What does it mean to be a “day one partner” for founders—and how does that change in an era of AI-driven acceleration?
On this episode of The Data Minute, Peter sits down with Ed Sim, founding partner of Boldstart Ventures and the voice behind “What’s Hot 🔥 in Enterprise IT VC.” Ed shares what it means to invest at the “inception stage”—before a company is even a company—and how startup formation, team sizes, fundraising expectations, and milestones have radically shifted post-AI boom.
This episode dives into how Boldstart identifies founding teams before they incorporate, why valuation round sizes are splitting into tiny “discovery rounds” and $25M+ jumbo raises, and why the industry is bifurcating between massive multi-stage funds and lean, focused early-stage firms.
Plus: When secondaries make sense, why software moats are elusive, how AI-native investing plays out against pre-AI portfolios, and the surprising thing Ed once did to stop a founder from selling too early. This one’s packed with memorable insights—and honest, founder-first advice.
Subscribe to Carta’s weekly Data Minute newsletter: https://carta.com/subscribe/data-newsletter-sign-up/
Explore interactive startup and VC data, with Carta’s Data Desk: https://carta.com/data-desk/
Chapters:
00:42 – Inception-stage investing explained
01:50 – The compressed cycles of AI and the speed of change
03:32 – Are we in an AI bubble?
05:00 – Why the "middle class" of startups is disappearing
06:56 – Inception investing vs Pre-seed, Seed, and Series A
08:02 – Finding technical founders before they incorporate
09:34 – Boldstart’s “pure play” approach to being first on the cap table
10:36 – From inception through IPO: Boldstart’s full lifecycle model
11:40 – Snyk as a case study of inception-to-scale investing
12:45 – Discovery vs Classic vs Jumbo inception rounds
14:30 – How fund size determines which deals you can join
15:46 – Why some founders intentionally raise small
16:51 – Raising too much: “The tail wagging the dog”
18:00 – Rethinking how much capital founders actually need
18:57 – Founder pressure and capital: choosing wisely
19:40 – Multi-stage firms at the early stage: Helpful or distorting?
21:15 – Two worlds: legacy portfolio vs AI-native upstarts
22:57 – Superhuman, Clay, and adapting to AI post-launch
25:10 – How early is too early for AI revenue?
26:19 – Moats, stickiness, and workflow depth
27:30 – What makes AI revenue durable?
28:39 – Defining “AI company”: product, workflow, or brand?
30:16 – Is data the new moat?
31:40 – Proprietary data and “day one” data strategy
32:37 – Signs that venture is growing up
33:54 – The bifurcation of venture: massive funds vs focused specialists
35:00 – Why LPs want more true early-stage exposure
36:07 – Lack of liquidity—and how it's changing fund strategy
37:25 – “Venture didn’t beat the S&P” and why that’s the wrong question
38:23 – Secondaries: Which companies actually get them
39:20 – Founder secondaries: removing the stigma
40:42 – Vesting schedules and proactive founder conversations
42:35 – Do we have too many VCs?
43:51 – How to navigate a frothy valuation market
45:28 – Lightning round
51:04 – Outro
This presentation contains general information only and eShares, Inc. dba Carta, Inc. (“Carta”) is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services, and is for informational purposes only. This presentation is not a substitute for such professional advice or services nor should it be used as a basis for any decision or action that may affect your business or interests. © 2024 eShares, Inc., dba Carta, Inc. Al
The Data Minute 