The Twenty Minute VCJason Lemkin: Cold Email Tips; Why Only 15% of Founders Listen to their VCs | 20VC #954
CHAPTERS
- 0:00 – 0:49
7 years later: building media brands takes time
Harry and Jason open by reflecting on how long “overnight success” really takes, using 20VC’s growth as the example. They riff on audience engagement mechanics (including Harry’s hat) and set the stage for an Algolia-focused conversation.
- •Reconnecting after seven years and what’s changed
- •"Overnight success" is usually a long grind
- •Light discussion of audience/engagement tactics
- •Framing the episode around the Algolia investment story
- 0:49 – 1:40
Why Lemkin only invests in inbound “SaaStr superfans”
Jason explains his unusual sourcing strategy: he largely avoids outbound and warm intros and instead relies on high-velocity inbound from founders who already know him and SaaStr. He argues this approach increases signal and fit, while admitting it can miss outliers.
- •Outbound deal-chasing hasn’t worked for him historically
- •Inbound from SaaStr fans as a filter for alignment and intent
- •Warm referrals and generic emails often fail to convert
- •Acknowledges the strategy has blind spots (missing Monday.com)
- 1:40 – 4:37
Cold inbound email that converts: what “breakthrough” looks like
Jason breaks down what makes a cold email high-signal—dense, specific metrics and crisp narrative—while noting top investors each prefer different formats. The throughline is that exceptional founders communicate clearly and credibly from the first touch.
- •Jason’s preferred format: detailed traction + story + why they win
- •Examples of metrics that matter (MRR, MoM growth, NRR, customers)
- •Different investor preferences: two lines vs long deck vs detailed email
- •Rules and playbooks vary—beware overgeneralizing advice
- 4:37 – 6:14
Algolia’s inbound and the first meeting: falling in love with the problem
They rewind to 2014: Algolia reached out after YC, the round was already full, and Jason almost missed the email. Once he met the team, his lived pain with search infrastructure made him immediately want to buy as much of the round as possible.
- •Context: 2014, Jason’s second venture investment (post-Pipedrive)
- •Algolia as Search-as-a-Service API
- •Founder-market fit: Jason’s prior Lucene/search downtime pain
- •Email triage miss, last-minute meeting before founders returned to France
- 6:14 – 9:28
Allocations, valuation sensitivity, and learning to “lose money” in venture
Jason shares the seed terms (500K at 12M pre) and why he underbought due to early-career valuation sensitivity. He describes the psychological shift required to accept losses in venture once you internalize that a few big winners outweigh many 0–1x outcomes.
- •How a “full” YC round gets re-allocated in practice
- •Seed check details and the alternative (1M at 15M) he declined
- •Early mistake: optimizing for not losing money vs maximizing ownership
- •Perspective shift: you must learn to tolerate losses in a power-law business
- 9:28 – 12:58
Ownership targets, adverse selection fears, and why founders “pick you”
Jason explains why he now prefers 10%+ ownership and wants at least one deal per batch where he can own 20%+ as a solo GP. He argues adverse selection is less relevant when exceptional founders have options and still choose you for a reason—alignment, trust, or insight.
- •Today’s bar: hard to take sub-10% positions seriously
- •Portfolio construction goals: occasional 20%+ ownership to “play to win”
- •Adverse selection reframed: great founders still have multiple options
- •Filter: founders must genuinely want the relationship (SaaStr affinity as proxy)
- 12:58 – 16:21
Bet on what you know: investing from operator pain points
Jason outlines how his best investments map directly to the headaches he had as a SaaS CEO (search, contact center, CRM, outbound). He contrasts this with areas he didn’t feel personally (e.g., payroll), which made it harder to spot why those markets could explode.
- •Operator pain as an investing edge (search → Algolia)
- •Contact center pain → Talkdesk, Front, Gorgias, MaestroQA
- •CRM pain → Pipedrive; outbound cadence pain → SalesLoft
- •Blind spots happen when you didn’t live the problem (e.g., payroll)
- 16:21 – 18:52
Retaining “plasticity” as a VC: inevitable decay and how to counter it
Harry asks how VCs stay close to current operator reality; Jason argues decay is real and mostly permanent. He suggests curiosity helps, teams can keep you fresh, and running an operating business/community (like SaaStr) can partially preserve modern pain-point awareness.
- •Claim: VCs naturally age out of frontline operator context
- •Curiosity matters but doesn’t fully solve the problem
- •One mitigation: build a team closer to the market and operators
- •Another mitigation: keep operating (SaaStr as real-time feedback loop)
- 18:52 – 21:04
Advice for operators turned VCs: move fast and back CEOs better than you
Jason advises new investor-operators to ignore “slow down” guidance—especially inside large funds with different incentives. He emphasizes investing heavily in domains you deeply understand and only backing CEOs who are clearly better than you, because competition and iteration will expose weaknesses.
- •Large fund incentives differ: they only need you to find one winner
- •New investors should build a track record quickly (do more good deals early)
- •Non-negotiable: invest in founders/CEOs better than you
- •If founders aren’t better, product advantage erodes against competition
- 21:04 – 28:40
Competition, open source, and avoiding lazy VC heuristics
They discuss competing against “free” (open source) and why early traction in that context is unusually strong signal. Jason critiques common pitch-deck mistakes like throwaway 2x2 matrices and advocates for a nuanced, respectful, data-driven view of competitors.
- •Open-source competition is hard for founders but clarifying for investors
- •Early traction vs free implies a 10x wedge in a specific segment
- •Don’t use throwaway 2x2 competition slides; choose the right format
- •Best founders respect competitors and explain honest tradeoffs (Algolia vs Elastic)
- 28:40 – 32:16
Speed, iteration, and when companies get “smoked” by competitors
Jason explains that companies often lose because they iterate slower—small differences in shipping compound massively over time. He argues speed matters even pre-PMF because you need reps and iterations before runway runs out, despite myths about long “crafting” cycles.
