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- 🎯 Death of the Sales Funnel
🎯 Death of the Sales Funnel
Why AI-native companies convert 2x more deals by killing traditional sales, plus MicroStrategy's latest $740M Bitcoin bet and the week's digital asset stories.
Hey there 👋,
I took a couple of weeks off, packed up a house, left a country, and I’m writing to you now from a hotel in the Netherlands on my way to Central Europe. I’ll be back properly next week, but Maciej, my business partner, generated this edition for me using our AI workflow at LetterOperators.
If you're a startup founder with a newsletter and want AI to cover for you when life gets hectic, just hit us up. That’s exactly what we built it for.
A crazy story hit my inbox yesterday. A founder saved $50K in three hours.
Not through budget cuts or layoffs, but by prompting AI to build what he needed instead of buying expensive software.
His name is Joshua Wöhle, and he was about to sign a $50,000 SaaS contract when he had a mad idea: "What if I just build this myself?" Three hours later, he had a working app that did everything the expensive software promised—and did it better.
He's not the only one. I've been digging into this trend, and it's proper mental what people are building these days.
The old playbook was simple: Problem → Research → Buy Software → Pay Forever
The new playbook? Problem → Prompt AI → Build Solution → Own It
People with zero coding experience are building enterprise-grade tools that would have cost them five or six figures annually. In hours, not months.
Honestly, when I first heard about this stuff, I thought it was complete bollocks. How could someone with no technical background build proper business software? Turns out I was dead wrong.
Why this matters right now
At LetterOperators, we've been living this shift without fully realizing it. Instead of paying for expensive newsletter tools, outreach software, or project management platforms, we've been building our own systems. Our AI-powered newsletter creation process would have cost us thousands monthly if we'd tried to replicate it with existing SaaS tools.
But here's what really caught my attention: these aren't just weekend hacks. These are proper business tools replacing serious software.
The SaaS industry has been taking the piss for years. Annual price increases, feature limitations, forced upgrades. Now people are building better tools in a weekend than these companies deliver after years of development.
Brian Christner was paying Kajabi increasing fees for his online course platform until the margins went negative. So he vibe-coded his own platform that cost one-tenth as much and had exactly the features his students needed.
Michael Luo, a product manager at Stripe, built a Docusign competitor in a weekend for under $50. So good that Docusign sent him a cease-and-desist letter. A $15 billion company feeling threatened by one person with AI.
Manny Bernabe built an enterprise vendor portal - the kind that handles invoices, contracts, and vendor tracking. Historically would have cost five figures to build and similar annual fees to maintain. He built it for basically nothing.
The pattern is everywhere. People are replacing:
$50,000 community platforms
$15,000 course platforms
$25,000 vendor management systems
$10,000 automation tools
All with AI-built alternatives that cost them hours, not years, to create.
What's actually happening here
This isn't just about saving money. It's about ownership.
When you buy software, you're renting someone else's vision of how your business should work. You adapt to their features, their limitations, their pricing changes. When they decide to triple their fees (like Kajabi did to Christner), you're stuck.
When you build your own tools, you own the solution. Need a new feature? Add it. Want to change how something works? Change it. No support tickets, no feature requests, no waiting for updates.
What this means for you
If you're paying five figures annually for software that does 80% of what you need, it might be time to build the 100% solution yourself. The tools exist. The AI agents are ready. The only question is whether you'll take advantage of it.
The founders who figure this out first get a proper competitive advantage. Not just in cost savings, but in speed, customization, and ownership of their tools.
I'm seeing it happen in real-time, and it's brilliant to watch.
If you're running any kind of business and this resonates, I'd love to hear what expensive software you're considering replacing. Hit reply - I actually read them.
📰 Top News Stories
📊 a16z breaks down crypto in 5 charts - Mobile wallet users up 23%, stablecoin volume up 49%, Bitcoin/Ethereum ETF flows up 28%. The infrastructure layer is proper maturing. Only 22 tokens generate over $1M monthly revenue, showing most projects still haven't figured out tokenomics. - Link
🤖 How to get ChatGPT to recommend your business - Kyle Poyar breaks down answer engine optimization (AEO). Reddit is now the most-cited domain in ChatGPT. Structured comparisons and lists perform best. The goal isn't clicks anymore—it's being mentioned when buyers ask AI what to buy. Citation drift happens fast, so monitor weekly. - Link
₿ The 6 best times to buy Bitcoin in history - Early adoption (2009-2010), post-bubble crashes, crypto winters, COVID panic, and bear markets. The pattern: buy when everyone's scared, hold when everyone's greedy. With Bitcoin at $100K+, we might be in the "acceleration phase" that precedes the next bottoming opportunity. - Link
🏛️ AI spending is now bigger than consumer spending for GDP - Ben Carlson's chart of the year: AI capex from big tech is adding more to US GDP than consumer spending (which makes up 70% of the economy). Microsoft, Google, Amazon, and Meta spent over $250B in 2024. Either they're all mental, or we're witnessing the biggest tech shift in decades. - Link
🛠️ Vibe coding is evolving into "context engineering" - New research shows the future of AI development isn't just about prompting, but systematic context management. Context is becoming the bottleneck for AI agents. The discipline is moving from "art" to "science" with formal frameworks for information optimization. Makes sense - the better context you give AI, the better results you get. - Link
💡 Harvard founder changes his mind on startup burn rates - Rob Snyder's counterintuitive take: don't just extend runway, optimize for "learning-per-dollar-of-burn." If spending $2K can double your sales conversations from 10 to 20 per month, you're essentially buying a month of learning that would have cost $25K in burn anyway. Your limiting factor is usually volume of conversations, not cash. - Link
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That’s it for this week, until next time, buy my product and catch me in the community!
Cheers!
Richard (@richardpatey)
Disclaimer: This email is for informational and entertainment purposes only. It is not financial advice, and I am not a licensed investment adviser. I share what I’m doing personally in the digital asset space—always do your own research. Some links may be affiliate links, so assume I may earn a commission if you use them.
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