The Twenty Minute VC20VC Exclusive: Mercury Founder Launches First $26M Fund with Immad Akhund
CHAPTERS
- 0:23 – 1:50
$26M debut fund: why now and who’s partnering
Immad announces the close of his first institutional fund: $26M raised with partner Yash Doshi (early Mercury investor, ex-EQT Ventures). He explains the shift from AngelList rolling funds and notes the fund is already deploying into several companies.
- •Closed a $26M first institutional fund
- •Partnering with Yash Doshi (ex-EQT Ventures, Mercury investor)
- •Background: ~350 angel investments since 2016
- •Previously invested primarily via AngelList/rolling fund
- •Fund is already active with initial investments
- 1:50 – 6:03
Lessons from 350 angel checks: ego, founder autonomy, and real ‘value-add’
Immad shares that new investors often over-insert their own ideas, which can derail founders and distort decision-making. The best investor role is supportive and available, not directive—founders should run their own playbook while investors provide occasional leverage.
- •Early mistake: pushing your own ideas onto founders
- •A founder agreeing too easily isn’t always a red flag—context matters
- •Best founders don’t ‘need’ you, but may value targeted help
- •Investor value-add works best as on-demand advice, not constant involvement
- •Learning from early hit: Rappi scaled fast without needing investor time
- 6:03 – 7:27
What actually matters from VC firms: partner quality and founder networks
The conversation turns to whether VC platforms are meaningful or just fee justification. Immad argues the individual partner relationship is the biggest determinant of value, followed by the network effects of a firm’s founder community and events.
- •VC ‘platforms’ can be hit-or-miss depending on company needs
- •The specific partner is the primary source of value
- •Long-term, high-frequency partner conversations compound
- •Portfolio founder networks and curated events can be genuinely useful
- •Choosing investors is largely choosing who you’ll talk to for years
- 7:27 – 10:15
How Sequoia came in: diligence intensity, conviction signals, and pricing realities
Immad recounts Sequoia’s process and why it felt needle-moving personally and professionally. He highlights that top firms often do the deepest diligence, build conviction early, and can match or beat price—though the relationship and long-term alignment matter more than squeezing valuation.
- •Sequoia as a brand can be a ‘needle-moving’ milestone
- •They conducted the most customer and data-room diligence
- •Lead partner conviction can form early even if process is long
- •Partnership meetings reflect work already done—not a single person’s call
- •Top firms often match/beat price; decision isn’t purely valuation-driven
- 10:15 – 12:51
Contrarian take on high valuations: raise enough, then don’t spend it
Discussing Mercury’s 2021 environment, Immad defends taking very high multiples—if the company raises sufficient capital and maintains discipline. The real failure mode is raising big at high prices and then burning it, often encouraged by VC incentives toward outlier outcomes.
- •Mercury Series B: 120x revenue and $120M raised
- •He’d do the high valuation again given the context
- •Core mistake to avoid: not raising enough at the high valuation
- •Second discipline: resist the urge to spend just because you raised
- •VC incentives can push spending in pursuit of outlier returns
- 12:51 – 17:25
Biggest angel wins and what they teach: Truebill, repeat founders, and timing
Immad names Truebill as his biggest realized win and attributes it largely to exceptional repeat founders in a hard market. He also emphasizes timing—founders who exit at the right moment can dramatically alter outcomes, and investors often underutilize secondaries when markets peak.
- •Truebill pre-seed investment and $1.25B exit
- •>30x return over ~2016–2021
- •Repeat founders excel in brutally competitive categories
- •Timing matters: December 2021 exit was exceptionally well-timed
- •Secondaries can be valuable but are hard to manage as an active CEO
- 17:25 – 21:38
Misses and biases: underestimating young founders + practical angel advice
Immad describes passing on Scale AI due to founder youth, learning that raw potential and speed of learning can overwhelm experience-based skepticism. He advises angels to diversify meaningfully (20–30+ bets) because outcomes are power-law driven and increasingly require decacorn-level winners at today’s entry prices.
- •Biggest miss: Scale AI—dismissed due to founder age
- •Lesson: youth can be an advantage; suspend disbelief appropriately
- •Angel investing requires enough shots on goal to learn and win
- •Diversification matters because seed is power-law and dilution is real
- •With higher entry prices, unicorns may be insufficient—need decacorns for fund-level outcomes
- 21:38 – 25:59
Secondaries, ‘go long,’ and revenue quality in the AI era
They debate when to take cash off the table and what makes revenue durable today. Immad is skeptical of “labor replacement” AI revenue due to rapid commoditization and margin compression, while seeing stronger stickiness where tools become entrenched workflows (e.g., developer tools).
- •Selective secondary selling can make sense during frothy rounds
- •Preference to hold long-term compounders when upside is massive
- •Skepticism of AI ‘labor replacement’ pricing—competition compresses margins
- •Most AI apps share similar foundation model inputs, limiting moats early
- •Durable revenue comes from workflow entrenchment and high switching friction over time
- 25:59 – 28:13
AI moats and org impact: the ‘flashlight apps’ phase and engineering headcount
Immad argues the market is still in a churn-heavy early phase where tools rapidly rotate, but defensibility will re-emerge through brand, consolidation, multi-product bundling, and enterprise relationships. On hiring, he expects more engineers over time because productivity gains expand ambition and scope rather than shrink teams.
