WI

Wilco Financial Model

• Developers join a "fantasy company" and complete game-like quests that simulate real production scenarios (debugging, monitoring, code review, crisis response, project management, soft skills).
• Quests run through the engineer's actual IDE and toolchain (GitHub, Jira, Slack, VS Code, MongoDB, etc.) via Wilco's Quest Orchestration Engine.
• Three quest tiers: Wilco-built (common stacks), company-custom (proprietary curriculum), community-built (open ecosystem).
• Management dashboard provides visibility into engineer growth and progress.
• XP system tracks progression; referral/invite loop built into product.

• Implied market: global software engineer workforce and the corporate L&D budgets spent on developer upskilling.
• Problem quantified only qualitatively: online courses have <4% completion rate; large enterprises spend heavily on internal academies; mid-market relies on "trial by fire".

• Not explicitly stated in deck. No pricing slide present.
• Implied structure from GTM and product design:
• B2B seat license or team subscription sold to engineering managers at mid-market companies; rationale: management dashboard feature, enterprise customisation, testimonial from CTO.
• Freemium community edition as PLG acquisition layer; rationale: "Release our community edition allowing every developer to play and create quests" is a stated use-of-funds goal.
• Potential content-partner revenue share or marketplace fee for third-party quest creators; rationale: community quest ecosystem and content partner validation slides (slides 9, 15).
• No ASP, ARPU, contract length, or billing cadence disclosed.

• Monthly active users: REDACTED
• Beta users source: REDACTED
• Content partners: REDACTED
• Product is live (app.wilco.gg referenced in UI screenshot).
• Customer testimonial from Jorge Garcia, Co-Founder & CTO of Hello Iconic - confirms product is in use and solves mentorship-load problem.
• No revenue figures, growth rates, or cohort data disclosed.

• 2x2 matrix (axes: Theoretical ↔ In-Depth, Low Scale ↔ High Scale).
• Wilco positions in the top-right: High Scale + In-Depth - the only player in that quadrant.
• Competitors mapped:
• Internal training programs (ThoughtWorks, Pivotal Labs, Swim): In-Depth but Low Scale
• On-site bootcamps (Lambda, Dev Boot Camp, Hack Reactor, App Academy): Low Scale + Theoretical
• Mentoring platforms (Codementor): Low Scale + Theoretical
• MOOCs (edX, Coursera, Udemy, Udacity, Pluralsight): High Scale but Theoretical
• Moat claimed: proprietary Quest Orchestration Engine; community flywheel; deep tool integrations; customisable curriculum.

• On Freund - Co-Founder & CEO: Operating Partner PICO, Global Head of WeWork Labs, VP Engineering & VP Product at WeWork, VP Engineering at Handy.
• Alon Carmel - Co-Founder & CPO: Senior PM at WeWork ($1B product), top-10 PM in Israel, TechCrunch50 winner, Seedcamp.
• Shem Magnezi - Co-Founder & CTO: 15+ yrs engineering, Staff Engineer at WeWork, Senior Engineer at Facebook.
• Ask: $6M seed
• Runway / period: Redacted (shown as orange block in slide image).
• Use of funds:

1. Release community edition (open quest creation).
2. Build team: engineering, product, game design, growth.
3. Reach target WAU and weekly quests played (numbers redacted).
4. Secure top-tier content partnerships (number redacted).

• Archetype + why: B2B SaaS ARR model with a PLG/freemium community funnel feeding into a paid enterprise tier. Wilco monetises companies (seats/teams), not individual developers directly - so the driver tree is: community MAU → enterprise pipeline conversion → ARR. A pure consumer subscription model is not appropriate given the management-dashboard and enterprise-customisation features.

• Forecast horizon & granularity: 3 years monthly (Yr 1–2 monthly detail; Yr 3 quarterly roll-up). Seed stage - operational model more important than terminal value.

• Key drivers & assumptions:

*Acquisition funnel*

• Community MAU: redacted baseline; seed at 1,000 MAU growing 15% MoM post-community-launch, rationale: early-stage PLG with strong engineer referral loop.
• MAU → enterprise lead conversion rate: 2–5% of MAU generate enterprise inbound, rationale: typical PLG B2B conversion benchmark.
• Enterprise sales cycle: 30–60 days, rationale: mid-market SaaS norm.

*Revenue*

• Average seats per enterprise deal: 20–50 seats, rationale: target is engineering teams at mid-market companies.
• ACV per seat: $200–$400/seat/year, rationale: comparable developer-tools SaaS (Pluralsight ~$400/seat; early-stage discount to land).
• Net Revenue Retention: 110–120%, rationale: seat expansion as teams grow + upsell to custom quest packs; typical for usage-based dev tools.
• Community/freemium tier: $0 (PLG engine only; monetise at enterprise layer).

*Cost structure*

• Gross margin: 70–75%, rationale: primarily cloud infra + quest-engine hosting; low marginal cost per user once quests built.
• S&M: 40–50% of revenue in Yr1–2 (PLG-heavy, lower CAC than pure sales-led); declining to 30% by Yr3.
• R&D: 35–45% of revenue in Yr1–2 (engineering-first product; quest engine + integrations are core); declining to 25% by Yr3.
• G&A: 15% of revenue, rationale: lean seed-stage overhead.

*Headcount*

• Use-of-funds implies heavy Yr1 hiring across eng, product, game design, growth.
• Seed team grows from ~5 (founders + 2) to ~15–20 by end of $6M runway.

*Cash*

• $6M raised; runway months redacted - 18–24 months, rationale: standard seed sizing for a ~15-person team at Israeli/US burn rates.

• Scenarios (Base / Bull / Bear - which variables flex):
• Bull: MAU growth 20% MoM, seat conversion 5%, ACV $350, NRR 120%.
• Base: MAU growth 15% MoM, seat conversion 3%, ACV $250, NRR 110%.
• Bear: MAU growth 8% MoM, seat conversion 1.5%, ACV $200, NRR 100%; enterprise sales cycle extends to 90 days.

• Required sheets / outputs:

1. Assumptions - all drivers above, scenario toggle (Base/Bull/Bear).
2. PLG Funnel - community MAU → enterprise leads → closed ARR.
3. ARR Bridge - new ARR, expansion, churn, net new ARR by month.
4. P&L - revenue, COGS, gross profit, S&M, R&D, G&A, EBITDA.
5. Headcount Plan - roles, hire dates, fully-loaded cost.
6. Cash Flow & Runway - cash in, burn, ending cash, months of runway.
7. KPI Dashboard - MAU, paying seats, ARR, MRR, NRR, burn multiple, CAC payback.