The next rung in AI is agent managers, not just better task-completing agents
pzakin · x · 2026-07-27
The author argues that AI progress can be seen as a ladder of abstraction: from writing code, to pairing with agents, to writing specs. Each step shifts leverage upward and forces incumbents and startups to keep climbing.
The next step, in the author’s view, is moving from task-completing agents to task-managing agents. They outline four primitives worth watching:
- Self-healers/improvers: agents that ingest business signals such as feedback, analytics, or sensor data and trigger automated responses.
- Sims: using simulation and synthetic scenarios instead of waiting for production signals.
- Explorers: long-running agents that search for new ideas under high-level goals.
- Taste replicators: systems that encode a person’s judgment or design taste so agents can act with that preference embedded.
The post also mentions experimentation with GEPA for prompt optimization.
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