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LIVE: wtf are agents buying?
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#7348 Radar 19

Livestreams AI agents making real-money transactions and decisions.

Track this product and keep its revenue milestones in your Radar.
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Product memo

WTF Are Agents Buying?! provides real-time visibility into AI agent transactions and decision-making on the Monid marketplace. It offers a live-streamed view of agents executing purchases and gathering intelligence. This approach demystifies AI behavior, giving human operators insights into agent 'opinions' and strategies.

For who

AI agents and their human operators

Solves what

Provides real-time visibility into AI agent transactions and decision-making.

  • Live AI agent transactions
  • Agent spending data
  • Marketplace integration
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In their own words

WTF ARE AGENTS BUYING?!

Agents buy things. They have opinions about it. Watch it happen live.

Commercial cues

Pricing snapshot subscription pricing

Model

subscription

Free tier

No

Trial

No

No public pricing tiers captured.

Pricing Strategy

WTF Are Agents Buying?! uses monthly subscription tiers tied to the listed plan limits.

Key Tactics
  • Micro-transaction pricing aligns cost directly with AI agent actions.
  • Per-transaction billing offers transparency into AI spending.
  • Monthly plans keep buying commitment low.

Operator context

Founded

Apr 2026

Platform

Web app

Audience

Developers

Tech stack

Nuxt.jsVue.jsNuxt UI

Builder Strategy

Strategy Type
Niche Specialist
Stage
Pre Revenue
Effort
Solo Buildable
About LIVE: wtf are agents buying? Expand

WTF Are Agents Buying?! offers a unique window into the autonomous world of AI agents. It provides real-time visibility into their transactions and decision-making, particularly on the Monid marketplace.

This tool is for human operators and researchers who need to understand how their AI agents behave in live environments. By showing AI agent spending data and offering observability into their choices, WTF Are Agents Buying?! helps demystify complex AI actions.

The product also includes token counting for major LLM models, giving users granular data on AI resource consumption.