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fullstacktard Profile picture
@fullstacktard
Dec 18 • 1 tweets • 1 min read • Read on X
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More from @fullstacktard

fullstacktard Profile picture
Oct 6
5 VC Dogmas in AI That Don't Matter When You're Bootstrapped

spent way too long listening to VC narratives about AI before I realized: none of this shit applies when you're a solo dev just trying to hit $5k MRR

here's what VCs keep repeating and why you can safely ignore it when you're building with APIs and shipping fast

short thread
1/ "AI wrappers have no defensible moat"

VCs love saying anything on OpenAI/Anthropic APIs is "just a wrapper" with no moat

cool story, but I'm not raising a Series A

I'm paying $200/month for API calls and shipping products that solve real problems. My moat is that I actually shipped while everyone else is still arguing about technical defensibility on Twitter.

Jasper hit higher valuation than OpenAI before ChatGPT. Character.AI got 100M users faster than ChatGPT. They understood distribution > purity.

Platform risk is real, sure. But you know what eliminates platform risk? Going narrow. Building for a specific workflow. Making something OpenAI can't be bothered to clone because the TAM is "only" $10M.

VCs need billion-dollar exits. I need profitable products. We are not the same.

latitudemedia.com/news/in-the-ag…
review.insignia.vc/2025/04/15/moa…
2/ "You need proprietary data to win"

the data moat narrative is VC cargo culting

A16Z literally published "The Empty Promise of Data Moats" debunking this. Companies like Harvey, Hebbia, Truewind are winning without proven proprietary data moats.

And here's the thing: I don't WANT a proprietary data moat. That means I have to collect data, clean data, label data, store data, worry about GDPR, build data pipelines...

fuck that

Claude and GPT-4 are already trained on more data than I could ever collect. My job is to build the workflow and ship fast, not become a data janitor.

LLMs improve with each version. The need for massive proprietary datasets is declining. This dogma comes from an earlier ML era that doesn't apply to foundation model APIs.

a16z.com/the-empty-prom…
unique.ai/en/blog/the-my…
review.insignia.vc/2025/03/10/ai-…
Read 8 tweets

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