Most VCs Are Afraid to Be Wrong | Rohan Pujara
Summary
Rohan Pujara avoids seed categories where consensus capital creates inflated entry prices, instant copycats, and structurally weak margins. He separates seed from growth: following momentum can make sense at Series A and beyond, but at formation it puts startups into a “knife fight” with ten competitors before they have a foothold. Agents, infrastructure models, neolabs, data centers, energy, chips, and defense currently look crowded to him; Valhalla instead searches their neglected edges.
Pujara thinks venture capital’s professionalization has replaced risk-takers with careerists who fear looking wrong more than losing money. His phone contains only 21 people who have personally generated more than $1 billion in DPI, remarkably few against 50 years of venture activity. His conclusion is deliberately harsh: convexity gives many investors one lucky success, while repeatability exposes how few are genuinely good.
Valhalla underwrites distinctive people before it underwrites fashionable markets. Pujara wants founders with independent histories, courage, trustworthiness, social agility, and visible energy—not prestigious degrees—and treats polarized references as stronger evidence than lukewarm approval. “You should leave a lasting impression on anyone who interacts with you”; a founder everyone merely likes is often less interesting.
Valhalla’s concentration model turns this philosophy into an unusually focused portfolio. From an $80 million–$100 million fund, Pujara wants only two to four exceptional new investments annually and can write a $10 million seed check; if one becomes an unmistakable fund-returner, he plans to allocate 20%–30% of the fund. The opposing statistical case—roughly 30 checks to improve the odds of catching one or two outliers—remains José’s strongest challenge.
K2 Space and Jaza are the clearest demonstrations of Valhalla’s non-consensus playbook. K2 bet on large, power-rich satellites while the market copied small-satellite successes; three and a half years later, Pujara says it still has no real competitor, has signed more than $1 billion of business, and is raising at a $6.8 billion valuation. Jaza spent 2017–2023 finding a workable electricity model in sub-Saharan Africa, then raised $100 million and grew roughly tenfold year over year.
Aftersort[?] and Truffle show how Pujara approaches technical bets without pretending to possess perfect technical foresight. Aftersort[?] offered a principled answer to a real LLM limitation; Truffle wagers that token demand will exceed centralized AI infrastructure capacity, perhaps visibly by early 2027 and, in the worst case, 2028. Its personal AI device, custom weights, supply-chain work, and three-year lead make it “probably the perfect Valhalla investment.”
Pujara ties his risk tolerance to having repeatedly discovered that financial ruin was survivable, while tying Valhalla’s future to aligned incentives. Childhood scarcity, seven or eight moves, leveraged crypto losses, and taking a delivery job with $0 in the bank weakened the instinct to protect status: “Don’t gamble,” but do take underwritten risk. His institutional ambition is a flexible private-markets firm where managers and LPs have their own capital exposed, because “incentives rule the world.”
Deep dive
1. Consensus destroys seed economics before it validates the market
Pujara’s objection is not to large markets but to categories where every fund reaches the same conclusion simultaneously. Once consensus forms, startups confront copycats, Meta-scale incumbents, expensive entry valuations, and a “knife fight” that can drive profit margins toward zero from day one.
José’s Cursor challenge—worth keeping—is that crowded, obviously enormous markets can still produce extraordinary winners. Pujara’s answer is stage-specific: early Cursor was not yet a consensus coding-agent bet, while Series A and growth investing are different games where following demonstrated momentum can make sense.
Responding to Ian from Cantos’s argument that private information makes “consensus” a public-markets concept, Pujara says relevant information still circulates efficiently among Tier 1 funds and emerging managers through group chats and shared deal flow. Outside that network, information fragments: most Tier 1 firms would not even interview an African energy company like Jaza.
Geography reinforces the effect. San Francisco is, in Pujara’s words, “the home of consensus”: the same language, parties, investors, and companies. He prefers New York as a meeting hub and sees LA—especially around SpaceX, Anduril, K2, and El Segundo—as a growing refuge for ambitious people who want the West Coast without its dominant intellectual bubble.
2. Venture professionalization rewards reputational safety over risk
Pujara calls the change the “MBA-ification of venture capital,” though he does not limit it to MBA holders. As VC became prestigious, it attracted highly credentialed, status-conscious careerists who want to be right with everyone else and are especially afraid of being wrong when the group is right.
Earlier generations included investors such as Michael Moritz, Vinod Khosla, and Fred Wilson, who arrived through less standardized paths. Pujara doubts that many people who prepare for venture from undergraduate school are natural risk-takers—or even investors capable of operating in another asset class.
