Lightspeed Partner Hemant Mohapatra: Venture Capital is a Negotiation About Founders' Ambitions
Lightspeed India partner Hemant Mohapatra stated that venture capital pricing is not a negotiation about valuation, but rather a negotiation about the ambitions of founders: how ambitious they are, whether they express it clearly, and how much external support they need to achieve that goal.
In his view, the valuation number is merely a result, not the starting point of negotiation. Investors need to assess three things: the scale of the founder's vision; whether this vision is clearly articulated into an executable path; and how much capital, resources, and luck are needed to achieve this goal. In other words, the valuation quoted for the same company depends on how grand and credible the story it tells is, rather than its current revenue multiples.
Mohapatra comes from a technical background. He graduated from the Indian Institute of Technology Bombay, worked early on as an engineer and product manager at AMD, responsible for low-power chips for laptops and mobile devices; then spent nearly five years at Google in growth-stage investments in software infrastructure, leading investments in storage company Avere Systems, which was later acquired by Microsoft; he then joined Andreessen Horowitz, focusing on software infrastructure. In 2018, he returned to India to join Lightspeed. He has publicly stated that he prefers "rough, unpolished, a bit crazy, with grand visions and endless optimism" founders.
He has participated in investments in over 20 companies, focusing on AI, data infrastructure, and cutting-edge technology. Notable projects include the open-source backend platform Supabase, Indian large model company Sarvam AI, satellite hyperspectral imaging company Pixxel, data observability company Acceldata, AI agent tool platform Composio, large model fine-tuning tool Unsloth, as well as Solana and NextBillion AI. Among these, Supabase raised funds continuously in 2025, with its valuation rising from $2 billion to about $5 billion. Sarvam AI completed a $41 million Series A round led by Lightspeed in 2023 and was selected for the Indian government's IndiaAI program in 2025 to develop a domestic sovereign large model.
The backdrop of this statement is that in the AI startup wave, "pricing ambition first, then verifying revenue" has become the norm. In 2025, Thinking Machines Lab, founded by former OpenAI CTO Mira Murati, completed a $2 billion seed round before launching any products, with a valuation of about $10 billion; Safe Superintelligence, founded by Ilya Sutskever, saw its valuation rise to about $32 billion the same year, also without a public product. The valuation of such deals is almost entirely based on the scale of the founder's goals and execution credibility, rather than financial metrics.
In terms of market mechanisms, this is a pricing logic driven by power-law returns. The vast majority of returns for venture capital funds come from a small number of super winners, so funds are more willing to pay a premium for the ambition of "potential super winners" rather than for stable revenue multiples. The buyers are increasingly large multi-stage funds and growth funds that need sufficiently large single investments to absorb the amount of capital they manage; the sellers are founders who exchange equity for funds. Capital is clearly flowing towards narrative-driven AI foundational models and infrastructure companies. Benefiting are top founders who can articulate grand paths and have a track record of execution; under pressure are companies with moderate goal positioning that can only be priced based on revenue multiples, as well as late-stage investors and fund LPs facing the risk of down-round financing after entering at high valuations.
Source: Public Information
ABAB AI Insight
"Pricing for ambition" has both created myths and disasters in the history of venture capital. Lightspeed led Snapchat's seed round in 2012 with about $485,000, when the ephemeral messaging app had almost no revenue, and Snap was valued at about $24 billion when it went public in 2017. Peter Thiel invested $500,000 in Facebook in 2004, also betting on Zuckerberg's ambition. A counterexample is SoftBank: in 2017, Masayoshi Son established a vision fund of about $100 billion, pushing WeWork's valuation to about $47 billion, which failed to go public in 2019 and filed for bankruptcy in 2023. Tiger Global rapidly acquired at high valuations in 2021, leading to a loss of about 56% in its hedge fund in 2022. Ambition can be priced, but the cost of mispricing is also amplified by power laws.
From a capital pathway perspective, global venture capital is concentrating on a few giant funds and the AI sector. Lightspeed raised about $9 billion for a new fund in 2025, heavily investing in AI companies; institutions like Andreessen Horowitz and Thrive Capital are also raising funds in the tens of billions. As fund sizes increase, the amount of single investments must be large enough to make a single success meaningful for the entire fund. Thus, large funds are willing to assign valuations of billions of dollars in seed or Series A rounds to capture shares of "potentially the next OpenAI." In the Indian market, Lightspeed's strategy is to bet on local AI infrastructure and sovereign large models, leveraging policy dividends and talent density for future platform-level returns.
Historically, during the 2000 internet bubble, "eyeball economy" was also popular, valuing based on user growth rather than profits, leading to the rapid collapse of companies like Pets.com and Webvan after the bubble burst; surviving Amazon proved the long-term value of grand vision combined with execution. In the zero-interest-rate era of 2021, SaaS company valuations reached as high as 50 to 100 times ARR, which significantly declined after interest rate hikes in 2022. In the current AI cycle, founder backgrounds and target scales have once again become the core pricing factors, with the primary market in a phase of "narrative premium expansion," highly similar to 2021; the difference is that the revenue growth rate of leading AI companies far exceeds that of any previous generation of software companies.
Essentially, this is a transfer of pricing power. In traditional growth-stage investing, pricing power resides with financial metrics: revenue multiples, gross margins, retention rates, with investors and founders bargaining around numbers. In the AI era, leading companies can grow their revenue from zero to hundreds of millions in just one or two years, making historical financial data quickly lose reference significance, thus transferring pricing power to the founder's "ambition narrative" and execution credibility. The mechanism of this transfer lies in the power-law distribution: as long as a few companies can create hundreds of billions of dollars in value, funds will rationally pay a premium for ambition, because the loss of missing a super winner far outweighs the cost of overpaying for a hundred ordinary companies. This also means that risk has shifted from financial models to judgments about people.
ABAB News · Cognitive Laws
- Valuation is the price of ambition, not the price of the present.
- In a power-law world, missing out is more expensive than overpaying.
- Narrative determines starting valuation, execution determines final valuation.