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May 9, 2026

1 min read

When Discovery Moves From Search to Agents

By Cristiano Pierry

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Running several agents in parallel made agent-mediated discovery feel less abstract: software can explore and compare before a person sees the options.

aiproduct-managementai-agentssearchdiscovery
A drawn interface lists artifacts and background agents exploring a project.

I have been using frontier coding tools to understand what they change about software development and how people may eventually interact with services, apps, and content.

Right now I have six OpenAI Codex subagents working on one project. They are exploring different files, checking assumptions, and helping me think through the structure in parallel. The experience feels like a small research team returning with work I can inspect.

That made an emerging discovery pattern feel more concrete. If agents can explore options, compare them, and filter what they bring back, a person may no longer perform every search manually. Some part of discovery happens before the available choices reach the consumer.

The discovery surface may move from a search box to an agent acting on the person’s behalf.

Several candidate experiences are collected and inspected before selected options reach the user’s workspace.
Discovery shifts when agents explore, compare, and filter on the consumer’s behalf.

I do not know how quickly that behavior will become common across consumer products. The question for businesses built on feeds, search, or recommendations is already useful: what information and controls would let an agent represent the service accurately before it presents an option to a person?


This writing reflects my personal perspectives on product management, AI, and content discovery. It does not represent the official position of my employer or any affiliated organization.