Is investing REALLY the hardest job? A TWIST VC Roundtable (ft. Deedy Das and Jay Eum) | E2204

Key Concepts

• Venture Capital Industry Transition: The VC landscape is undergoing significant changes, moving from traditional finance-focused investors to operators with "scar tissue" and experience in building companies.
• Sequoia Capital Leadership Change: The departure of Roelof Botha from his stewardship role at Sequoia Capital, handing over to Alfred Lin and Pat Grady, is discussed as a significant event, highlighting Sequoia's long history of generational transitions.
• Menlo Ventures' Strategic Shift: Menlo Ventures is actively recruiting experienced operators and business leaders to complement its traditional investor base, aiming to combine operational expertise with financial acumen.
• AI's Impact on Startups: The rapid growth and willingness to pay for AI-powered products are creating significant opportunities, but also challenges related to retention, margins, and the potential for AI-generated content to saturate online platforms.
• Funding Environment Evolution: The pre-seed and seed funding landscape has become more competitive, with higher expectations for traction and revenue, driven by a reduction in available capital for early-stage, pre-revenue companies.
• Global Startup Ecosystem: Innovation and strong startup formation are no longer confined to Silicon Valley, with emerging hubs in regions like Saudi Arabia, Asia, and Scandinavia producing significant companies.
• The Role of Data and Due Diligence: In a frothy market, there's a risk of reduced due diligence, leading to potential issues like those seen with FTX. Maintaining discipline and standard practices is crucial.
• Founder vs. Investor Challenges: While founders face immense pressure to execute and grow, investors also grapple with the difficulty of identifying and backing successful companies in a rapidly evolving market.
• AI Content Generation and Authenticity: The rise of AI-generated content raises concerns about the "dead internet theory" and the potential for a loop of AI consuming AI-generated content. This is leading to a counter-movement emphasizing human-generated content.

Sequoia Capital's Leadership Transition and Industry Shifts

The discussion begins with the recent leadership change at Sequoia Capital, where Roelof Botha has stepped down as chief steward, passing the reins to Alfred Lin and Pat Grady. Jason Calacanis, a long-time friend of Botha, expresses surprise but acknowledges Botha's significant contributions, including his role in building Sequoia into a legendary firm. He notes that Sequoia has a tradition of generational stewardship, citing Don Valentine, Michael Moritz, and Doug Leone as predecessors. Calacanis also touches upon recent controversies surrounding Sequoia, such as the divestment of China/India funds, the FTX situation, and public statements by Shaan Puri, though he is unsure if these contributed to the leadership change.

Jay, from GFT Ventures, adds that he saw Botha recently at a Stanford Business School event where Botha discussed stewardship. Jay admires Sequoia's model of handing over leadership to the next generation to prevent stagnation. He contrasts this with the past, where firms like Kleiner Perkins were also prominent, but Sequoia has since solidified its dominant position. Jay also recalls a conversation with Jim Gats, a prior Sequoia steward, who intentionally stepped back to allow new leaders to emerge.

Dee Doss, a new partner at Menlo Ventures, expresses his surprise at the news, having had positive interactions with Botha and the Sequoia team. He acknowledges that a firm of Sequoia's stature will always attract scrutiny, especially during such transitions.

Menlo Ventures' Strategic Evolution and Dee Doss's Role

Dee Doss shares his perspective on his recent promotion to partner at Menlo Ventures. He expresses gratitude for being brought into venture capital despite lacking prior direct experience, having learned through online writing and his involvement with the successful startup Glean. Doss emphasizes his focus on teamwork and reinvigorating the firm's mission. He highlights Menlo's long history (50 years, 17th fund) and the current period as one of "resurgence and rebuilding."

Doss details Menlo's strategic hiring of individuals with operational experience, such as Tim Tully (CTO of Splunk), Joff Redern (CPO of Atlassian), and Matt Craning (founder of a cybersecurity unicorn). The firm aims to "marry" these experienced operators with investors who understand finance and long-term vision. Doss states his current focus is on defining the firm's investment principles and partnering with the best founders. He humorously notes that his increased media presence might be due to Menlo's media training budget.

Calacanis observes that the venture capital industry has shifted from professional finance individuals to founders with "scar tissue" and battlefield experience, a trend exemplified by Doss's own background.

