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Union Square Ventures' Nick Grossman argues the dominant mental model for AI is shifting. Instead of thinking of agents as personified 'employees' to hire, we should see them as cloud infrastructure. Businesses will programmatically spawn and orchestrate thousands of agents as integral parts of their core systems.
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As AI evolves from single-task tools to autonomous agents, the human role transforms. Instead of simply using AI, professionals will need to manage and oversee multiple AI agents, ensuring their actions are safe, ethical, and aligned with business goals, acting as a critical control layer.
The fundamental model of AI use is changing. It's moving from 'assisted' AI, which helps humans with their tasks, to 'agentic' AI, where autonomous systems perform tasks. This paradigm shift requires new methods for adoption, management, and measuring success, moving from 'seats' to 'tokens'.
The future of work isn't just using AI as a tool, but managing it. Greg Brockman describes a paradigm where users act as high-level overseers, setting goals for a "fleet of agents" that handle the low-level execution, abstracting away details like clicking buttons or writing specific formulas.
Building a single AI tool is not enough. The real value lies in becoming the 'conductor,' creating a system that orchestrates multiple specialized AI agents to complete complex workflows. Whoever owns this coordination layer owns the entire value flow.
The number of AI agents will soon vastly exceed human employees. This requires a fundamental shift in software development, prioritizing API-first design, reliability, and machine-to-machine interaction over traditional human-centric user interfaces.
Recent updates from Anthropic's Claude mark a fundamental shift. AI is no longer a simple tool for single tasks but has become a system of autonomous "agents" that you orchestrate and manage to achieve complex outcomes, much like a human team.
The future of software isn't just AI-powered features. It's a fundamental shift from tools that assist humans to autonomous agents that perform tasks. Human roles will evolve from *doing* the work to *orchestrating* thousands of these agents.
The paradigm for employees shifts from being an individual contributor to being a manager of AI agents. Success is no longer just direct output, but the ability to effectively set up, direct, and manage a team of autonomous agents to achieve goals.
Drawing a parallel to the microservices boom, enterprises will soon deploy thousands of AI agents, creating immense operational complexity. The most valuable future products will be those that, like Datadog for microservices, provide governance, monitoring, and orchestration for this sprawling agentic workforce.
The next frontier in AI is not just developing individual agents, but orchestrating teams of them. Users will move from dialoguing with a single chatbot to managing multiple agents working in parallel on complex, long-running workflows. This becomes a new core skill for knowledge workers.
