The AI Opportunity that goes beyond Models (A16Z)
The future trends of enterprise AI and consumer AI are rapidly reshaping industry landscapes. From a technical perspective, AI-native products are replacing traditional software, for example, tools like Krea have attracted young designers, while vertically integrated companies like Eleven Labs have created entirely new voice markets. The core opportunities for enterprise AI lie in:
- Proprietary data to build barriers: For instance, Slingshot trains AI models using therapist consultation data, creating unique value;
- Symbiosis between application layer and model layer: Aggregators have a greater advantage than single models, similar to Kayak integrating information from multiple airlines, AI tools need a unified interface to leverage multi-model capabilities;
- Coexistence of labor replacement and enhancement: AI may eliminate some positions (such as night-time customer service), but also expands service boundaries, for example, Slingshot’s AI therapists can work around the clock.
Consumer AI follows a similar logic:
- Traditional categories shifting to AI-native: Photoshop is being replaced by tools like Krea, cloud-native models are replicating in consumer markets;
- Vertical integration creates new markets: Eleven Labs builds a voice industry through model + product lines;
- Data-driven differentiation: For example, AskLeo gains unique competitive advantages by mastering old contract data from Deloitte.
However, challenges are equally significant:
- Difficulty in building moats: Atmospheric programming accelerates product iteration, enterprises without barriers may be quickly replicated;
- Shift in value capture models: Transitioning from charging by functionality to competing with human costs, requiring a rethinking of pricing logic;
- Balancing social impacts: Technological progress reshapes the job market, needing vigilance against AI’s impact on careers while embracing new opportunities brought by efficiency improvements.
Lample’s warning is profound — “the good old days” are being replaced by an AI-driven software ecosystem. For developers, this is both a challenge and an opportunity, and the golden age of AI applications may have quietly arrived.
Translation
企业AI与消费者AI的未来趋势正加速重塑行业格局。从技术角度看，AI原生产品正在取代传统软件，例如Krea等工具已吸引年轻设计师，而像Eleven Labs这样的垂直整合公司则创造了全新语音市场。企业AI的核心机遇在于：
- 专有数据构建壁垒：如Slingshot通过治疗师咨询数据训练AI模型，形成独特价值；
- 应用层与模型层的共生：聚合器比单一模型更具优势，类似Kayak整合多家航空信息，AI工具需统一界面调用多模型能力；
- 劳动力替代与增强并存：AI既可能淘汰部分岗位（如夜间客服），也扩展服务边界，如Slingshot的AI治疗师能全天候工作。
消费者AI同样遵循相似逻辑：
- 传统品类转向AI原生：Photoshop被Krea等工具取代，云原生模式正在消费市场复制；
- 垂直整合创造新市场：Eleven Labs通过模型+产品线构建语音赛道；
- 数据驱动差异化：如AskLeo掌握德勤旧合同数据，形成独特竞争优势。
但挑战同样显著：
- 护城河构建难度：氛围编程加速产品迭代，缺乏壁垒的企业可能快速被复制；
- 价值捕获模式转变：从按功能收费转向与人力成本竞争，需重新设计定价逻辑；
- 社会影响平衡：技术进步重塑就业市场，需警惕AI对职业的冲击，同时拥抱效率提升带来的新机遇。
兰佩尔的警示意味深长——”美好旧时光”正被AI驱动的软件生态取代。对开发者而言，这既是挑战也是机遇，AI应用的黄金时代或许已悄然来临。
Reference:
https://www.youtube.com/watch?v=3XVDtPU8xKE