All moonshots in this document are generated from publicly available information and research only. No proprietary information, internal challenges, or company-specific findings have been taken into account. These proposals would sharpen significantly with inside context.

Charlotte Schell // February 2026

Moonshots for
Lettuce

Seven hypotheses I'd test in the first 90 days, plus the one that makes them all possible. Each testable end-to-end with AI tools and a modest budget. Results, not ideas.

43.0M

Independent workers (US)

$30B

Uncaptured tax savings

$17M

Raised to win this market

What's already on the field

Table Stakes

Before proposing anything new, here's what Lettuce already ships and what's obviously coming. These are not moonshots. These are the cost of playing the game.

Already Shipped

  • S Corp formation + automated tax withholding
  • Real-time financial dashboard
  • Business banking + debit card
  • Expense management + invoicing (Stripe)
  • Payroll via Gusto
  • Tax preparation (1120-S, K1, individual)
  • Retirement via Carry partnership

Announced / Obvious Roadmap

  • Healthcare enrollment (Mar 2026, Besolo)
  • Dental, vision, accident insurance
  • Deeper AI tax advisor (LettuceHead)
  • More retirement options
  • Mobile app improvements
  • Website management, CRM, email
  • International contractor payments

The uncomfortable truth

The Moat Problem

Financial products are commodities. A dollar is a dollar. The moat has to come from higher conversion rates, lower cost of capital, or lower operating costs. All driven by proprietary data and distribution.

Lettuce sits on a dataset most fintech companies would kill for: every solopreneur's revenue, expenses, tax situation, growth trajectory, industry, pricing, and seasonal patterns. Today that data powers tax optimization. Tomorrow it could power much more.

If Lettuce stays a tax-and-accounting platform, LLMs will eat into its value proposition within 18 months. If Lettuce becomes the platform where solopreneurs grow their revenue, the data moat gets deeper with every user.

What LLMs Can vs. Cannot Replicate

Tax prep, bookkeeping, basic financial advice

IN THE BLAST RADIUS

Proprietary financial data from thousands of solopreneurs

DEFENSIBLE

Trust relationships built over years of handling money

DEFENSIBLE

Network effects between users

DEFENSIBLE

Source: a16z, "Bat Out of Hell: Identifying Your Durable Advantage in Fintech"

Seven hypotheses I'd test

The Moonshots

These are hypotheses, not conclusions. I'm working from public information only, without access to Lettuce's internal data, user behavior, or roadmap priorities. The sequencing below reflects some sample ideas to test. Click any card to expand.

Where the whitespace is

Underserved Segment Opportunity Map

Lettuce's current base likely skews toward tech freelancers, fractional executives, and management consultants. High income, digitally fluent, S Corp savings are obvious. But these are also the segments every competitor targets and where LLM-powered tax tools will hit first.

Below are segments I researched across two dimensions: how underserved they are by current fintech, and how big the opportunity is for Lettuce.

Tier 1: Go After Now

SegmentWorkersAvg RevenueSeasonalityScoreKey Insight
Real estate agents (1099)1.3M$56-101KHigh (Apr-Jun peak)8/10Commission-based income is perfectly suited for income smoothing. Nobody serves them well.
Skilled trades (electricians, plumbers, HVAC)120-150K$60-150KMedium8/10Essential services, resilient income, high S Corp savings. Completely ignored by fintech.
Independent healthcare (chiro, PT, acupuncture)~67K$70-120KMedium8/10Insurance billing complexity creates switching costs. Once on Lettuce, they stay.
Insurance agents & financial advisors (1099)~185K$70-120KMedium8/10Commission-based, multiple income streams, high willingness to pay.

Tier 2: Test With Vertical Landing Pages

SegmentWorkersAvg RevenueScoreKey Insight
Life/business/executive coaches232K+$50-150K+8/10Unregulated industry, no standard tools. Executive coaches at the high end are ideal.
Content creators (pro segment)~500K$48-89K8/10Huge market, bursty income. The pro segment earning $60K+ is underserved and growing fast.
Musicians & performers200-300K$25-75K8/10Extreme seasonality. Income smoothing would be transformative.
Personal trainers & fitness coaches350-400K$45-65K7.5/10Large segment but lower income. Top 30% earning $60K+ are viable.

The Seasonality Opportunity

Seasonality is the single biggest unsolved financial problem across almost every underserved segment. Nobody is building a product for it. Lettuce Income Smoothing (auto-reserving during peak months, distributing during troughs) would create massive switching costs and solve the #1 pain point.

SegmentPeakTroughRevenue Swing
Real estateApr-JunSep-Feb40-60%
TutorsSep-MayJun-Aug70-90%
MusiciansSummer, DecJan-Feb, Sep50-70%
PhotographersMay-Jun, Sep-OctJan-Feb40-60%
TrainersJan-MarJul-Aug, Nov-Dec30-50%
CreatorsJul, DecFeb-May30-50%

The long game

AI-Resistant Segments as a Defensive Play

Ramp's Economics Lab found that businesses are shifting spend from freelancers to AI at a striking rate: labor marketplace share fell from 0.66% to 0.14% between Q4 2021 and Q3 2025. The segments hit hardest are writing, graphic design, web development, and data entry. Task-based, digital, well-scoped work.

