AI Was the Last Nail in the Coffin of Venture Capital As We Know It
Smaller teams, faster cycles, and smarter tools powered by AI are rewriting the startup funding playbook
The Cracks Were Already Showing
Venture capital didn't break overnight. The model has been quietly misfiring for years.
Fund sizes ballooning from $50M to $500M+. Exit timelines stretching from 5 years to 10+. LPs still asking for 3x net returns, but most funds quietly optimizing for assets under management and 2% management fees—not the 20% carry that would align them with founder and LP success.
Even in Web3—an ecosystem that promised to reinvent venture—familiar patterns took hold. Startups were pushed to launch tokens they didn't need. Token warrant structures padded investor returns but damaged community trust. Tokenomics became a tool to satisfy cap table math, not ecosystem design.
Meanwhile, secondaries became a pressure-release valve—not because the system was working, but because liquidity had vanished. IPOs are down 80% from 2021. Acquisitions are increasingly rare. The market for exits has evaporated.
The model wasn't dead yet. But it was definitely sick.
Along Came AI
And that changed everything.
In 2000, I helped launch a startup that raised a $19M seed round—half of it went to servers. A few years later, AWS made that infrastructure obsolete and ushered in the Web 2.0 era.
Now we're at another inflection point, but this one is 100x faster and more consequential for the venture industry:
AI is rewriting the startup playbook. Small teams can go from idea to product-market fit in months—not years—using off-the-shelf tools that cost just a few hundred dollars a month. What once required dozens of engineers and millions in capital now requires only speed and vision.
I recently spoke with a founder who built, launched, and hit $50K in MRR within 90 days—solo, with no outside funding, using tools that didn't exist a year ago. This isn't an edge case anymore. It's becoming the norm.
Founders today are optimizing for speed, ownership, and optionality. Venture is still optimizing for check size, ownership, and 10x exits.
Worse, most funds aren't prepared and are facing a typical innovator's dilemma: while AI is eroding their edge in sourcing, diligence, and support, adapting would mean dismantling the very business model—predictable, fee-based, and risk-free—that keeps them alive. That's why many VCs pretend that AI will not come after their business. They are wrong…
A Time for Change
In the last few months, I started asking myself some hard questions:
Do I still believe in the way venture works today?
Would I be comfortable leading a 7-year closed-end fund in a world where cycles are compressing this fast and where incentives are so misaligned?
What kind of investor do I want to be in the AI era?
After decades investing through traditional venture, and after nearly a year as a Partner at a leading Web3 Venture fund, I decided to step away from traditional venture models to focus on building something new.
Not out of frustration or burnout.
But because the gap between what founders need and what traditional VC offers is widening by the day. And I no longer felt that retrofitting a model I no longer believed in was something that I could do.
What I'm Building Instead
Today, I'm launching Bluelabel.Ventures — not just a fund, but a flexible, independent platform for early-stage investing in the AI era.
It's early. It's experimental. But it will be built for the world that's coming instead of the one we used to live in. Some guiding principles are:
Independent
No LPs. No committees. I will move fast, invest my own capital, and stay close to founders. When a deal makes sense, I can say yes in days, not weeks. When it doesn’t, I will try to provide valuable feedback and not waste founders’ time.
Structure-Agnostic
I'm planning to test new funding and partnership models: rev-share deals where founders keep 100% equity, founder buybacks with flexible timelines, equity/token hybrids optimized for community health—whatever fits the company's actual trajectory, not just my fund's.
AI-Enhanced
I plan to use AI across sourcing, diligence, and portfolio support—not to replace judgment, but to scale my capacity. I already started building what I call Bluelabel OS, a series of agents that can help me do the work of a traditional 3-person investment team, and I plan to add new features and functionalities that can also benefit my portfolio companies (more on this soon).
Aligned & Collaborative
I'm not chasing unicorns. I want to back teams building meaningful, sustainable businesses. At the end of the day, return is not just IRR. I want to have fun and be proud about the portfolio I create. I also want to learn new stuff and work with people I trust and admire. This is my measurement of success.
What I'll Be Sharing
This is a hands-on experiment. But while I dust off my coding skills (vibe coding, as they call it now, hehe!), I plan to also share my experience and thoughts, posting about:
How I'm leveraging AI to run a solo operation that competes with larger firms
Why most VCs are stuck in the pre-AI paradigm—and what needs to change
What AI is (and isn't) changing in venture decision-making
Interesting ideas and examples of AI applications I find while experimenting
Real numbers behind alternative deal structures I'm testing
And, occasionally, notes on scuba diving, books, and other random thoughts
Join Me and the Bluelabel Ventures Community
If you've read this far, you're likely feeling the same tension I am—between how venture has worked and how it needs to work in the AI era.
I'm building Bluelabel Ventures not just as an investment platform, but as a community for those interested in how to reimagine early-stage funding and startup building in an era of ubiquitous AI. Here's how to get involved:
For Founders:
Subscribe to the Bluelabel.Ventures Substack for frequent insights on AI-era company building
Share your experiences using AI, tell me what tools you'd like to have and can't find
Connect on LinkedIn or DM me on X @bluelabel with "Founder Chat" if you're building something aligned with my thesis
For Investors & Industry Observers:
Share your own experiences with what's working/breaking in traditional venture
Tell me about your own experience using AI for investing, or reply to any Substack post with questions about AI's impact on investing you'd like me to address
Suggest topics for upcoming deep-dives or podcast conversations via email (hello@bluelabel.ventures)
I'll be sharing new frameworks, data, and case studies from the frontlines of this transition. No fluff, just practical insights you can apply immediately.
The old playbooks are becoming obsolete. Let's write the new ones together.
🔹 Subscribe to Bluelabel Ventures Substack
🔹 Follow on X: @bluelabel
🔹 Connect on LinkedIn
Ad astra. 🤖🚀🤖