AI, LPs, and the New Era of Venture | Lu Zhang (Founder & Managing Partner, Fusion Fund)

Описание: Lu Zhang, Managing Partner of Fusion Fund, joins Peter this week to talk about what it takes to scale an early-stage venture firm—and back game-changing companies—at the speed of today’s AI boom.

Fresh off her oversubscribed $190M Fund IV raise, Lu talks about what most managers get wrong when pitching institutional LPs, what it takes to stand out in a bubble-driven market, and why true founder support means going way beyond capital. She opens up about her unique CXO and Super Founder networks, team-based investing philosophy, and how Fusion unlocks early commercial contracts—even from highly regulated enterprise buyers.

Plus, why Lu took LP calls from Antarctica (via Starlink), how she thinks about data privacy and AI affordability, and why a founder’s revenue durability matters more than their paper markup.

If you’re looking to raise a fund, raise a round, or just understand how great institutional investors think, this is a must-listen.

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Chapters:
00:00 – Intro & welcome to Lu Zhang
01:15 – Fund IV success: fusion in a $190M market moment
02:14 – Why repeat founders are jumping back in
03:32 – Different edges: repeat vs. first-time AI founders
04:46 – Are we in a valuation bubble?
05:40 – Founders, pricing, and capital discipline
07:10 – Fusion’s advice-first approach to early-stage rounds
08:19 – CXO network as a go-to-market advantage
09:44 – Why “revenue is the best capital”
10:14 – Building founder loyalty through value creation
11:33 – Handling tough decisions: shutdowns, M&A, and alignment
13:23 – Lu’s take on the new role for secondaries
14:38 – Distribution vs. recycling: how Fusion thinks
15:15 – Fund structuring and reserving for multiple follow-ons
16:04 – From solo GP to a 12-person team
17:05 – Matching long-term firm vision with scaling founder support
18:12 – Working across sectors with deep research and reports
19:31 – Beyond Silicon Valley: geopolitical signals + timing
20:05 – What CXOs actually want from AI startups
21:29 – Edge compute, vertical models & AI infrastructure
22:24 – Enterprise readiness and compliance bottlenecks
23:10 – The true cost of AI: what founders overlook
24:18 – Portfolio growth stats: 20x revenue in one year
25:04 – When small teams scale to $100M+
26:13 – Leveraging open source for enterprise distribution
27:15 – How to break into regulated markets with AI
28:25 – Complying with data regulations by design
29:12 – The upside of regulation-readiness for AI adoption
30:18 – Foundation models & new healthcare openness
30:57 – M&A momentum inside Fusion’s most recent exits
32:14 – Fund IV hard cap decisions & LP allocation dynamics
33:24 – LP calls from Antarctica: a real story
34:04 – M&A vs. IPO: timelines, outcomes & premiums
35:07 – From angels to institutions: how Fusion’s LP base evolved
36:01 – Building LP community with intention
36:56 – Graduation moment: from emerging manager to fund IV
37:47 – Why large LPs are warming to small fund strategies
38:44 – Growing with consistency: keeping method over trend
39:42 – The LP metric that matters: revenue at the portfolio level
40:43 – Why clean marks and real revenue matter so much now
41:17 – Has co-investor behavior changed post-2021?
42:12 – Why Fusion’s map of investors is still highly consistent
42:58 – Lightning round: sectors, geographies & support
43:03 – Sector Lu’s most excited about? Healthcare & space
44:04 – Should founders be in Silicon Valley?
44:58 – A founder-first mindset, from housing to liquidity
46:00 – Final thoughts and outro

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