The dashboard is the proof. This is the strategy that scales it.
You just used a live, multi-chain Aave V3 risk dashboard (home) consuming an Envio-hosted indexer that's caught up to chain head on Polygon, Arbitrum, and Base. Here's how I'd turn that single live artifact into Envio's named-account expansion motion — 6 levers, $250k–$880k year-1 sensitivity band, half-case 1.7× payback against a typical Growth Engineer total comp.
Reads in 5–7 minutes. Each section links to the full memo on GitHub for depth.
Why money-market vertical is the lead
The vertical with the highest ClickHouse-tier conversion fit, deepest analytical workloads, and stickiest customer profile.
Money-market protocols are analytics-product by default. Their customers (treasuries, liquidator bots, governance DAOs) consume risk dashboards, utilization curves, and liquidator leaderboards as first-class product features — not as ops afterthoughts. That puts them on the analytical workload curve where Postgres aggregation latency becomes painful, which is exactly where ClickHouse Sink (and the Dedicated tier) earn their keep.
The pain-map matrix names 5 funnel stages × 2 root causes (Tech, Business) for the money-market vertical. Two stages carry the largest year-1 levers in the revenue model: Activation (Lever 1, recovering non-activators through onboarding fixes) and Monetization (Lever 6, named-account expansion to Dedicated tier).
The dashboard you just used is the lead vertical's reference application. The other two templates (DEX, perp) are shape variants proving the same growth motion generalizes — fork → deploy → upsell — but money-market is the lead because it has the highest fit per customer dollar.
The 6-lever revenue model
$490k year-1 incremental ARR at placeholder values. Half-case $250k still pays back the role 1.7×.
Six operational levers, each individually defensible. Every input is either real (mine, from Mirror Protocol), an industry benchmark, or a labelled placeholder you replace on day 1 with internal data:
| # | Lever | Year-1 ARR | Mechanic |
|---|---|---|---|
| 1 | Activation | $88k | Recover non-activators via 4 onboarding fixes |
| 2 | Migration concierge | $110k | 5 named migrations × $22k ACV |
| 3 | Case-study factory | $120k | 6 studies × 5 inquiries × 20% close × $50k |
| 4 | Tier expansion | $40k | Free → Production cohort upgrades |
| 5 | Vertical content | $12k | SEO + community (back-loaded) |
| 6 | Dedicated-tier ClickHouse Sink | $120k | 10 outreach → 5 trials → 3 Dedicated upgrades |
| Total · placeholder year-1 ARR | ~$490k | Sensitivity band $250k–$880k | |
The dashboard you just used IS Lever 6's reference application. The named-account funnel for ClickHouse-tier expansion stops being "imagine the conversion path" and becomes "click → fork → deploy → upsell." Click any reserve in /reserves, see the analytical workload that Aave's own treasury team consumes today, and that's the workload Lever 6 monetizes by tiering up to Dedicated.
The 90-day operating plan
Day 1, Week 1, Month 1, Quarter 1 — what gets shipped at each checkpoint.
The strategy isn't a slide deck — it's a working document. Day 1 is replacing every placeholder in the revenue model with internal data (the hardest part of any new role's first week). Week 1 is shipping the four onboarding fixes the forensic identified, the highest-ROI ones being the Greeter tutorial time-estimate + success-indicator (industry benchmark: 2× tutorial completion).
Month 1 is the first case study live — an open-source-derived seed like the Sablier 0-alias Effect cache trick, or Velodrome's CLAUDE.md gotcha list. These don't require customer interviews; they're sitting in plain sight in your customers' open-source code.
Quarter 1 is the named-account outreach for Lever 6: Velodrome, Sablier, Aave, LI.FI, Limitless + 5 wave-2 targets. Each gets the dashboard pre-deployed against their protocol's contracts (5 mins of config), then a single DM/email: "I built you a risk dashboard at <URL>. Free, hosted, yours to fork." Track inbound; measure conversion to Sink trial.
Shape variants — same motion, other verticals
Money-market is the lead, but the 'fork → deploy → upsell' motion generalizes. The other two templates prove it.
Real ABIs, real factory address. 10 vitest passing including 3 Effect-cache hit/miss tests. 31,091 cross-entity checks live on Optimism. Same three-layer architecture (EventHandlers → Aggregators → Snapshots) as the money-market template.
Subscribes to a single global EventEmitter contract, decodes the EventLogData typed dictionary. v1 scope: PositionIncrease only — proves the architecture against real chain data; v2 (PositionDecrease, Liquidation, Funding) is mechanical extension.
The "lead" choice is intentional — money-market has the strongest ClickHouse-tier conversion fit per customer dollar. But the same conversion funnel runs against any vertical where customers ship analytical products: DEX TVL/volume dashboards, perp leaderboards, prediction-market volume curves, NFT-collection holders dashboards. Each is a separate flavor of Lever 6.
Why I'd do this for Envio, specifically
I built Mirror Protocol on Envio. Indexed 7 entities. 1,000× latency improvement over RPC. Lived the customer side end-to-end.
Mirror Protocol — my own behavioral pattern matcher — runs on Envio. 7 entities indexed, 140+ Sepolia trades, bot decision latency improved from ~4.2 seconds (RPC) to 3–5 milliseconds (Envio). That's a ~1000× improvement, but it's not the lever; the lever is that I ran the full customer journey. I hit Envio's onboarding flow as a fresh user. I shipped a deploy. I watched the GraphQL playground query return data. I felt the friction the onboarding forensic identifies, and I shipped fixes for it in this package. That's the customer-shaped advantage: not "I read your docs" but "I executed your funnel and have the artifacts to show it."
The package as-shipped is uniquely positioned for the role: a live working dashboard at a public URL, 23+ strategy memos triangulated from public data, 3 forkable templates with 21 invariants × 48,014 live cross-entity checks passing on real on-chain data, and a docs site that hosts the whole memo collection. Most candidates ship one of these. This package ships all five.
The "Growth Engineer" name is two halves of the same job: the engineering half (you saw it on the dashboard) and the strategy half (you're reading it now). I'd want the role because it's the rare position where shipping code AND shipping a revenue model are the same job. The package is the resume.