AI-First Startup Guide Outlines Core Principles for 2025-2026

TL;DR. A new evidence-graded guide details ten axioms and a five-layer concept stack for building AI-native startups. - The guide emphasizes AI as the building layer, not a feature, and context engineering as a core discipline. - It highlights data, workflow, evaluations, and distribution as the primary moats, not the AI models themselves. - The framework focuses on closed-loop systems that compound intelligence and an evaluation-driven build sequence.

• AI is the fundamental building layer, not merely a feature, for new startups.
• Moats in AI-native companies derive from data, workflow, evaluations, and distribution, not proprietary models.
• Context engineering is critical, as most agent failures stem from context, not reasoning.
• Compounding intelligence requires a closed-loop system of sensing, deciding, acting, evaluating, and improving.
• Evaluation acts as the steering wheel for AI development, enabling guided progression.

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