The Twenty Minute VCFigma’s IPO: The Full Breakdown & Why Melio’s $2.5BN Acquisition is “Discouraging”
CHAPTERS
- 0:27 – 3:27
Figma’s S-1 highlights: rule of 80 growth, cash-rich balance sheet, and IPO valuation range
The group reacts to Figma’s S-1, focusing on 46% growth, strong profitability, and $1.5B cash with no debt. They debate where the IPO could price (roughly $20B–$30B) and how expensive the multiple looks relative to other enterprise leaders.
- •Figma’s reported metrics: ~$821M revenue, ~46% YoY growth, ~$1.5B cash, no debt
- •40%+ free cash flow margins and operating income positivity imply a “rule of 80” profile
- •Discussion of likely IPO valuation bands and whether Figma needs to “leave money on the table”
- •Comparison to public enterprise comps (e.g., ServiceNow valuation vs 20x revenue)
- 3:27 – 3:54
Adobe’s failed acquisition: why paying “two years ahead” can still be right
They revisit Adobe’s attempted Figma acquisition and argue the price may have been justified in hindsight. The conversation explores the strategic logic of paying up for a category-defining asset and the downside of letting a market-expanding platform slip away.
- •In retrospect, the $20B price looks less like 2021 excess and more like strategic foresight
- •Big winners can justify paying ahead of the curve if synergies and market expansion are real
- •Figma’s developer reach broadens Adobe’s footprint beyond traditional design buyers
- •Post-deal-crater narrative (“Adobe moved on to genAI”) vs. Figma as a core strategic plank
- 3:54 – 7:11
What should Adobe buy next? Big-deal M&A lessons from Salesforce and the ‘Canva’ question
Prompted to name what Adobe should buy today, the discussion shifts to how great acquirers approach large-scale M&A. Jason references Salesforce’s playbook—buying meaningful revenue and scaling it—then floats Canva as the obvious, if imperfect, example.
- •Salesforce corp dev lesson: be great at buying large revenue bases and growing them (MuleSoft, Slack)
- •Argument for focusing on fewer, bigger, synergistic acquisitions vs. ‘screwing around’ on small deals
- •Adobe’s scale: a $1B+ revenue acquisition materially moves the needle
- •Canva raised as a plausible (though “obvious”) target
- 7:11 – 14:17
The ‘orphaned company’ problem: when your VC champion leaves and reserves become political
They draw parallels between acquisition sponsorship risk and venture board dynamics when a partner moves on. The group debates how reserve decisions should be made, whether separating reserve authority reduces bias, and why companies suffer when they lose an internal advocate.
- •Companies can become ‘orphans’ when a partner/board champion departs
- •You need someone “in the room where money is allocated” to defend reserves
- •Pros/cons of having a separate partner or committee decide reserves to reduce bailout bias
- •Incentive misalignment: junior partners may over-support marginal companies to protect their track record
- 14:17 – 19:01
Pay-to-play and troubled financings: usually bad, occasionally legendary
Harry asks whether pay-to-play structures ever work out; Rory argues they’re generally a sign you’re already in trouble. They cite rare exceptions (e.g., a pivotal down round) while emphasizing that most such situations are about salvaging outcomes rather than hitting home runs.
- •Rule of thumb: when you’re deep in legal terms, odds of a great outcome drop sharply
- •Pay-to-play tends to reduce home-run probability; it’s often about avoiding a total wipeout
- •Historical example: FedEx down round as a rare case of huge upside at the tipping point
- •Opportunity cost isn’t just capital—it’s partner time and distraction
- 19:01 – 24:17
Liquidity returns and ‘fewer, bigger winners’: Index, Scale, DPI, and why venture may ‘rip’
They discuss how a small number of outsized outcomes can drive enormous LP liquidity, citing Index’s potential ~$3.5B back from just two major deals. The conversation frames venture as increasingly concentrated: fewer IPOs, but much larger companies at exit.