The Changing Venture Capital Landscape

The conversation delves into the broader shifts in the VC industry. Calacanis notes the transition from a model where VCs were primarily finance professionals or entered the field early in their careers to one where founders are expected to have operational experience. He also points out the bifurcation of the industry into boutique, handcrafted models and large, multi-billion dollar platforms like Andreessen Horowitz, which can sometimes lead to average returns. Sequoia, he argues, has successfully maintained its traditional venture model.

Jay discusses the global nature of innovation, with great companies emerging from regions like Riyadh, Seoul, and Tokyo, not just the US. He also highlights the strategic element of government-driven funding in some regions, focused on job creation and innovation, which may not solely benchmark against pure financial returns. He explains that GFT Ventures was founded by former corporate venture capitalists with a specific focus on frontier tech, particularly AI and data science, a thesis that proved serendipitous with the rise of ChatGPT.

Doss brings up the point that throwing more money into Silicon Valley doesn't necessarily yield more great companies, referencing Roelof Botha's sentiment. However, he counters this by observing the current density of great companies being built and scaled, citing Glean's rapid growth to over $100 million ARR.

Calacanis agrees that there's too much capital chasing too few great ideas, leading to inflated valuations that can make seed investing difficult. He mentions a seed investor who might only see a 2.5x return on a unicorn investment due to dilution. He also quotes Botha's remark about "return-free risk" venture capital.

Jay emphasizes that innovation is global and that while the US ecosystem is private capital-driven, other regions have strategic funding objectives. He also notes the difficulty of justifying a new venture firm without a clear reason for existence, highlighting GFT Ventures' specific focus on frontier tech.

The Rise of AI and Willingness to Pay

Doss discusses Glean's $100 million ARR milestone, noting that such achievements are now less heralded due to the sheer volume of companies reaching similar scale. He attributes this to the "boring B2B top-down sales" nature of Glean, contrasting it with the broader appeal of companies like ChatGPT. He also points out that companies at this growth stage are raising at high, forward-looking valuations, which attracts media attention.

Doss further elaborates on the shift in how large growth-stage companies view going public. With ample private market capital, some founders question the necessity of an IPO, preferring the ease of private markets and avoiding SEC reporting.

Jay highlights the "smile curve" phenomenon in AI retention, where users may churn but return and even increase their engagement over time, indicating strong product-market fit. He contrasts this with traditional enterprise SaaS retention.

Doss agrees that there's immense willingness to pay for AI products. He argues that growth is harder to fix than retention or margins, making him comfortable backing companies with strong growth potential. He uses ChatGPT's retention curve as an example, showing how it has improved significantly over time.

Calacanis adds that the infrastructure for AI adoption is in place, and businesses are willing to pay for tools that enhance productivity, making it an easy decision for management to invest in such tools rather than hiring more personnel.

Jay discusses Higsfield, a B2C company in short-form video creation for creators, which has seen 60x ARR growth in six months. He notes that while not as "sticky" as enterprise revenue, this "prosumer" segment is loyal.

Doss reiterates the willingness to pay for AI, emphasizing that growth is the primary driver for investors, with retention and margins being fixable issues. He points to the massive weekly active user base of OpenAI as a factor that mitigates the importance of retention percentages.

The discussion touches on the adoption of AI in India, noting differences in internet usage patterns, with YouTube being more dominant than search, and a generally lower willingness to pay for software compared to the US.

Doss explains the "smile curve" in cohort retention for ChatGPT, where users who initially churn return and increase their engagement, signifying strong product-market fit. He contrasts this with the lower retention of other products and argues that growth is the most critical factor for investors.

The Evolving Pre-Seed and Seed Funding Environment

Jay addresses the increasing bar for pre-seed funding, attributing it to the AI boom masking a tougher environment for other sectors. He notes that much of the capital that rushed in during the 2021 bubble has receded, making it harder for pre-seed and seed funds to raise capital. This leads to more selective investing, with a preference for companies demonstrating traction and product-market fit, reducing the need to take on pre-revenue risks. Jay shares an example of investing in a profitable $1 million ARR company at a sub-$20 million post-money valuation.

Calacanis echoes this, stating that founders are competing against each other, not just their past selves. He likens the current situation to the public markets, where there's a "flight to quality," with investors favoring companies with strong revenue growth, margins, and network effects, even at the seed stage.

Doss presents data showing a decline in deal count despite a return of capital to the market, indicating a more selective investment environment. He explains Menlo Ventures' strategy of lower-volume, concentrated investments, which carries higher variance but aims for outlier returns.

