Snowflake's CEO describes a shift to "spec-driven development," where engineers write English-language requirements and AI automates the coding, testing, and deployment. This transforms the entire software creation process, moving beyond simple code completion to full workflow automation.
AI agents are not just chatbots; they are powerful orchestrators that connect to various underlying tools (e.g., portfolio analyzers, databases). This allows non-technical users to perform complex data analysis and execute subsequent actions using simple natural language commands.
The significant barrier of messy, legacy data is being overcome by AI. Snowflake is developing "agent-driven migrations" that automate the process of moving data from old systems onto modern platforms. This drastically reduces project timelines from multiple years to just a few weeks.
While GDPR provided consumers valuable data rights, its high compliance costs created an unintended moat for large incumbents. Startups struggle to meet the complex requirements from day one, whereas giants could easily absorb the costs, stifling competition and reinforcing their market power.