- •Index’s concentrated liquidity: massive distributions from a couple of standout deals
- •Structural shift: longer private holding periods lead to bigger companies at IPO/exit
- •Implications for fund size debates and why 10-years-ago outcome expectations were smaller
- •Core truth: venture is great only if you’re in the winners—selection is everything
- 24:17 – 33:08
Melio’s $2.5B sale: ‘discouraging’ multiples, late-stage pricing illusions, and pref-stack dynamics
The group breaks down why Melio sold for $2.5B despite reported strong ARR and growth, with Jason calling the valuation discouraging for M&A expectations. They explore how 2021 late-stage marks distort perceptions, why 1x preference outcomes change board incentives, and how founders can feel ‘liberated’ when late-stage investors just want their money back.
- •Debate on Melio’s reported metrics (ARR/revenue and very high trailing growth) vs. sustainable forward growth
- •Outcome multiple discussion (roughly low-teens revenue multiple) and what it implies for broader M&A
- •Late-stage ‘rigged game’ framing: 1x outcomes on losers can still protect late-stage IRR
- •Preference stack dynamics create misaligned incentives between late vs early investors and founders
- 33:08 – 35:42
Secondaries and ‘foie gras’ rounds: when growth investors stuff the cap table and everyone gets weird
They move from Melio into founder secondaries and the mechanics of co-sell rights. The group argues that founders taking money off the table can be rational—especially when investors are forcing huge checks—but notes smaller investors often get squeezed or waived out of selling.
- •Founder secondaries can be rational when driven by oversized growth rounds (the ‘foie gras’ effect)
- •Co-sell rights exist but can be limited or waived by larger investors
- •Tension between fairness to founders and providing proportional liquidity to earlier/smaller investors
- •Late-stage capital can distort governance and create resentment when outcomes reverse
- 35:42 – 37:59
Big money and the death of focus: do $100M packages demotivate AI talent?
The conversation turns to incentives and whether massive compensation leads to complacency—especially for AI researchers. Rory argues money reveals priorities more than it changes people, while warning that internal inequity and disruption may be the bigger risk than individual motivation.
- •Question: do huge pay packages reduce efficiency and focus for founders/researchers?
- •Rory’s view: money reveals what people truly want; demotivation isn’t universal but is a real risk
- •Greater danger may be internal disruption from unequal compensation across teams
- •Examples of big-tech ‘making it work’ with highly paid leaders for long enough to be worth it
- 37:59 – 40:13
AI CapEx reality check: $300–$400B per year, ‘economically rational’ vs game-theory rational
Rory challenges whether today’s AI investment wave will produce near-term ROI, given unprecedented CapEx and operating cost burdens. They distinguish between positive-NPV rationality and ‘must-attend’ strategic spending to avoid missing the platform shift.
- •AI spend magnitude: ~$300–$400B/year in CapEx plus massive talent costs
- •Uncertainty on near-term ROI vs long-term inevitability of AI value creation
- •Two rationalities: positive NPV vs strategic/game-theory spending to stay relevant
- •AI spending flips ‘dream businesses’ into cash-incineration machines (Buffett lens)
- 40:13 – 42:55
Selling the future to LPs: Menlo’s new fund, Chime proof points, and the Anthropic narrative
Harry asks whether LPs are more persuaded by realized legacy wins or by a forward-looking AI story. Rory argues great managers need both: hard returns (e.g., Chime) plus credible positioning and ownership in frontier AI (e.g., Anthropic).
- •Menlo’s fundraising success: combining realized outcomes with an AI-forward narrative
- •LP persuasion comes from both proof (cash-on-cash winners) and credible future access
- •LPs increasingly understand fund math and the outcome sizes required to return large vehicles
- •“You win, you get the prize”: capital flows to managers perceived as consistently in the right deals
- 42:55 – 46:46
Couchbase PE buyout: isolated ‘rifle-shot’ or the start of SaaS zombie clean-up?
