The New Application Layer - Malte Ubl, CTO Vercel

2026-04-20 · Source: AI Engineer · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Cloud Computing & IT Infrastructure · Depth: Intermediate, long

Summary

Malte Ubl, CTO of Vercel, delivered a keynote at the first AI Engineer conference in Europe, asserting that AI engineering is the legitimate successor to web development and will shape the next decade of software. He introduced his "vibe coding" stack, including chat SDK for agent-to-chat app integration and just bash, a TypeScript-written bash interpreter for agents with nanosecond startup. Ubl emphasized that agents represent a new kind of software, making previously uneconomical automation viable and leading to a significant increase in software creation. He highlighted archetypes of effective agents being built today, such as automating support, compressing research, surfacing existing information, and eliminating boring work. Ubl also noted a shift where AI agents are becoming the majority users of web properties, citing that over 60% of vercel.com page views in the last 7 days were from AI agents, necessitating an API and CLI-first approach for developer tools and infrastructure designed for agent-written code. He concluded by positioning Europe as a leader in AI engineering innovation, independent of model labs, and predicted model commoditization, which would empower AI engineers at the application layer.

Key takeaway

For AI Architects designing future systems, recognize that AI agents are rapidly becoming the primary users of software, not just builders. Prioritize API and CLI-first development for all new features, ensuring your infrastructure is optimized for agent-written code and automated workflows. This shift will be critical for scalability and security, demanding a re-evaluation of traditional software architecture to support agent-native applications.

Key insights

AI agents are a new software paradigm, enabling previously uneconomical automation and driving increased software creation.

Principles

• Agents make previously uneconomical automation viable.
• AI engineering is the successor to web development.
• Model commoditization empowers application-layer innovation.

Method

Identify agent opportunities by automating support, compressing research, surfacing existing information, or eliminating tedious tasks to save costs and improve job satisfaction.

In practice

• Build agents for 24/7 support operations.
• Automate research phases in human decision processes.
• Develop tools for agents to use via API/CLI.

Topics

• AI Engineering
• Software Agents
• Application Layer
• Model Commoditization
• Vercel

Best for: AI Engineer, Director of AI/ML, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Engineer.