- •Current AI landscape is unstable with high churn between tools
- •Defensibility likely returns via brand, bundling, and enterprise distribution
- •Cursor is the dominant internal tool mentioned
- •AI increases code output, but shipping and prioritization remain constraints
- •He expects engineering headcount to grow as ambition expands with productivity
- 28:13 – 32:58
Mercury strategy reflections: product timing, competition posture, and valuation narratives
Immad shares a key strategic regret: delaying Mercury’s credit card launch until 2022, giving competitors space to expand. He also outlines his philosophy of ignoring competitor-driven roadmaps and anchoring decisions in customer needs and long-term product vision, while noting markets value enterprise/payment narratives differently than banking.
- •Regret: waited too long to launch Mercury credit card
- •Mercury credit card is dominant among Mercury customers due to account visibility
- •Competition rarely matters as much as customer focus and execution
- •Rejects building features just because competitors did them
- •Banking is valued differently than enterprise SaaS/payments in markets
- 32:58 – 34:03
Why move from angel to VC: LP demand, deal-flow overload, and doing it ‘properly’
Immad explains the institutional fund was driven by inbound LP interest and the reality that his deal flow outgrew his capacity. Bringing on a partner enables better selection and process, addressing his concern that he was becoming a ‘bad angel’ by not being able to evaluate everything thoroughly.
- •Institutional LPs preferred a traditional fund vs AngelList structure
- •Deal flow surged as Mercury became ubiquitous among startups
- •Capacity constraint: couldn’t review everything thoughtfully
- •Wanted a full-time partner to professionalize selection and process
- •Goal: improve quality without pretending to be a lead investor everywhere
- 34:03 – 38:31
Fund construction: 60-company portfolio, $150k non-lead checks, reserves vs SPVs
They get specific on the $26M strategy: diversified, mostly non-lead participation with typical $150k checks and selective higher-conviction positions. Harry pushes an SPV-heavy approach; Immad prefers selective reserves and dislikes FOMO-driven SPVs, arguing you can often recognize trajectory earlier as an insider.
- •Targeting ~60 companies with mostly non-lead checks
- •Typical check size ~150k; occasional ~$1M conviction checks
- •Selective reserves rather than automatic pro-rata for every company
- •Debate: SPVs (flexibility, deal-by-deal carry) vs reserves (intentional follow-on)
- •View: founders may dislike SPVs; reserves allow reassessment after progress signals
- 38:31 – 41:19
AI investing: ‘overhyped at seed’ and what qualifies as investable
Immad says seed-stage AI is crowded, repetitive, and often priced too high, making the math difficult. He still invests selectively when founders bring deep domain expertise with a non-generic application, or when traction is unmistakably real despite valuation.
- •Seed AI often repeats the same ideas with inflated valuations
- •Hard to avoid AI entirely, but selection bar must be higher
- •Best AI bets: domain-expert/second-time founders applying AI specifically
- •Alternative: undeniable traction/‘rocket ship’ signals justify pricing
- •Looks to less-hyped areas (fintech, space/hard tech) for better entry dynamics
- 41:19 – 46:23
Space tech as a ‘less crowded’ frontier: markets, learning strategy, and seed pricing
Immad explains how he approaches unfamiliar categories by making a few early investments to learn through founder conversations. He outlines three main current space markets—launch, imagery, and communications—arguing seed valuations can be surprisingly reasonable compared to hot AI SaaS despite later capital intensity.
- •Learning approach: invest small early to build understanding fast
- •Space markets: rockets/launch, earth imagery, communications
- •Space is more ‘repeatable’ now due to launch reliability improvements
- •Examples cited: Momentus (early), Stoke (reusable rockets), Albedo (high-res imagery)
- •Seed rounds can be attractively priced; later rounds become capital intensive
- 46:23 – 48:53
First-time fundraise realities: anchor LPs, LPA friction, and the ‘boring’ pitch loop
Immad describes fundraising as easier than expected due to track record, with major allocations secured quickly. The truly painful part was legal and administrative—negotiating the LPA across many parties—while the pitch process itself felt repetitive and less intellectually rewarding than company fundraising.
- •Core commitments secured in ~3 weeks
- •Largest LP check was $7.5M; anchor LPs included fund-of-funds
- •LP base: ~60% fund-of-funds; remainder entrepreneurs/GPs
- •Biggest pain: LPA negotiation and process drag (~1.5 months)
- •Fundraising felt less educational/fulfilling than startup fundraising
- 48:53 – 53:56
Founder-CEO running a fund: conflict concerns, transparency, and mutual flywheels
Harry challenges whether it’s appropriate for founders to manage LP capital while running a company. Immad argues it can work with transparency and alignment—especially for Mercury, where investing strengthened founder relationships that also fueled early customer acquisition and ongoing product insight.
- •Acknowledges the tension between CEO duties and LP obligations
- •Argues transparency upfront is critical: Mercury remains primary job
- •Mercury benefited directly from founder/investor relationships (early customers)
- •Investing helps Mercury via insight and network; Mercury helps investing via access
- •This model may not generalize to founders whose businesses don’t sell to startups
- 53:56 – 1:04:29
Future of venture + quick-fire reflections: IPO’ing mega-funds, public markets, and Mercury’s $100B case
Immad predicts more capital and potential IPOs for multi-stage VC platforms, with pressure on mid-sized firms caught between barbell extremes. In quick-fire, he shares evolving views on AI progress, highlights culture design as an early founder priority, reflects on over-raising in Mercury’s seed, and lays out a thesis for Mercury becoming a $100B company through integrated banking + financial software.
- •Prediction: some multi-stage VC firms may IPO; more capital flows into venture
- •Barbell outcome: small-check networks and mega-funds win; ‘middle’ struggles
- •Public markets are structurally unattractive: compliance burden + passive dominance
- •Quick-fire: increased belief in advanced AI arriving sooner; ChatGPT as daily tool
- •Mercury bull case: unify banking + financial tools into one integrated platform across huge markets
