# Conclave Prompt — Rajiv Endeavor: 3-Year Success Factors
## Context
I'm Matt Murray — Senior GTM Strategy & Ops at DocuSign IAM, ex-Carlyle (late-stage PE), ex-tech investment banker, and ex-operator (ran a ~$240M industrial distribution business to exit). I'm building an AI consulting practice targeting hedge funds, law firms, and family offices, and I ship AI-native projects through coding agents (DC Scout, Negotiate, Tribunal, Cellarmate, Roll Your Own Memory, HumanizeAI).
A friend, Rajiv, is pitching me to co-build an AI-native research lab as part of a fund he's raising. What he's shared so far:
- He's actively raising. Deck goes to LPs Monday, calls and firm commits over the next month.
- Proposed structure: Operating Company + Private Infrastructure Fund + Research Lab + SPV + "Act Two" (undefined).
- Stated thesis: "bidirectional data flow" between the research lab and capital allocation — lab generates theses, fund deploys capital, fund outcomes and positions feed back into the lab as labeled signal and research priorities.
- His value: managing and steering research (his stated multi-year background), mentoring talent, anchoring the fund.
- His ask of me: be the AI-builder side of the lab. I bring agent and infrastructure shipping speed plus prior builds.
Reference points he shared or that apply:
- **Capability comp:** funda.ai (AI-native equity research sold to hedge funds; multi-million ARR in year one).
- **Exit comp:** Venn by Two Sigma → Insight Partners (Jan 2026).
- **Scale comp:** BlackRock Aladdin (~$1.5B annual revenue from external clients, managing $25T+ in assets).
## The Question
What are the key success factors for this endeavor — the combined OpCo + Fund + AI-native Research Lab — to genuinely succeed over the next three years (target horizon: mid-2029)?
Evaluate "success" along two axes, separately:
1. **Enterprise success.** The fund actually closes, the lab actually ships, the architecture works, and by mid-2029 the venture has either (a) deployed and returned capital on a credible Fund I track record, or (b) demonstrated a clearly externalizable Aladdin/Venn-shape lab, or ideally both.
2. **My personal success.** I have meaningful equity and/or carry that is vested or in clear sight, the role expanded with the business rather than getting eclipsed, the work materially advanced my AI-consulting practice or set up a venture-scale next move, and the relationship with Rajiv survived the deal.
## Specifically Address
- The strategic, structural, and execution decisions made in the first 6–12 months that will most determine whether this works.
- The dependencies likeliest to break the thesis if mishandled: LP base quality, asset class clarity, Rajiv's verifiable track record, the closed-loop architecture, competitive density vs. funda and internal hedge-fund AI teams, team build, IP ownership of my prior work.
- What "looks fine on paper" but kills 3-year outcomes for ventures of this shape (first-time fund + captive tech operation + non-technical founder + technical co-founder).
- Where I hold unique leverage entering this deal, and how to convert that leverage into terms.
- A short verdict per axis on the conditions under which I should commit deeply, participate lightly, or decline.
## Ground Rules
Adversarial perspectives are welcome and encouraged. I'd rather hear sharp disagreements among the panel than a smoothed consensus. If any panelist believes the entire premise is flawed, say so directly.
Matt should not commit as a co-founder on Monday. Instead, he should enter a 6-month paid advisory role with 1–2% equity in a standalone Platform OpCo, securing a Right of First Refusal (ROFR) to convert into a **25–30% co-f…
Gray smoke