The New Application Layer - Malte Ubl, CTO Vercel

Summary — “The New Application Layer” (Malte Ubl, CTO Vercel)

Core thesis

• Agents are a new kind of software that both build and use software, creating a new application layer.
• This makes many previously uneconomic automations viable, increasing the total amount of software produced and the demand for engineers.
• Two possible futures:
  • Model-lab dominated: AI remains expensive and value accrues to model providers.
  • Commoditized models: models become cheap and innovation happens at the application/agent layer.
• Malte argues the commoditized-models future is more likely and desirable.

Practical technologies, products & prototypes mentioned

• Chat SDK: connector to hook agents into chat platforms (Slack, Telegram, WhatsApp, etc.).
• just-bash: a Bash interpreter implemented in TypeScript that provides a fast, sandbox-like environment for agents.
• Vercel’s in-house agents on vercel.com:
  • Routing “contact sales” submissions by inspecting LinkedIn/company size and routing appropriately.
  • Triaging abuse reports.
• In-house support agent with ~90% deflection, handling routine queries in real time and routing only complex cases to humans, which improved job satisfaction.

Agent archetypes and recommended use-cases (actionable guide)

• Support automation: 24/7 agents handle predictable support work, offloading routine tasks to increase availability and reduce toil.
• Compressed research: agents gather context and data (web/LinkedIn checks, docs) and leave final decisions to humans — low risk, high ROI because decision ownership remains with humans.
• Information surfacing: extract and synthesize information already present across issue trackers, recordings, docs, Slack, etc., to make it practically useful.
• Eliminate boring work: identify tasks people hate about their jobs and automate them to improve morale and productivity.

Platform & infrastructure implications

• Agents are becoming major software consumers — Vercel observed >60% of page views on vercel.com coming from AI agents in a recent week.
• Expect usage patterns to shift from human/GUI interactions toward APIs and CLIs.
• Design for agents-as-users: expose clear APIs/CLIs and automation-first workflows rather than only UI-driven features.
• Sandboxing and fast startup environments are essential; many teams ship sandboxes so agents can safely execute code or interact with systems.
• Security is a major emerging challenge, comparable to earlier eras of widespread insecurity; anticipate paradigm shifts in architecture and defenses.

Architectural guidance & criticisms

• Separation of harness vs. execution: many agent harnesses are architecturally wrong because they mix where the harness runs with where generated code runs.
• Separate orchestration/harness from execution environments — Malte notes Anthropic has adopted this separation in a recent product.
• Be open to future paradigm shifts — current agent patterns are still early innings.

Economic / industry context

• Cheaper software creation via agents will lead companies to “make” rather than “buy” (the “SaaS copocalypse” idea), increasing engineering work rather than reducing it.
• Europe is well positioned for application-layer AI engineering innovation (examples: Vercel’s AI SDK team in Berlin, Pi — an Austrian coding agent, OpenClaw).
• Europe may not lead model labs but can lead innovation at the application/agent layer.
• Numeric and subtitle-derived claims from the talk may be inaccurate.

Key recommendations for builders

• Focus on low-hanging agent use cases that speed up existing processes (research, routing, surfacing information).
• Prioritize APIs/CLIs and sandboxed, separable execution for agent workloads.
• Use the “what do you hate about your job?” heuristic to discover impactful automations.
• Prepare for security and architecture changes; avoid coupling harness and execution.

Speakers / sources referenced

• Main speaker: Malte Ubl — CTO, Vercel (keynote presenter).
• Projects/companies mentioned: Vercel (agents on vercel.com, AI SDK), Anthropic (agent product with separation), Pi (Austrian coding agent), OpenClaw.
• Other people referenced in the talk (transcribed): Last/Lars Gammel (leads Vercel’s AI SDK — name/numbers may be mis-transcribed), Mario (speaker about Pi), Peter (speaker for OpenClaw).

Note: some numeric and name details come from auto-generated subtitles and may be inaccurate.