Calacanis emphasizes that the hardest job is being a founder, but acknowledges the significant compensation for VCs. He highlights that founders who can execute and focus on revenue growth are the ones getting funded, with companies growing 20% monthly being preferred over those growing 5%.

The discussion then explores the disconnect between VCs giving up and the abundance of great companies. Calacanis attributes this to an oversupply of VCs, particularly those who entered the market during the bubble and engaged in less rigorous due diligence. He likens the ecosystem to Darwinian selection, where revenue-generating companies (the "sharks") receive more resources. He notes that VCs who relied on blind betting and lacked time diversification (deploying capital too quickly) are struggling to raise new funds.

Jay adds that timing (vintage year) is a primary driver of VC returns, and those who deployed capital at peak valuations without time diversification are at a disadvantage.

Jay discusses entry prices, noting that while median valuations have normalized, underlying revenue growth is stronger, leading to better-priced opportunities. However, he cautions that at the extreme end, companies with no revenue are still raising at billion-dollar valuations, driven by the "AI guys" narrative.

Doss highlights the rapid growth of companies like Anthropic, tracking to $10 billion in ARR, and notes that these companies have historically underestimated their projections.

Doss and Calacanis debate whether founders or investors have the harder job, with Calacanis ultimately stating that founders have the clearer path to making "big money," while VCs have better work-life balance. Doss candidly shares his intense work ethic as a new entrant to the industry.

Jay describes the constant "on" nature of VC work, driven by the need to keep pace with founders and the speed of deals. He shares an anecdote about a founder securing term sheets without a fully prepared data room, illustrating the rapid deal-making.

Calacanis warns against the lack of discipline and due diligence during hot markets, citing FTX as an example. He describes how greed and a suspension of disbelief can lead to unethical behavior and a lack of transparency in deal terms. He advises founders and VCs to stick to standard documents and avoid "games." He also notes that in hot markets, founders may try to extract concessions from early investors.

Jay acknowledges hearing stories of malfeasance and poor behavior, and notes that FOMO (Fear Of Missing Out) is reaching bubble levels, with founders being aggressively pursued.

The Impact of AI on Marketing and Content Generation

Doss discusses the trend of founders using social media for viral growth, particularly on platforms like TikTok and Instagram. He believes that while viral marketing is acceptable, the product must follow. He expresses concern about AI-generated content spamming platforms like Reddit and LinkedIn, potentially creating a "dead internet theory" scenario where bots consume AI-generated content.

Calacanis counters that the quality of short-form video creation is improving dramatically, with AI tools enabling sophisticated content generation. He highlights the efficiency of using AI for virtual likenesses, auto-generated scripts, and targeted distribution. He shares an investment in Lizer, an AI chatbot company that used its own tools for fundraising, demonstrating "eating their own dog food."

Doss expresses philosophical opposition to the "dead internet theory" but acknowledges that founders will use any avenue for engagement. He notes the emergence of "human-only" or "100% human" labeling as a reaction to AI-generated content. He praises the storytelling ability of founders like Elon Musk and Steve Jobs, and how current tools enable punchy short-form video storytelling to explain value propositions.

Portfolio Company Shout-outs and Future Outlook

Jay's Favorite Portfolio Company: Abacus, a bootstrapped company that has reached $1 million ARR. Abacus provides an AI foundry service for enterprises in industries like finance and healthcare, where data cannot leave the premises. They enable customers to train AI models on their own data using open-source models and offer an application generation platform for in-house AI solutions, with a focus on accuracy and hallucination screening.

Dee Doss's Favorite Portfolio Company: GoodFire, a mechanistic interpretability company focused on understanding how AI models work. Doss believes this is fundamental for society to trust AI, as we cannot rely on black boxes for critical decisions. He highlights the team's expertise from leading AI research institutions and their potential for significant scientific breakthroughs. He also briefly praises OpenRouter for its product-led growth strategy and its role in a multimodal AI world.

Jason Calacanis's Favorite Portfolio Company: NextVisit AI, an AI-powered clinical note-taker specifically for psychiatry. The company has a co-founding team of a psychiatrist and an AI specialist, and has quickly achieved high fidelity in a niche vertical. Calacanis emphasizes the importance of laser focus and executing exceptionally well on a specific problem, drawing parallels to companies like Robinhood.

The discussion concludes with reflections on the intensity of work in venture capital and the importance of long-term games, respect, and avoiding unethical practices in a rapidly evolving industry. The panel also touches on the quality of Paul Thomas Anderson films, highlighting a shared appreciation for cinema.