The New Rules of AI Costs: From Profit Killer to Growth Engine 🚀💰

Описание: Is the staggering cost of AI inference a threat to your business, or is it actually your most powerful competitive advantage? For most companies, the massive expense of running AI models feels like a profit-killing monster, but a new breed of AI-native startups is flipping the script.

In this briefing, we explore the "Inference-as-Marketing" reframe that is disrupting the software industry. You’ll discover why the fastest-growing companies in 2026 aren't trying to cut their AI spend—they’re leaning into it to build "moats" that traditional competitors simply cannot match.

In this video, you’ll learn:

The AI Cost Paradox: Why the old business playbook of "high costs are bad" is leading companies in the wrong direction.

Inference as Marketing: How to reframe computation spend as a replacement for traditional customer acquisition costs (CAC).

The Viral Growth Playbook: A look at how companies like Cursor achieved the fastest SaaS growth curve in history by prioritizing "wow moments".

Efficiency at Scale: How Lovable generates $1.5M in revenue per employee—8x the industry average—without a traditional sales team.

The Premium Escape Hatch: How high-value AI agents can command $100K+ price tags by replacing labor rather than just selling software.

Building the New Moat: The three key takeaways to turn your AI spend into a viral distribution channel.

The future of business isn't about minimizing costs; it's about maximizing value so overwhelming that price becomes irrelevant.

Timestamps: - Introduction: The AI cost headache - Is AI a profit killer? - Section 1: The AI Cost Paradox - Section 2: Inference as Marketing (The Big Reframe) - Section 3: Viral Growth Playbook in practice - Case Study: Cursor’s rocket ship growth - Case Study: Lovable’s staggering efficiency - Section 4: Choose Your Path (Inference-First vs. Sales-First) - Section 5: The Escape Hatch (The Premium Path) - Section 6: The New Competitive Moat - Key Takeaways and Summary

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