Data Driven VC
24 posts
Data Driven VC
@datadriven_vc
Data Driven VC is a community of 45k+ experts at the intersection of venture capital, data, and AI. Everything you need to run a modern investment firm.
Join 45k+ readers ➡️ Katılım Ağustos 2024
50 Takip Edilen16 Takipçiler
AI Landscape and tool cycles are changing faster than ever.
The question for VC's is no longer whether to build.
It is what to build, where to build it, and how deep to go.
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We’re launching the 2026 Data Driven VC Landscape in a few weeks.
AI is rapidly changing how venture firms source, evaluate, support, and operate.
The tech stack inside top VC firms is becoming a competitive moat.
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The full session covers the design and architecture files, the tool tradeoffs, agent harnesses, and security and governance.
Live build, start to finish.
datadrivenvc.io/community
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There is no version of this where you walk away and come back to working software.
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Vibe debugging is the hard part of vibe coding.
Here's how Georgiy from @enteroverdrive built a VC Operating System
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Deep tech's VC share: ~10% → 20%+ in 2025.
EU: $20.3B (32% of VC).
Switzerland: 60%.
Deep tech IRR: 17% vs ~10% traditional.
AI collapsed hardware cycles from 15-20yrs to 5-8, fitting the fund window.
The arbitrage window before capital reprices is the best in venture today.
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Data Driven VC retweetledi
Our April GTM survey found that CRM usage has risen since AI tools began to be adopted at scale.
The agents that listen to calls and write structured notes back into the system are, for the moment, giving reps fresh reason to consult it, because the data sitting there has become dramatically richer than it used to be.
a16z's Gio Ahern, Steph Zhang, and Alex Immerman on the shift from "systems of record" to "systems of intelligence": a16z.news/p/from-system-…
Steph Zhang@steph_zhang
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Our data shows the majority of VC tech stacks are now owned by GPs and partners, not engineers.
As Rahul Nath (CPO, Accel) put it at our summit: AI lowers the build barrier, but data infrastructure and security still need technical owners, and that's not the investment team's job.
Lenny Rachitsky@lennysan
Not enough people are talking about how much AI is impacting the role of data science. I was chatting with a DS friend, and he said that most of his team's work now is reviewing half-assed AI data analysis from PMs and engineers. And that 50% of the time, that analysis is wrong. The role is becoming less fun.
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The point in @_avichawla's piece data-driven VCs should apply to their own internal systems:
A wiki page on "Project X" tells you what got discussed.
A typed knowledge graph tells you which decision was made, who promised what, and what's shifted since.
Avi Chawla@_avichawla
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Full breakdowns of both episodes in the newsletter.
Join 45,000+ investors reading @datadriven_vc:
newsletter.datadrivenvc.io
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Carta: half of acquired startups raised under $10M before getting bought. Fewer than 10% raised $100M+.
You can't realistically IPO under $3-5B today.
Every extra round of funding narrows your exit options. Capital efficiency is an exit strategy.
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For every $0.90 AI venture-growth startups raised in Q1, investors had $1 to deploy.
Non-AI peers got $1 for every $1.70 sought.
PitchBook + Coller: capital supply now exceeds AI founder demand. Late entrants are buying the top.
That and 3 more findings from this past week's @datadriven_vc Insights:
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