Ask HN: What are some actual use cases of AI Agents right now?

The article discusses the use of AI agents in orchestrating fully automated web scrapers. Instead of using a single, large, general-purpose agent, the approach involves using several smaller agents, each responsible for a specific sub-task in the workflow. These agents are medium-sized LLM prompts with context and a set of functions to call. Tasks include website loading, navigation, network analysis, validation, and data transformation.

The main challenge lies in scaling this system. While it works well for a few data sources with low complexity, applying it to thousands of websites in a reliable, scalable, and cost-efficient manner is significantly more difficult.

Key takeaways

The AI agents are used for orchestrating fully automated web scrapers, with each agent handling a specific sub-task.
Each agent is a medium-sized LLM prompt with context and a set of functions to call.
Tasks handled by the agents include website loading, navigation, network analysis, validation, and data transformation.
The main challenge is scaling this system to handle thousands of websites in a reliable, scalable, and cost-efficient way.

Ask HN: What are some actual use cases of AI Agents right now?

Key takeaways

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