His private scorecard contains only 21 people who have produced more than $1 billion of DPI through personal investments. Against the number of people practicing venture over five decades, that scarcity suggests convex returns can make someone lucky once; consistently repeating that success is the rarer skill.
José supplied the starkest crypto contrast: extremely intelligent people made no money while less conventionally brilliant participants took risks confidently at the decisive moment. Pujara’s own self-description is intentionally deflationary—“on the left side of a normal distribution”—because he thinks avoiding elaborate forecasts helps him focus on people and durable businesses.
3. Proprietary sourcing begins with unusual people, not fundraising lists
Valhalla cultivates people who are “a little controversial” or polarizing, studies why they see the world differently, and remains close to them long before a financing. When one starts a company or says, “Hey, check this out,” the relationship produces access without monitoring every active seed round.
That approach often reaches founders who are not fundraising. In unconventional fields, having one investor genuinely believe them can matter more than manufacturing competition; Valhalla has rarely competed across multiple term sheets and may interpret an already crowded process as evidence that the opportunity no longer fits.
Pujara does not require outrageous public behavior. He wants someone who stands apart, thinks from first principles, chose an uncommon path, and will express a genuine view despite reputational pressure. A reference saying “I don’t like that person” or “I disagree with them” may be informative; indifference is worse.
His adverse-selection heuristic is similarly blunt: if someone contacts Rohan at Valhalla, that can be a warning. He would rather identify the person through research, understand why the idea belongs in Valhalla’s opportunity set, and initiate the conversation himself.
4. Courage, trust, and agency matter more than pedigree
The first underwriting question is whether the founder has taken real risks when prevailing advice felt wrong. The second is trust: Valhalla expects to own companies for 10 or 15 years, not sell magically after two, so Pujara will not enter that relationship with someone he cannot trust.
Intelligence remains necessary, but résumé proxies do not. Pujara often does not know whether a founder attended university, much less their grades; he values quick reactions, social navigation, proactivity, and the energy of someone visibly pursuing an objective more than raw IQ.
Motivation is the diagnostic center: “Why are you doing this?” A founder who noticed AI was fashionable after graduation differs from someone whose history leads naturally to the problem. Pujara argues that raising $5 million–$10 million has made startup formation a relatively safe career path for technically connected people.
Reference work tests specific suspicions rather than checking a box. If a compelling founder seems careless with detail or too excitable, Pujara finds people positioned to examine that trait. The desired founder should have left a clear impression—positive or negative—on almost everyone who worked closely with them.
5. Concentration forces conviction but raises the cost of being wrong
José discloses that Delphi is an LP in Valhalla’s second fund. Fund I began with a plan for 30–40 companies, was revised to 20, and ended with roughly 20; Pujara’s concentration model is only two to four exceptional opportunities per year.
With an $80 million–$100 million vehicle, Valhalla can lead a seed round with a $10 million check. It does not maintain systematic reserves for every Series A or B; Pujara instead wants the freedom to identify “our K2 Space,” then direct 20%–30% of the fund toward that evident return-driver.
José describes concentration as a “forced-conviction function,” but presents Michael Dempsey’s opposing arithmetic: about 30 checks may be required to include one or two major winners. A ten-company first-time fund can simply miss every outlier, leaving no engine for returns.
Pujara says selective follow-ons can be done in several ways, including the SPVs José raises, but does not call them reserves: his funds do not maintain reserves during the operating period. José warns against automatic doubling after six months of momentum, since private marks can rise vertically before a company goes to zero or is sold as preferred stock; his hypothetical obvious case is discovering the next Elon Musk.
6. Valhalla stays generalist while searching for future monopolies
Valhalla’s 2021 website emphasized digital assets, metaverse games, and psychedelic therapy. Pujara says he met the Valhalla partners at 20 and eventually formed a partnership with them in 2020; he spent roughly 2020 through late 2022 observing, building relationships, and developing judgment before gaining their trust to devote more attention to physical technology.
His reasoning preceded ChatGPT: software looked likely to commoditize because nearly every smart young person he knew studied software engineering, while mechanical, electrical, and aerospace engineering were neglected outside SpaceX. By 2023–2025 Valhalla made several physical-technology bets—but Pujara now thinks that field itself is becoming consensus.
That evolution made him reject sector boxes. LPs prefer legible mandates because they simplify allocation, yet Pujara wants carry rather than a management-fee business; being forced to buy defense during “the hottest defense market in history” would sacrifice the flexibility required to outperform.