No industry will be completely AI-erosion-proof forever. But some segments are far slower to be disrupted, giving Lettuce longer longevity with those customers. Physical, relational, judgment-heavy work is harder to automate. And some of these aren't about AI inability at all — they're a future luxury. The wealthy will continue to pay for the human touch even when AI can technically do the job. Lettuce should prioritize both: the slow-to-automate and the premium-human-touch segments.

Highly AI-Resistant (Physical + Trust + Licensing)

SegmentWhy AI-ResistantGrowth OutlookFinancial Complexity
Healthcare practitioners (therapists, dietitians, nurses)Physical presence, licensing, trust+45.7% (nurse practitioners by 2032)Insurance billing complexity, continuing ed requirements
Skilled trades (electricians, plumbers, HVAC)Physical dexterity, unpredictable environmentsSteady, essential servicesEquipment depreciation, licensing, mixed payment methods
Personal fitness/wellness (trainers, yoga, massage)Physical touch, motivation, accountabilityGrowing post-pandemicIrregular income, cash-heavy, seasonal

Moderately AI-Resistant (High-Touch + Relationship)

Childcare/eldercare providers

Trust, physical care, emotional intelligence

Event planners/coordinators

Physical logistics, vendor relationships, real-time problem solving

Real estate agents/property managers

Physical showings, local knowledge, negotiation

Musicians/performers

Live performance, physical presence, emotional connection

Why this matters for Lettuce

These segments are growing (healthcare practitioners +45.7% by 2032). They won't be immune to AI forever, but they'll be the slowest to erode — giving Lettuce years of runway with these customers. They have the most complex financial needs (licensing, insurance, equipment depreciation). And they are the least served by current fintech. Collective, Bench, and Pilot all target tech and creative freelancers. AI actually helps these solopreneurs (scheduling, billing, marketing) without replacing their core work. And for the premium segments — executive coaches, high-end wellness, concierge healthcare — the human touch is a luxury their clients will keep paying for regardless of what AI can do. Building for both categories now means a long-term defensible customer base.

Where to start

How They Stack Up

Two views. First: which moonshots have the highest ROI potential. Second: how fast and cheap I can test them.

Important caveat: these rankings are hypotheses based on public research. I don't have access to Lettuce's actual user data, conversion metrics, or internal priorities. The sequencing reflects what I believe is testable today with a small user base and limited data, vs. what becomes possible as both grow.

ROI / Market Potential

Highest potential first. Score out of 100.

MicroloansMarketplaceIntl. ExpansionRevenue Bench.AI Client Acq.Vertical Exp.Referral Net.0255075100

Time + Budget to Test

Fastest and cheapest first. Weeks to first results.

Referral Net.AI Client Acq.Revenue Bench.Vertical Exp.MarketplaceIntl. ExpansionMicroloans02468Weeks

Moonshot 8 (Track 3 Engine) excluded from charts. It's the multiplier that makes 1-7 possible.

First 90 Days: Where I'd Start

Given that Lettuce likely has a limited (but growing) user base and I'd be working from public data initially, I'd sequence by what's testable right now vs. what needs more data to be meaningful:

Moonshot 3 (Referral Network) first, because it costs almost nothing, works even with a small user base, and tests whether Lettuce customers actually want to find each other. That signal tells you a lot about what to build next.

Moonshot 1 (Revenue Benchmark) second, because it directly tests the data moat hypothesis. Even with a small dataset, a prototype reveals whether solopreneurs care enough about peer comparison to share it.

Moonshot 6 (Vertical Expansion) third, because vertical landing pages are cheap to test and the conversion data tells you which segments to double down on. No internal data required, just ad spend and landing pages.

Moonshots 2, 5, and 7 (Microloans, Marketplace, International) are higher-ceiling plays but need more users and data to test properly. They move up the queue as the user base grows. And Moonshot 8 (Track 3 Engine) is the one that makes all of them possible.

How it gets done

Charlotte + AI Execution Speed

One person with the right judgment and the right tools can run experiments at a pace that used to require a team. The experiments that work get handed to the team to scale.

Why even do customer interviews when you can build the prototype and ship it to potential customers as the real thing in different variations? Run an SDR email campaign, measure real behavior. The prototype IS the research.

Competitive intelLanding pages (40x)Outbound campaignData analysisCustomer validationProduct prototype06121824Days
Traditional Team Charlotte + AI
TaskTraditionalCharlotte + AI
Competitive intel reportHire analyst, 2-3 weeks48 hours
Landing pages (design + copy + deploy)Designer + copywriter + dev, $5K+ per page$20/variation, 40 in a weekend
Outbound campaignSDR hire, $80K/yearAI agent, $200/month
Financial data analysisData analyst, 1-2 weeksRuns async in background
Customer validationResearch firm, $15K+, 2-3 weeksBuild it, ship it, measure real behavior
Product prototypeSprint team, 2-4 weeks2 days (Charlotte's SportConnect Marketplace: built + tested in 48 hrs)

The cost of inaction

The Risk of Not Doing This

Lettuce raised $28 million to win the solopreneur market. Collective has similar funding and a similar product. Intuit has infinite resources and 100 million users. The window to build a defensible moat is measured in months, not years.

Every week without someone dedicated to growth experiments is a week where the next distribution hack, the next product insight, the next segment opportunity goes untested. Not because the ideas don't exist, but because everyone capable of running them is busy keeping the engine running.

That's the real cost. Not the salary of one more person. The compound interest on experiments that never got run.