Chapter 1: The AI-First Imperative¶
In March 2025, a solo developer built a browser-based flight simulator and crossed $1 million ARR in 17 days. AI wrote most of the code.
Three months earlier, at my company Yirifi, just 2 people built 15 backoffice microsites in 3 months. Not because we're superhuman. Because AI changed the math.
These stories aren't about productivity hacks. They're about something bigger—a 107x cost collapse in AI processing over two years. When intelligence becomes cheap, everything built on the assumption that intelligence is expensive breaks.
This chapter is about what that shift means for how you build a company.
"15 backoffice microsites in 3 months, just 2 people. Not because we're superhuman—because AI coding changed the math."
Universal insight: The economics of software development have inverted. What used to require 10 engineers and 12 months now takes just 2 people and 3 months—if you design for AI from the start.
Memorable close: "When development costs approach zero, the only constraint is imagination."
What You'll Learn¶
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The AI Inflection Point: The 107x cost collapse, productivity data from production use, and three shifts that separate this wave from previous AI hype—plus the METR study showing when AI actually slows you down.
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AI-First vs AI-Enabled: The Kill Test framework and five observable characteristics that distinguish companies built on AI from companies built with AI.
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First-Mover Advantages: Why Jasper's moat flooded while Glean's holds, and a timeline framework for when first-mover advantages lock in.
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The Cost of Retrofitting: Why 95% of AI pilots fail, what Salesforce vs Notion teaches about retrofit timelines, and three paths forward for legacy systems.
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The Economics of AI-First: The inverted build vs. buy calculus when AI makes building faster than integrating.
The Real Question¶
The economics have already shifted. What used to be prohibitively expensive to build is now cheap. What used to be cheap to buy now carries compounding integration costs.
For startups, this is the advantage of a generation. Build what incumbents are still buying.
For established organizations, the path is harder but not closed. Start with one internal tool. Prove the economics work in your context. Pick a low-stakes domain, build with AI, measure the results.
Either way, the window won't stay open forever. Every month you spend evaluating, piloting, and planning, competitors are accumulating advantages that take 12-18 months to build.
When development costs approach zero, the only question is: what would you build if you could?
Let's find out.