His model is TCI, which he describes as Chris Horn with perhaps three or four other members or analysts managing nearly $100 billion across roughly nine to 12 public monopolies. Its task is simply to decide whether each moat endures. Valhalla’s translation is to find future monopolies at seed, support them with conviction, and hold them for the long term.
7. K2 Space inverted the small-satellite consensus
K2 was not raising when Pujara visited its facility. After several hours with the team, observing its ability to recruit strong SpaceX talent and checking the ecosystem, he asked to invest; the founders considered it for roughly a day and accepted.
The thesis began with a mismatch: Starship and broader launch capacity promised rapidly increasing orbital mass and power, while venture-backed companies kept imposing tighter small-satellite constraints. Pujara saw that pattern-matching Planet Labs and Starlink ignored Starlink’s vertically integrated launch advantage and the limited economics available to imitators.
K2 instead built much larger, more powerful satellites for a five-to-ten-year future in which launch constraints loosen and customers demand greater mass and power. Pujara says it still lacks a real competitor three and a half years later, has signed a deal worth more than $1 billion, and is raising at a $6.8 billion valuation.
8. Jaza proved that a hated market can conceal working economics
Corey from Fundomo introduced Pujara to Jaza; Rohan believes Corey was an angel investor. Founder Jeff’s path—growing up without affluence in northern Canada, forging his own route, operating in Africa, and eventually confronting household electrification—immediately marked him as unusually energetic, serious, and relentless.
More than one billion people in sub-Saharan Africa lacked home electricity, yet Jaza’s answer required years of iteration, beginning around motorcycle batteries. Between 2017 and 2023 it navigated governments, local politics, violence, communication barriers, and other execution hazards before discovering a small formula that actually worked.
José framed Africa as a venture “graveyard”; the nine-month diligence reflected that history. Valhalla interviewed investors in similar failed businesses and repeatedly tested whether it had missed a fatal flaw. It concluded that others’ losses explained the aversion better than Jaza’s economics; Jaza subsequently raised $100 million and, Pujara says, grew roughly tenfold year over year.
Fund I’s failures sharpened the hierarchy. Attractive markets paired with founders rated seven or eight out of ten generally returned little; now differentiation earns the meeting, an exceptional founder earns the work, and a “20 out of 10” founder may justify tolerating more business uncertainty—especially at a $10 million rather than $100 million post-money valuation.
9. Technical underwriting needs a bounded possibility test, not omniscience
José presses Pujara on whether a non-engineer outside frontier labs risks buying technically indistinguishable “call options.” Pujara concedes the concern—it contributed to passing on Oliks[?]—but argues that investors can distinguish a plausible engineering program from open-ended scientific experimentation without understanding every nuance ten layers down.
Aftersort[?] cleared that bar because Pujara saw a real LLM gap and a rational, principled approach to closing it. He did not need other VCs’ approval: the combination of a missing capability, a reasoned solution, and an exceptional thinker made the bet acceptable.
Truffle’s thesis is that token demand will eventually exceed feasible AI infrastructure investment. Pujara expects the constraint to become visible around the beginning of 2027, or 2028 in the worst case, against consensus forecasts of $4 trillion–$5 trillion of AI capex in 2028; power, supply chains, and centralized inference costs become the bottleneck.
Srikanth’s analogy is the migration from mainframes and terminals to personal computers: Pujara expects people eventually to have personal computing devices, potentially with large local memory, a dedicated operating system, and continuous learning. Truffle has its own device and custom weights; as Instinct and Muse degrade under costly 24/7 frontier inference, its three-year supply-chain lead makes it “probably the perfect Valhalla investment.”
10. Personal downside tolerance and aligned incentives complete the strategy
Pujara grew up in a low-income household supported financially by his mother, moved seven or eight times, and always knew his parents’ bank balances. Repeatedly entering new cities without social context trained him to adapt, while early scarcity made earning money a practical concern rather than an abstraction.
Leveraged crypto trading later wiped him out multiple times. At college he reached $0, took a food-delivery job, and learned that embarrassment mattered less than eating; the durable lesson was “Don’t gamble,” alongside the realization that a satisfying life requires far less money than status-protection implies.
Work became his social world because it connected him with the first people he deeply admired. He describes founders and investors as friends, talks with portfolio founders nearly every day, and wants a life built around people who “energize you” and “ignite your ambition.”
Over five to ten years, he wants Valhalla to recruit similarly independent investors and pursue new private-market alpha. His diagnosis is that institutional LP structures reward AUM, management fees, and not looking bad more than performance; the antidote is personal capital at risk throughout the chain. Valhalla says it has funded at least 50% of the fund with its own money. “If you truly understand incentives, you can understand how the world works very quickly.”