They debate whether Couchbase’s acquisition signals a broader return of PE liquidity for sub-scale public SaaS. Rory frames it as a specific thematic bet by an experienced buyer rather than a general market reopening for slow-growing infrastructure names.
- •Couchbase deal viewed as thematic/strategic rather than representative of a broad PE trend
- •Skepticism that every ~$200M revenue, low-growth infra company will be ‘hoovered up’
- •Many venture portfolios contain sub-scale companies; PE is unlikely to ‘save everyone’
- •Technical infrastructure assets can be complex and don’t always fit classic PE playbooks
- 46:46 – 51:52
Roll-ups and price-clearing: Constellation/Visma models vs the reality of 2x revenue bids
The discussion broadens to roll-up strategies as a potential endpoint for ‘SaaS zombies’ that can’t IPO. They note that roll-up buyers often demand low multiples (e.g., ~2x revenue), creating a stubborn gap between what sellers will accept and what disciplined buyers will pay.
- •Roll-ups can create public-market-scale entities from many sub-scale software assets
- •Constellation/Visma cited as archetypes—valuable at scale even if individual assets stagnate
- •Key friction: buyers want ~2x; sellers may only come down to ~5–6x, delaying clearing
- •“Price clears all markets,” but AI-driven disruption may make many assets feel ‘hopeless’
- 51:52 – 58:52
AI urgency doctrine: if AI didn’t re-accelerate you by June 30, you’re ‘already dead’
Jason lays out a hard line: AI must drive real growth acceleration, not just features. They argue that markets are net-zero with budget shifting between vendors, so companies that fail to replatform quickly lose relevance versus AI-native challengers.
- •Strong claim: if AI hasn’t produced growth acceleration, the company is failing competitively
- •AI-native startups enjoy structural GTM/product advantages vs ‘layering AI on top’
- •Example of successful reinvention: Vlex becoming AI-relevant and getting acquired by Clio
- •Relative market share dynamics: if you aren’t accelerating, competitors are taking your budget
- 58:52 – 1:05:34
Oracle’s $30B AI deal and the data-labeling war: Scale’s ‘empty husk’ and Surge/Macaw rising
They use Oracle’s OpenAI deal as proof incumbents can move decisively into AI economics. The conversation then shifts to Scale’s situation post-acquisition and how demand reallocates to competitors like Surge, fueling a new competitive phase in AI data services.
- •Oracle’s AI pivot: redirecting cash flow into GPUs and landing a massive OpenAI contract
- •Incumbents can become ‘AI-native-ish,’ raising the bar for startups to move fast
- •Scale aftermath: loss of trust/neutrality drives customer and talent reallocation
- •Surge emerges as a huge, low-profile competitor; data quality becomes a battleground
- 1:05:34 – 1:12:15
Founder/CEO exits and ‘winner-take-most’ pressure: leadership turnover, burnout, and mercenary moves
They close the main discussion on rising CEO resignations and founder exhaustion as startup timelines stretch to 12+ years. The group links extreme outcome concentration to more job-hopping and higher risk-taking on entry prices, especially in early-stage investing.
- •Founder fatigue rises when a ‘4–6 year journey’ becomes 12–13+ years
- •Record CEO departures reflect stress, changing incentives, and accelerating turnover
- •Winner-take-most dynamics increase the opportunity cost of missing the very top deals
- •Early-stage pricing inflates as investors pay up to avoid missing rare mega-winners
- 1:12:15 – 1:15:39
Kalshi quick-fire: Elon party odds and whether an AI founder becomes a billionaire by 2029
In a rapid-fire segment, they place bets on whether Elon will create a political party and debate a founder’s chances of becoming a paper billionaire by 2029. The discussion quickly becomes a valuation math exercise about ownership, multiples, and AI hype risk.
- •Elon political party: skepticism it happens (and some indifference)
- •Billionaire-by-2029 question framed as valuation and ownership math
- •Acknowledgment that AI revenue claims and multiples can be inflated/uncertain
- •Consensus drifts toward ‘yes’ given current AI market behavior and pricing
