds expanded significantly in the low-rate environment. Typical dilution in past seed/Series A: ~20% per round - Nina notes founders used to sell about 20% of the company in a round. Dilution in recent seed rounds: <10% in some cases - She says investors bought smaller slices of rounds during the capital surge. Committed venture capital raised in the prior year: $330B - She cites this as locked-in capital that VCs must deploy over the next two to three years. Tiger Global hedge fund performance: Down 52% in 2022 - Referenced as an example of crossover/private-public investor pain. Tiger Global long-only fund performance: Down 61.7% in 2022 - Another example of severe losses in crossover investing. Public-market realization from 2018 IPO cohort: About a third trading below IPO price - Used to show that many tech IPOs did not return expected capital to investors. Workloads still on-premise: 80% to 90% - Cited as evidence that digital transformation is still early across enterprise IT.

Pivotal Quotes: "I think valuations just got way out of whack the last two years. I think we're seeing a cooling of that, and I think we're going back to a focus on fundamentals." — Nina Shadian: Her core thesis on why the market correction is healthy for startups and investors. "Quality startups are startups that are solving a mission-critical problem, meaning your customers literally could not live without your software." — Nina Shadian: Her definition of what will survive and thrive in the new environment. "This is probably the best time to invest in venture capital because the valuations have come down." — Nina Shadian: Her argument to LPs and long-term investors that downturns can create attractive entry points.

Implications: Founders should prioritize efficiency, retention, and real customer value over blitzscaling. Late-stage funding and IPOs may stay muted, while early-stage capital remains available. The next winners are likely to be disciplined companies solving real problems with durable economics.