- •Competitive advantage compounds through faster shipping cadence
- •“Mediocre teams” freeze while great teams ship relentlessly
- •Pre-PMF speed still matters: more tests, more iterations, faster learning
- •Launching too late can burn runway and eliminate iteration opportunities
- 32:16 – 35:21
Zombies and the post-bull-market hangover: too much money, too little urgency
They discuss heavily funded, pre-PMF companies and Jason’s concern about “zombie” SaaS—long runway with stalled growth and declining urgency. Harry notes a new pattern of later-stage investors offering founders secondary to return capital and end non-working experiments early.
- •Overfunding can create complacency and delay hard decisions
- •VCs may ignore zombies while focusing on bigger portfolio fires
- •Capital recycling: returning money + founder secondary as alignment tool
- •Founder psychology: many resist shutting down even when economics suggest it
- 35:21 – 38:12
TAM skepticism: Algolia’s ‘$2M market’ and why early hypergrowth proves size
Jason recounts that at the time, the measurable market for paid search APIs looked tiny—around $2M in revenue across competitors. He argues that sustained early hypergrowth is itself evidence of a much larger eventual TAM as technology remakes categories.
- •At the time, observable TAM looked absurdly small
- •“Dumb math”: growth rate made a $2M TAM impossible over time
- •Hypergrowth in early days is strong proof of real market depth
- •Categories expand as new technology changes what’s possible (eSignature analogy)
- 38:12 – 42:50
Why hypergrowth plateaus: management team timing and scaling inflection points
Jason says every major winner he’s seen has had at least one plateau year. The core driver is usually management-team evolution—either hiring too late or missing on key executives—because each failed VP hire can cost a year and stall expansion into new TAM or products.
- •Plateaus are common even in unicorn trajectories
- •Primary cause: sticking with 1.0 management too long or hiring too late
- •Late exec hiring reduces “second chances” if early leaders don’t work out
- •Underlying needs (upmarket, second product) are solved by great teams
- 42:50 – 47:16
Founders, boards, and truth-telling: why only ~15% really listen
Jason and Harry debate direct feedback vs sugarcoating in board dynamics. Jason claims only a minority of founders can truly absorb hard feedback; most resent the messenger, which is why many board members stay silent despite fiduciary responsibility.
- •Board/CEO relationship is nuanced; feedback timing matters
- •Jason’s estimate: ~15% can take feedback, many tolerate or resent it
- •Direct “ass-kicking” advice can permanently damage relationships
- •Tradeoff: honesty now vs coaching founders to reach conclusions themselves
- 47:16 – 51:53
Partnership decisions, conviction, and why VC partnerships break after two
Jason describes pushing Algolia through internal skepticism, contrasting it with later unanimous decisions like Talkdesk. He argues “conviction” can mask sloppy thinking, and suggests most partnerships become dysfunctional beyond two people—though he personally believes he’d invest better with a true co-founder.
- •Algolia was an internal ‘no’ while Talkdesk was immediate ‘yes’
- •Conviction is double-edged: necessary but can justify weak reasoning
- •Partnership structure critique: >2 partners often lose true partnership benefits
- •Personal reflection: he would be a better investor with a real co-founder
- 51:53 – 1:00:00
LP markets, brand power, and the mistakes of the bull market
They examine whether LPs will churn away from venture; Jason expects manager churn but continued asset-class commitment among established institutions. They discuss how LPs often focus on returns over narrative, why 3x net is exceptional, and how bull-market expectations distorted reality.
- •Prediction: managers get dropped, but LPs stay in venture as an asset class
- •LP diligence often reduces to performance and category allocation
- •3x net returns are rare and still beat most asset classes
- •Bull-market era inflated expectations (everyone claiming 8–10x funds)
- 1:00:00 – 1:03:41
In-person meetings in a Zoom world: trust vs transactional investing
Harry asks about meeting founders face-to-face; Jason says he hasn’t solved it and feels he’s a worse investor without in-person first meetings. He argues the key lost ingredient is trust-building—not magical founder ‘reads’—and worries investing has become overly transactional.
- •First in-person meetings have largely disappeared post-2020
- •Jason feels reduced edge and higher risk without face-to-face time
- •Value of in-person: relationship and trust more than character detection
- •Acknowledges counterexamples (Point Nine) but sees trust as central
- 1:03:41 – 1:12:29
Being replaced, evolving platforms, and why brands endure in venture
They talk candidly about aging in public relevance and the rise of new creators and platforms. Jason argues brands remain a durable advantage in venture if actively nurtured, even as channels shift from blogs/Quora to TikTok and beyond.
- •Fear of replacement as new media-native voices emerge
- •Founders gravitate to loud brands; brand influences deal access
- •Platforms change: Quora’s decline, TikTok’s rise, channel adaptation required
- •Strong brands can keep sourcing 1–2 great deals per year for a decade
- 1:12:29 – 1:16:11
Rapid-fire Algolia reflections: pre-mortem, underrated supporter, hardest moment, future
In closing quick-fire, Jason says startups mostly die only when founders stop pushing. He highlights Salesforce Ventures’ Alex Kile as an underrated champion, points to a failed late-built management team as the hardest period, and predicts Algolia’s future will track the evolving nature of search—especially across e-commerce and SaaS tailwinds.
- •No formal pre-mortems; momentum makes B2B hard to kill unless founders quit
- •Expected early outcomes were much smaller in the 2014 market context
- •Underrated contributor: Alex Kile (Salesforce Ventures)
- •Hardest period: late management-team build that nearly derailed execution
- •10-year view: search evolves unpredictably; strong vertical tailwinds remain
