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The article highlights the irony of Venture Capitalists demanding AI strategies from founders while their own funds still rely on manual, inefficient workflows, leading to a loss of operational alpha.
AI 生成摘要
文章指出創投業者要求創始人制定AI策略的諷刺之處，然而他們自身的基金卻仍依賴手動、低效率的工作流程，導致營運上的阿爾法收益流失。
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There is a supreme irony we witness every day in the world of Venture Capital.
We watch you sit across the table (or Zoom) from founders and grill them about their “AI Strategy.” You demand operational leverage. You scrutinize their tech stacks. You ask them how they plan to do more with less.
And then? You go back to your desks and manually copy-paste data from a PDF into a spreadsheet.
We work with dozens of funds, from emerging managers to Tier-1 giants. The pattern is always the same: You are funding the AI automation revolution, yet functionally, your funds are operating like it’s 2015.
You are the cobbler’s children, and you are walking around barefoot.
The issue isn’t laziness. The role has evolved faster than the operating system supporting it. From the outside, this mismatch is precisely why manual workflows are killing alpha.
From our vantage point, the modern VC looks less like an investor and more like a high-throughput data router. We’ve analyzed the workflow, and it usually looks like this:
A VC’s day is a constant loop of context switching - IC prep in the morning, a founder call, portfolio updates, a board meeting, then back to a call you half-remember. Every step forces a mental reset. Research shows it takes roughly 20+ minutes to regain deep focus after a disruption, yet investors switch tools and tasks every few minutes.
The result isn’t poor judgment, it’s shallow attention. You’re not truly analyzing companies or patterns; you’re spending your cognitive energy reconstructing context and keeping systems updated. That hidden tax compounds across the fund and quietly erodes decision quality.
The Impact We See: Attention is consumed by operations rather than insight. Strong investors miss subtle but material signals in materials, not because they lack skill, but because mental bandwidth is drained by avoidable workflow friction.
Let’s be honest: no one wakes up excited to update the CRM.
For many funds, it has quietly become a write-only repository. Data is captured out of routine and operational necessity, but the system rarely repays that effort with actionable insight.
True intelligence is “Recall”.
If you have to manually search for these answers, your data isn’t working for you.
The Impact We See: Institutional Amnesia. Your fund’s collective intelligence is trapped in silos. When a Partner leaves, their knowledge leaves with them, because it was never properly synthesized into your system.
We watched closely how funds handled the SVB crisis.There were two types of funds that week:
Most of you are still relying on “The Monthly Update” - a call or a PDF that arrives in your inbox on the 15th of the month. By the time you read it, the data is three weeks old. That is lag. In finance, lag kills.
The Impact We See: You are functioning as firefighters, not fire preventers. You find out about runway issues when there are 4 months of cash left, not 12.
The friction we see is not solved by hiring more Associates. It is solved by Agentic Workflows.
We believe you need to stop viewing AI as a tool that “writes emails” and start viewing it as an infrastructure layer that “does work.”
Next Week: Build It YourselfYou don’t need a full platform rollout to start fixing the cracks in your workflow.
In Part 2 of this series, we will open up the hood. We’ll show you how to use n8n, and the OpenAI API to build a functional “Deal Flow Screener” that runs on autopilot.
Get your API keys ready. We’re going to help you build.
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Co-Founder @ Stealth
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